CN113555111A - Doctor-patient joint decision multi-subject negotiation method, system and readable storage medium - Google Patents
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Abstract
The invention discloses a doctor-patient joint decision multi-subject negotiation method, a doctor-patient joint decision multi-subject negotiation system and a readable storage medium, wherein the method comprises the following steps: acquiring the preference and behavior characteristics of doctors and patients, and constructing fuzzy constraint and a fuzzy constraint satisfaction function; constructing and generating a doctor agent behavior model and a patient agent behavior model and a distributed fuzzy constraint satisfaction problem based on the fuzzy constraint and the fuzzy constraint satisfaction function; the distributed fuzzy constraint satisfaction problem is generated according to a doctor-patient co-decision problem, wherein the doctor-patient co-decision problem is an issue that a doctor agent and a patient agent need to negotiate in a decision making process; and carrying out negotiation between the doctor agent and the patient agent based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem until the negotiation is successful to generate a common negotiation result or fails and the negotiation is terminated.
Description
Technical Field
The present invention relates to the field of negotiation of doctor-patient treatment schemes, and in particular, to a doctor-patient co-decision multi-topic negotiation method, system and readable storage medium.
Background
With the development of the bio-psycho-socio-medical model and the increasing awareness of the public laws and medical participation in society, patients are more concerned about medical procedures and more expected to participate in medical decisions. The existing negotiation based on a game theory method is as follows: the method and the tool of the game theory are introduced into the agent negotiation, the agent negotiation is regarded as the game, the game with the limited strategy of multi-person dynamic perfect but incomplete information mixing is realized, and the agent negotiation is realized by using the game theory to obtain a negotiation method with more realistic significance.
For this solution, the computational resources are always set to be infinite, and the solution is independent of computational theory. Therefore, such an approach inevitably involves a problem of computational complexity, since in many cases the problem solution is an NP problem (a non-deterministic polynomial puzzle). And the chess playing theory often makes some premise assumptions, such as that the participants are completely rational, the strategies are fixed, and the like, which greatly limits the research on agent negotiation.
Disclosure of Invention
In view of the above problems, the present invention provides a method, a system and a readable storage medium for doctor-patient joint decision multi-topic negotiation, so as to improve the above problems.
The embodiment of the invention provides a doctor-patient joint decision multi-topic negotiation method, which comprises the following steps:
acquiring the preference and behavior characteristics of doctors and patients, and constructing fuzzy constraint and a fuzzy constraint satisfaction function;
constructing and generating a doctor agent behavior model and a patient agent behavior model and a distributed fuzzy constraint satisfaction problem based on the fuzzy constraint and the fuzzy constraint satisfaction function; the distributed fuzzy constraint satisfaction problem is generated according to a doctor-patient joint decision problem, and the doctor-patient joint decision problem is an issue that a doctor agent and a patient agent need to negotiate in a decision making process;
and carrying out negotiation between the doctor agent and the patient agent based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem until the negotiation is successful to generate a common negotiation result or fails and the negotiation is terminated.
Preferably, the doctor-patient joint decision multi-topic negotiation method further comprises:
matching the common negotiation result with a treatment scheme recommendation model, taking a treatment scheme with larger similarity with the common negotiation result as a recommendation scheme, and sending the recommendation scheme to a doctor agent and a patient agent;
wherein the treatment plan recommendation model comprises a plurality of treatment plans.
Preferably, the negotiating between the doctor and the patient based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem specifically includes:
based on the distributed fuzzy constraint satisfaction problem, the doctor agent behavior model and the patient agent behavior model, one of the doctor agent and the patient agent determines whether yielding is performed or not and the degree of yielding in the negotiation process through the internal state and the environmental state of the one of the doctor agent and the patient agent and the response state of the other one of the doctor agent and the patient agent so as to generate a yielding value;
generating a feasible solution set and an expected solution set based on a fuzzy constraint network, the doctor agent behavior model, the patient agent behavior model and the latest behavior state of the doctor agent and the patient agent; the latest behavior state is obtained according to an overall satisfaction threshold and the yield value;
and generating an asking price according to the feasible solution set and the expected solution set and sending the asking price to the other party of the doctor agent and the patient agent until the negotiation is agreed or fails.
Preferably, the internal state is obtained from satisfaction of the latest asking price and closeness of a set of alternative solutions;
the environment state comprises a time constraint, and the time constraint is obtained according to the current negotiation time and the negotiation deadline;
the response status is obtained based on the degree of difference between the asking price of the previous round and the most recently received counter-offer.
Preferably, in the negotiating between doctor and patient step based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem, the doctor agent and the patient agent negotiate by sending and receiving messages, the messages including:
ask, the negotiator sends an Ask or offer to his opponent asking for the value of an issue relevant to the treatment plan;
tell, the negotiator sends the counter-offer to the opponent;
accept, the negotiator accepts counter-offers offered by the opponent and terminates the negotiation;
reject, the negotiator sends rejection information to the other party for self consideration, refuses to accept the bid of the other party and terminates the negotiation;
an Agree, wherein the negotiator temporarily accepts the price of the other party and waits for the confirmation of the other party; and/or
Abort, the negotiator selects to exit the negotiation without new asking price generation, and the negotiation is terminated.
Preferably, the distributed fuzzy constraint satisfaction problem is generated according to a doctor-patient joint decision problem, and specifically:
modeling based on the doctor-patient co-decision issues, and constraints and associations between doctor and patient agents and/or between issues and issues generates a distributed fuzzy constraint satisfaction problem.
The embodiment of the invention also provides a doctor-patient decision-making bilateral multi-topic negotiation system, which comprises:
the behavior model modeling unit is used for acquiring the preference and behavior characteristics of doctors and patients, constructing a modeling fuzzy constraint satisfaction function, and combining fuzzy constraint construction to generate a doctor agent behavior model and a patient agent behavior model;
the negotiation unit is used for carrying out negotiation between the doctor agent and the patient agent based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem so as to generate a common negotiation result; or
The negotiation unit is also used for carrying out negotiation between the doctor agent and the patient agent based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem until the negotiation is successful or failed and the negotiation is terminated;
the distributed fuzzy constraint satisfaction problem is generated according to a doctor-patient joint decision problem, and the doctor-patient joint decision problem is a question that doctors and patients need to negotiate in the decision process.
Preferably, the doctor-patient co-decision bilateral multi-topic negotiation system further includes:
the treatment scheme recommending unit is used for matching the common negotiation result with a treatment scheme recommending model, taking a treatment scheme with larger similarity with the common negotiation result as a recommending scheme and sending the recommending scheme to a doctor agent and a patient agent; wherein the treatment plan recommendation model comprises a plurality of treatment plans.
Preferably, the negotiation unit includes:
the yield value calculation module is used for determining whether to yield and the degree of yield to generate a yield value in the negotiation process according to the internal state and the environment state of one of the doctor agent and the patient agent and the response state of the other one of the doctor agent and the patient agent based on the distributed fuzzy constraint satisfaction problem, the doctor agent behavior model and the patient agent behavior model;
a solution set calculation module for generating a feasible solution set and an expected solution set based on a fuzzy constraint network, the doctor agent behavior model, the patient agent behavior model and the latest behavior state of the doctor agent and the patient agent; the latest behavior state is obtained according to an overall satisfaction threshold and the yield value;
and the asking price generating module is used for generating asking prices according to the feasible solution sets and the expected solution sets and sending the asking prices to the other party of the doctor agent and the patient agent until the negotiation is agreed or fails.
An embodiment of the present invention further provides a computer-readable storage medium, which stores a computer program, where the computer program can be executed by a processor of a device in which the computer-readable storage medium is located, so as to implement the doctor-patient joint decision multi-topic negotiation method described above.
Through the embodiment, the invention constructs the doctor agent behavior model and the patient agent behavior model based on the preference and behavior characteristics of doctors and patients and through the fuzzy constraint network, and provides the preference of simulating actual doctors and patients in the negotiation process for the doctor agent and the patient agent. And the doctor-patient joint decision problem is modeled into a distributed fuzzy constraint satisfaction problem based on a doctor agent and a patient agent, so that a discussion and negotiation basis is provided for the doctor-patient joint decision problem.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a flowchart illustrating a doctor-patient decision-making multi-topic negotiation method according to the present invention.
Fig. 2 and fig. 3 are schematic diagrams of doctor-patient agent and patient agent interactive negotiation of the doctor-patient decision-making multi-topic negotiation method of the present invention.
FIG. 4 is a schematic diagram of a recommendation model of the doctor-patient joint decision multi-topic negotiation method of the present invention.
Fig. 5 is a schematic diagram of the negotiation of the topic in the treatment protocol of the first embodiment of the present invention.
Figure 6 is a graph showing the treatment recommendation for different weights in a first embodiment of the present invention.
Fig. 7 is a diagram illustrating the joint overall satisfaction of different policies under different negotiation issues of the second embodiment of the present invention.
Fig. 8 shows negotiation turns diagrams of different policies under different negotiation issues of a second embodiment of the invention.
Fig. 9 and 10 are schematic diagrams of 10 doctor agents and 10 patient agents simulating joint overall satisfaction and negotiation rounds for 100 groups of doctor-patient negotiations according to a third embodiment of the present invention.
Fig. 11 is a schematic structural diagram of an electronic device capable of performing a doctor-patient joint decision multi-topic negotiation method according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
An embodiment of the present invention provides a doctor-patient joint decision multi-topic negotiation method, wherein the negotiation method performs multi-topic joint negotiation on both sides of the doctor-patient. In other embodiments, it may be the case that a multi-topic co-negotiation is performed. Referring to fig. 1, the method includes:
s100, acquiring the preference and behavior characteristics of doctors and patients, and constructing fuzzy constraint and a fuzzy constraint satisfaction function.
S200, constructing and generating a doctor agent behavior model and a patient agent behavior model based on the fuzzy constraint and the fuzzy constraint satisfaction function, and solving the problem of distributed fuzzy constraint satisfaction.
In this embodiment, the corresponding preferences and behavior characteristics are entered in the predefined forms by the doctor and the patient at the doctor client and the patient client, respectively. In the doctor-patient joint decision making process, according to different characteristics of psychology, behaviors and the like of doctors and patients, a behavior framework and a model for realizing doctor agents and patient agents and a negotiation protocol to be observed by a negotiation party are designed, so that the doctor agents and the patient agents can perform sufficient negotiation on behalf of the doctors and the patients to reach the agreement.
And S300, carrying out negotiation between the doctor agent and the patient agent based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem until the negotiation is successful or failed and terminating the negotiation. The distributed fuzzy constraint satisfaction problem is generated according to doctor-patient co-decision questions, and the doctor-patient co-decision questions are questions which need to be negotiated by a doctor agent and a patient agent in a decision making process.
In this embodiment, specifically, the doctor-patient common decision problem is constructed as a distributed fuzzy constraint satisfaction problem by using the doctor-patient common decision feature:
in the distributed fuzzy constraint satisfaction problem, there are two main types of agents, namely, a Doctor Agent (DA) and a Patient Agent (PA), which represent a doctor and a patient respectively in the negotiation process, and the relation between the doctor and the patient is CN, and the three constitute a triple (DA, PA, CN). All constraints in a Distributed Fuzzy Constraint Network (DFCN) are satisfied by specifying fuzzy relationships between doctor agents and patient agents. Defining a DFCN (U, X, C) in the patient co-resolution problem as Nk＝(Uk,Xk,Ck) Belonging to agent k. In bilateral multi-topic negotiation for doctor-patient decision making, there are mainly two fuzzy constraint networks, i.e. NDA＝(UDA,XDA,CDA) And NPA＝(UPA,XPA,CPA) Belonging to a doctor agent and a patient agent, respectively. Wherein the content of the first and second substances,
u: representing the domain of discourse of the fuzzy constraint network N;
x: a set of non-repeating object tuples representing N representing the beliefs, intentions, wishes of the agent;
c: the fuzzy constraint set is represented, and all the constraints suffered by the agent, such as priority constraints, target constraints and the like.
In step S300, the negotiating between the doctor and the patient based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem specifically includes:
s301, based on the distributed fuzzy constraint satisfaction problem, the doctor agent behavior model and the patient agent behavior model, one of the doctor agent and the patient agent determines whether to yield and the degree of yielding to generate a yield value in a negotiation process through the internal state and the environment state of the doctor agent and the patient agent and the response state of the other party.
In this embodiment, the physician agent and the patient agent interact by asking and counter-asking each other until the parties agree on all issues, or until someone exits the negotiation due to the limits of a satisfaction threshold or some external factor, i.e. for the purpose of making a common decision or until the common negotiation terminates due to a failure.
In this embodiment, one side of the agent determines whether to yield and the degree of yielding in the following negotiation by evaluating the response status of the opponent, the internal status of the agent and the environmental status of the agent. The response state o of the opponent can be obtained from the degree of difference between the previous round ask a and the most recently received counter-offer B:
σ＝1-(G(A0,B0)-G(A,B))/G(A0,B0)
wherein A is0And B0Representing initial asking and counter-asking prices, G (A, B) referring to the negotiation subject IiThe distance measurement between the ask A and the counter-offer B on the epsilon X is calculated by the following formula:
wherein A isiAnd BiIndicates A, B is negotiating topic IiE probability distribution over X, NiIs expressed as NiA negotiation topic, i.e. a negotiation target.
The internal state i of the agent itself, relating to the satisfaction level p related to the latest asking price a and the closeness δ of a set of alternative solutions, where:
δ＝1-(ρ-ε)
in the above formula, S*Represents the desired solution of the agent, Ψ (S)*) Represents it to the solution S*Is used, epsilon represents the overall satisfaction threshold. Fi(S) represents the fuzzy membership function of the ith subject in the solution S, which is directly set by the doctor or the patient, and can flexibly and effectively represent the preference of the doctor and the patient to each negotiated subject, NiIndicates the total number of negotiation issues, wiIs the weight of the ith issue.
In the doctor-patient joint decision negotiation process, the environment constraint E borne by the agent is mainly time constraint. The time constraint experienced by the agent is expressed as:
in the above formula, tnowIndicating the current negotiation time, tmaxDenotes the negotiation deadline, t denotes the time constraint imposed on the agent during the negotiation, α, β are constants, and β>1， 0≤α≤1。
According to the formula, the adversary response state O, the internal state I of the adversary response state O, and the environment state E can be calculated, and the yielding value is calculated. The formula for calculating the yield value delta epsilon in the agent negotiation is as follows:
Δε＝(μσ(σ),μρ(ρ),μδ(δ),μt(t))ω
μσ(σ)，μρ(ρ)，μδ(delta) and mut(t) respectively represents yielding expectations according to the difference, satisfaction, closeness, and time constraints, ω being related to the negotiation convergence speed.
S302, generating a feasible solution set and an expected solution set based on a fuzzy constraint network, the doctor agent behavior model, the patient agent behavior model and the latest behavior state of a doctor agent and a patient agent; the latest behavior state is obtained according to an overall satisfaction threshold and the yield value.
In this embodiment, doctor agent obfuscation based on the aboveConstraint network and patient agent obfuscate the intent of constraint network N, physician and patient
The latest behavior state epsilon of the agent*The corresponding feasible solution set is generated. The feasible solution P is defined as follows:
where Ψ (S) represents the satisfaction of the target set of agents in N. Given the ask B and the set of feasible solutions P, the desired solution S*The following conditions were followed for the selection of (c):
S*＝arg(maxS∈PH(S,B))
h (S, B) is a utility function used to evaluate the similarity of the feasible solution S ∈ P against the reduction B, and is defined as follows:
in the above formula, W1Is a preference function of the agent on topic i, W2Is a similarity function, ω, that calculates the distance between the solution S and the counter-offer B1And omega2Respectively, represent weights associated with preference, similarity, and ω1And omega2The value is selected in relation to the negotiation strategy adopted by the agent: 1) omega1≤1.0,ω2≤1.0,ω1＝ω2A win-win strategy; 2) omega1≤1.0,ω2≤ 1.0,ω1＜ω2Is a collaborative strategy; 3) omega1≥1.0,ω2≥1.0,ω1>ω2It is a competitive strategy.
The adoption of the win-win strategy for negotiation means that the agent considers the benefit of the agent and also considers the benefit of the opponent agent, and the negotiation result of 'satisfaction' of both parties is expected to be obtained; the use of the cooperation strategy indicates that the agent will consider the benefit of the opponent agent more in the negotiation process so as to reach the agreement as soon as possible; the negotiation using the competition strategy shows that the agent pays more attention to the self-benefit acquisition in the negotiation, and hopes to maximize the self-acquired benefit.
S303, generating an asking price according to the feasible solution set and the expected solution set, and generating a transmittable message according to the asking price and the negotiation protocol.
And S304, based on the negotiation termination condition, sending the transmittable message to the other party of the doctor agent and the patient agent until the negotiation is agreed or fails.
In the present embodiment, the topic I is considered based on the feasible solution set P and the desired solution set SiE.g. set of asking price of X
Is generated as follows:
in the above formula, issue Iie.X ask and set A*Middle element
In response to this, the mobile terminal is able to,
is value
The edge probability distribution in space X can be defined as:
wherein the content of the first and second substances,
is that
In space
Round columnForm extension, XiIs the object of issue i, NXIs the total target number.
Finally, the negotiation is terminated: the exchange of asking and refunding prices between the doctor agent and the patient agent is continued until agreement is reached or no new asking/refunding price is generated, i.e. the negotiation is terminated in both agreement or failure. Given a feasible solution set P and a reduction B, the conditions to be met for negotiation to reach agreement are:
Ψ(S*)≥ε*
the negotiation failure meets the conditions that:
ε*≤0 or P＝□
in the above embodiments, all message types and contents exchanged by the doctor agent and the patient agent during the negotiation protocol are definitions, representations, processing and semantic interpretation of the Agent Communication Language (ACL), which is mainly used to process the interaction between the agents during the negotiation process, which is essentially a rule that all agents must comply with. In doctor-patient co-decision problems, doctor and patient agents may negotiate by sending or receiving various types of messages including one or more of the following:
ask (negotiator, opponent, Ask): the negotiator sends an ask or offer to his opponent asking for the value of the topic associated with the treatment plan.
Tell (negotiator, opponent, counter-offer): the negotiator sends the counter-offer to the opponent.
Accept (negotiator, opponent, counter-offer): the negotiator accepts counter-offers offered by the opponent and terminates the negotiation.
Reject (negotiator, opponent, ask): the negotiator, in view of itself, sends a refusal message to the other party, refuses to accept the offer of the opponent and terminates the negotiation.
Agree (negotiator, opponent, ask): the negotiator temporarily accepts the price of the other party and waits for confirmation of the other party.
Abort (negotiator, opponent): the negotiator selects to exit the negotiation without new asking price generation and the negotiation is terminated.
In one embodiment, the doctor-patient decision-making multi-topic negotiation method further includes:
and S400, matching the common negotiation result with a treatment scheme recommendation model, taking the treatment scheme with larger similarity with the common negotiation result as a recommendation scheme, and sending the recommendation scheme to a doctor agent and a patient agent. Wherein the treatment plan recommendation model comprises a plurality of treatment plans.
In this embodiment, in the doctor-patient decision making, the purpose of negotiation between the doctor and the patient is to obtain some treatment schemes that meet the preferences of both parties and the actual conditions of the patient, rather than reaching the agreement on the value of each question. Therefore, the embodiment designs a recommendation model, which converts the negotiation result of the doctor agent and the patient agent into a treatment scheme in accordance with reality for the doctor and the patient to select. In this recommendation model, first, a doctor and a patient share basic information, and the doctor diagnoses a condition of the patient based on the basic information. Then, a treatment regimen appropriate for the patient's condition is selected from the treatment guidelines. Similarity between the negotiation result and the treatment plan is then calculated and ranked. And finally, sending the treatment scheme with the recommendation information to the doctor and the patient.
Specifically, assuming that the doctor agent and the patient agent agree on the values of the respective issues through negotiation, a solution set S with consistent preference needs to be obtained*Similarity matching is carried out with each treatment scheme in the existing treatment schemes, and the similarity between each treatment scheme and each treatment scheme is calculated as follows:
wherein, wiIndicating the associated topic weights (e.g., average of physician agent and patient agent preference weights) in the treatment plan, Si(S*) The method is the similarity calculation of the negotiation item level, namely the fuzzy membership function corresponding to each negotiation item in the treatment scheme.
In order to more clearly illustrate the present invention, the following description will describe the specific embodiments, model structures and algorithm features of the method.
Firstly, according to the doctor-patient joint decision characteristics, the doctor-patient joint decision topic is converted and modeled into a distributed fuzzy constraint satisfaction problem, and complete doctor-patient joint decision negotiation content is determined, as shown in fig. 2. The doctor-patient co-decision issues are modeled as a distributed fuzzy constraint satisfaction problem of fuzzy constraints existing between agents and other agents, and between issues and other issues. The goal of each agent is to establish a behavior model by fuzzy constraint, and the mutual constraint relation between each agent determines whether a solution meeting all constraint conditions of the satisfaction degree problem of the distributed fuzzy constraint exists. Doctor agents and patient agents can solve the distributed fuzzy constraint satisfaction problem through negotiation, and further solve practical application problems.
Then, an FCAN Negotiation model (Fuzzy Constraint-directed Agent-based Negotiation model) for doctor-patient common decision is constructed, and a behavior model for doctor Agent and patient Agent Negotiation decision is constructed according to doctor and patient preferences and behavior characteristics, so that the doctor Agent and the patient Agent can carry out interactive Negotiation with an opponent through the steps of abduction value calculation, feasible solution generation, asking price generation, Negotiation termination condition judgment and the like. In the process, the doctor agent and the patient agent firstly determine whether to give way in the next round of negotiation and the degree of the giving way, namely the magnitude of the giving way value, by evaluating the response state of the hand agent, the internal state of the doctor agent and the environmental state of the patient agent. And then, determining a new behavior state based on the size of the yield value, generating a group of feasible solutions, and selecting an optimal solution for generating the asking price/counter-offer to be sent to the opponent agent. When this ask/counter-offer cannot be accepted by the opponent's agent, the agent will counter-offer based on the negotiation policy and consider solutions with the same level of satisfaction, or provide less satisfactory solutions, which are sent to the opponent. The above negotiation process is repeated until a termination condition (agreement or loss of agreement) is met. The specific negotiation steps and negotiation protocol are shown in fig. 3.
Finally, in the actual doctor-patient decision making, the purpose of the doctor-patient is to obtain the treatment scheme meeting the preferences of both parties and meeting the actual condition through negotiation, and the agreement on the values of all the issues is not always achieved. Therefore, the invention converts the negotiation result of the agent into a treatment plan corresponding to reality for selection by doctors and patients. Therefore, the invention provides a treatment scheme recommendation model to process the negotiation result, so as to achieve the purpose of recommending the 'best' treatment scheme. Firstly, a mapping table between a treatment scheme and negotiation topic values is constructed according to treatment guidelines and expert opinions. And then, carrying out similarity matching on the agent negotiation result and the existing treatment scheme, and sequencing the similarity values. And finally, selecting the treatment scheme with the maximum similarity for recommendation, or directly sending the arrangement result to an agent. The model is generally referred to in the description of fig. 4.
Based on the above, the embodiment of the invention constructs the doctor agent behavior model and the patient agent behavior model based on the preference and behavior characteristics of doctors and patients and through the fuzzy constraint network, and provides the preference of simulating actual doctors and patients in the negotiation process for the doctor agent and the patient agent. The doctor-patient co-decision problem is modeled into a distributed fuzzy constraint satisfaction problem based on a doctor agent and a patient agent in step S200, and an issue negotiation basis is provided for the doctor-patient co-decision problem.
Through the negotiation behaviors of the doctor agent and the patient agent and the negotiation protocol followed in the steps S301-S304, a negotiation model is provided for solving the doctor-patient joint decision making issue, the doctor-patient joint decision making process can be effectively simulated and realized, and various problems existing in the current doctor-patient joint decision making implementation process are solved.
The consultation result of the doctor agent and the patient agent is converted into a specific treatment scheme for the selection and reference of the doctor and the patient through the step S400, and the purpose of doctor-patient joint decision is further realized.
The FCAN negotiation model and the treatment recommendation model are provided for realizing doctor-patient co-decision, and relieving or even eliminating the problems of unequal doctor-patient negotiation positions, lack of doctor-patient communication skills, lack of patient medical knowledge, limited doctor visit time and the like in the implementation process of the doctor-patient co-decision. On one hand, the doctor agent and the patient agent reach the agreement about the concerned problems of the doctor and the patient through continuous interaction, on the other hand, the negotiation result is converted into a feasible treatment scheme through the calculation of the recommendation degree of the treatment scheme, and the treatment scheme can be selected and referred by the doctor and the patient.
In the following, the present invention further explains the above embodiments by three specific embodiments, specifically, this embodiment is exemplified by the decision-making of pediatric asthma patients.
The first embodiment is as follows: assuming a 9 year old infant, the severity of asthma can reach level 4, and the physician and the patient (family members of the patient) need to set corresponding preferences at the time of medical visit, and consult with the physician and the patient agents in their own right. According to the agent-based doctor-patient co-negotiation and recommendation model provided in fig. 2 and 4, a doctor agent and a patient agent can be constructed to negotiate on behalf of a doctor and a patient, respectively. The doctor agent and the patient agent negotiate according to the steps and protocols provided in fig. 3, and finally obtain a negotiation result. A treatment plan (refer to 2016 edition of guidelines for the diagnosis and prevention of bronchial asthma in children) mapping table is constructed as shown in FIG. 5 (wherein: ICS: inhaled glucocorticoid; LTRA: leukotriene receptor antagonist; LABA: long-acting beta 2 receptor agonist; THP: theophylline; ICS/LABA: inhaled glucocorticoid and long-acting beta 2 receptor agonist combined preparation), and the negotiation result is matched with the existing treatment plan to obtain the corresponding recommendation score as shown in FIG. 6. The treatment regimen with the highest final recommendation is: middle and high dose ICS/LABA + LTRA. The second embodiment is as follows: it is under the situation that the negotiation questions are increased, to the three negotiation strategies involved in the above proposed method of the present invention: and performing collaboration, win-win and competition comparison, and mainly comparing the final joint overall satisfaction value of the negotiation result and the number of rounds required by the negotiation. It can be seen from fig. 7 and 8 that the agent can obtain a relatively high joint overall satisfaction value by using the competition policy, but the number of negotiation rounds required is relatively large. The negotiation round required for the agent to use the collaboration policy is minimal, but the obtained joint overall satisfaction value is minimal. The agent uses the combined overall satisfaction value under the win-win strategy and the required number of negotiation rounds to be in the middle of the competition strategy and the cooperation strategy. Overall, the outcome of the agent using the win-win strategy is optimal. In addition, as the number of negotiation issues increases, the joint overall satisfaction value of the negotiation results decreases, and the number of required negotiation rounds increases.
In the third embodiment, 10 doctor agents and 10 patient agents with different preferences are used for simulating 100 groups of doctors to negotiate, all agents use a win-win strategy in the process, negotiation results are analyzed when negotiation issues increase, as shown in the attached figures 9 and 10, when negotiation issues increase, the negotiated joint overall satisfaction value is reduced, the required negotiation rounds are increased, and the conclusion is verified again.
An embodiment of the present invention provides a doctor-patient co-decision bilateral multiple-issue negotiation system, which is applied to the electronic device 1, and referring to fig. 11, the doctor-patient co-decision bilateral multiple-issue negotiation system includes a behavior model modeling unit 11, a negotiation unit 12, and a treatment plan recommendation unit 13, where the behavior model modeling unit 11 is configured to obtain preferences and behavior characteristics of doctors and patients, and construct and generate doctor agent behavior models and patient agent behavior models according to fuzzy constraints.
The negotiation unit 12 is used for performing negotiation between the doctor agent and the patient agent based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem to generate a common negotiation result; the distributed fuzzy constraint satisfaction problem is generated according to a doctor-patient co-decision problem, and the doctor-patient co-decision problem is an issue that a doctor agent and a patient agent need to negotiate in a decision making process.
The treatment plan recommending unit 13 is configured to match the common negotiation result with a treatment plan recommending model, and send a treatment plan with a larger similarity to the common negotiation result as a recommended plan to the doctor agent and the patient agent. Wherein the treatment plan recommendation model comprises a plurality of treatment plans.
And the negotiation unit is also used for carrying out negotiation between the doctor agent and the patient agent based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem until the negotiation is successful or failed and the negotiation is terminated.
In one embodiment, the negotiation unit includes a yield value calculation module 121, a solution set calculation module 122, and an ask price generation module 123.
The yielding value calculating module 121 is configured to determine, based on the distributed fuzzy constraint satisfaction problem, the doctor agent behavior model and the patient agent behavior model, whether to yield and a degree of yielding to generate a yielding value in a negotiation process by using an internal state and an environmental state of one of the doctor agent and the patient agent and a response state of the other of the doctor agent and the patient agent.
A solution set calculation module 122 for generating a feasible solution set and a desired solution set based on the fuzzy constraint network, the doctor agent behavior model, the patient agent behavior model, and the latest behavior state of the doctor agent and the patient agent; the latest behavior state is obtained according to an overall satisfaction threshold and the yield value.
The asking price generating module 123 is used for generating asking prices according to the feasible solution sets and the expected solution sets and sending the asking prices to the other party of the doctor agent and the patient agent until the negotiation is agreed or the negotiation is lost.
The implementation methods and implementation principles not mentioned by each unit and each module in the doctor-patient joint decision bilateral multiple-issue negotiation system can be combined with the methods mentioned in the doctor-patient joint decision multiple-issue negotiation method.
An embodiment of the present invention provides a computer-readable storage medium, which can be applied to the electronic device described above. The computer-readable storage medium includes a stored computer program, wherein when the computer program runs, the apparatus where the computer-readable storage medium is located is controlled to execute the doctor-patient co-decision multi-issue negotiation method according to the above embodiment.
Illustratively, the computer programs described herein can be divided into one or more modules that are stored in the memory and executed by the processor to implement the invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program in the implementation server device. For example, the doctor-patient co-decision bilateral multi-topic negotiation system in the above embodiments of the present invention.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an APPlication Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor is a control center of the light emitting unit brightness configuration method in the printer, and various interfaces and lines are used to connect the various parts of the whole method for implementing the light emitting unit brightness configuration method in the printer.
The memory can be used for storing the computer program and/or the module, and the processor realizes various functions of the doctor-patient joint decision multi-topic negotiation method by running or executing the computer program and/or the module stored in the memory and calling the data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, a text conversion function, etc.), and the like; the storage data area may store data (such as audio data, text message data, etc.) created according to the use of the user terminal, etc. Further, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Wherein, the module for realizing the service device can be stored in a computer readable storage medium if it is realized in the form of software functional unit and sold or used as a stand-alone product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may be implemented by a computer program, which may be stored in a computer-readable storage medium and used for implementing the steps of the embodiments of the method when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, etc. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
It should be noted that the above-described embodiments of the apparatus are merely schematic, where the units described as separate parts may or may not be physically separate, and the parts shown as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement it without inventive effort.
The above description is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A doctor-patient decision-making multi-topic negotiation method is characterized by comprising the following steps:
acquiring the preference and behavior characteristics of doctors and patients, and constructing fuzzy constraint and a fuzzy constraint satisfaction function;
constructing and generating a doctor agent behavior model and a patient agent behavior model and a distributed fuzzy constraint satisfaction problem based on the fuzzy constraint and the fuzzy constraint satisfaction function; the distributed fuzzy constraint satisfaction problem is generated according to a doctor-patient co-decision problem, wherein the doctor-patient co-decision problem is an issue that a doctor agent and a patient agent need to negotiate in a decision making process;
and carrying out negotiation between the doctor agent and the patient agent based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem until the negotiation is successful to generate a common negotiation result or fails and the negotiation is terminated.
2. The doctor-patient co-decision multi-topic negotiation method of claim 1, further comprising:
matching the common negotiation result with a treatment scheme recommendation model, taking a treatment scheme with larger similarity with the common negotiation result as a recommendation scheme, and sending the recommendation scheme to a doctor agent and a patient agent;
wherein the treatment plan recommendation model comprises a plurality of treatment plans.
3. The doctor-patient decision-sharing multi-topic negotiation method according to claim 1, wherein the negotiation between doctor and patient based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem is specifically:
based on the distributed fuzzy constraint satisfaction problem, the doctor agent behavior model and the patient agent behavior model, one of the doctor agent and the patient agent determines whether yielding and the degree of yielding to generate a yielding value in a negotiation process through the internal state and the environmental state of the one of the doctor agent and the patient agent and the response state of the other of the doctor agent and the patient agent;
generating a feasible solution set and an expected solution set based on a fuzzy constraint network, the doctor agent behavior model, the patient agent behavior model and the latest behavior state of the doctor agent and the patient agent; the latest behavior state is obtained according to an overall satisfaction threshold and the yield value;
and generating an asking price according to the feasible solution set and the expected solution set and sending the asking price to the other party of the doctor agent and the patient agent until the negotiation is agreed or fails.
4. The doctor-patient co-decision multi-topic negotiation method of claim 3, wherein said internal state is obtained from satisfaction of the latest asking price and closeness of a set of alternative solutions;
the environment state comprises a time constraint, and the time constraint is obtained according to the current negotiation time and the negotiation deadline;
the response status is obtained based on the degree of difference between the asking price of the previous round and the most recently received counter-offer.
5. The doctor-patient co-decision multi-topic negotiation method of claim 1, wherein in the step of negotiating between doctor and patient based on the doctor agent behavioral model, patient agent behavioral model and distributed fuzzy constraint satisfaction problem, the doctor agent and patient agent negotiate by sending and receiving messages, the messages comprising:
ask, the negotiator sends an Ask or offer to his opponent asking for the value of the topic associated with the treatment plan;
tell, the negotiator sends the counter-offer to the opponent;
accept, the negotiator accepts counter-offers offered by the opponent and terminates the negotiation;
reject, the negotiator sends the rejected information to the other party for self consideration, rejects to accept the offer of the opponent and terminates the negotiation;
an Agree, wherein the negotiator temporarily accepts the price of the other party and waits for the confirmation of the other party; and/or
Abort, the negotiator selects to exit the negotiation without new asking price generation, and the negotiation is terminated.
6. The doctor-patient co-decision multi-topic negotiation method according to claim 1, wherein the distributed fuzzy constraint satisfaction problem is generated according to a doctor-patient co-decision problem, specifically:
modeling based on doctor-patient co-decision questions, and constraints and linkages between doctor and patient agents and/or between issues and issues generates a distributed fuzzy constraint satisfaction problem.
7. A doctor-patient decision-making bilateral multi-topic negotiation system, comprising:
the behavior model modeling unit is used for acquiring the preference and behavior characteristics of doctors and patients, constructing a fuzzy constraint satisfaction function, and combining the fuzzy constraint construction to generate a doctor agent behavior model and a patient agent behavior model;
the negotiation unit is used for carrying out negotiation between the doctor agent and the patient agent based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem so as to generate a common negotiation result; the distributed fuzzy constraint satisfaction problem is generated according to a doctor-patient co-decision problem, wherein the doctor-patient co-decision problem is an issue that a doctor agent and a patient agent need to negotiate in a decision making process; or
And the negotiation unit is also used for carrying out negotiation between the doctor agent and the patient agent based on the doctor agent behavior model, the patient agent behavior model and the distributed fuzzy constraint satisfaction problem until the negotiation is successful or failed and the negotiation is terminated.
8. The doctor-patient co-decision bilateral multi-topic negotiation system of claim 7, comprising:
the treatment scheme recommending unit is used for matching the common negotiation result with a treatment scheme recommending model, taking a treatment scheme with larger similarity with the common negotiation result as a recommending scheme and sending the recommended scheme to a doctor agent and a patient agent, wherein the treatment scheme is a final common decision scheme;
wherein the treatment plan recommendation model comprises a plurality of treatment plans.
9. The doctor-patient co-decision bilateral multi-topic negotiation system of claim 7, wherein the negotiation unit comprises:
the yielding value calculating module is used for determining whether yielding and the degree of yielding to generate a yielding value in the negotiation process through the internal state and the environment state of one of the doctor agent and the patient agent and the response state of the other one of the doctor agent and the patient agent based on the distributed fuzzy constraint satisfaction degree problem, the doctor agent behavior model and the patient agent behavior model;
a solution set calculation module for generating a feasible solution set and an expected solution set based on a fuzzy constraint network, the doctor agent behavior model, the patient agent behavior model and the latest behavior state of the doctor agent and the patient agent; the latest behavior state is obtained according to an overall satisfaction threshold and the yield value;
and the asking price generating module is used for generating asking prices according to the feasible solution sets and the expected solution sets and sending the asking prices to the other party of the doctor agent and the patient agent until the negotiation is agreed or fails.
10. A computer-readable storage medium, characterized in that a computer program is stored, which is executable by a processor of a device in which the computer-readable storage medium is located, so as to implement the doctor-patient joint decision multiple issue negotiation method according to any one of claims 1 to 6.
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