FR3102260B1 - Apprentissage automatique multi-agents. - Google Patents

Apprentissage automatique multi-agents. Download PDF

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Publication number
FR3102260B1
FR3102260B1 FR1911581A FR1911581A FR3102260B1 FR 3102260 B1 FR3102260 B1 FR 3102260B1 FR 1911581 A FR1911581 A FR 1911581A FR 1911581 A FR1911581 A FR 1911581A FR 3102260 B1 FR3102260 B1 FR 3102260B1
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Prior art keywords
machine learning
agent
learning
cooperative
systems
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FR1911581A
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FR3102260A1 (fr
Inventor
Jonathan Bonnet
Florent Pajot
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Continental Automotive Technologies GmbH
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Continental Automotive France SAS
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/35—Clustering; Classification
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/105—Speed
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Software Systems (AREA)
  • Mathematical Physics (AREA)
  • General Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • Evolutionary Computation (AREA)
  • Biomedical Technology (AREA)
  • Health & Medical Sciences (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Transportation (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Computational Linguistics (AREA)
  • Mechanical Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Databases & Information Systems (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Traffic Control Systems (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

L’invention a pour objet des systèmes informatiques (100) et procédés (200) pour l’apprentissage automatique prédictif d’au moins une première caractéristique physique d’un système complexe du type électronique et/ou mécanique, tel un véhicule routier. Le principe général de l’invention est basé sur l’utilisation du paradigme des systèmes multi-agents dans la mise en œuvre de l’apprentissage automatique (« machine learning », en anglais) de manière décentralisée et ascendante. En pratique, l’invention recourt à l’approche des systèmes multi-agents adaptatifs coopératifs (« Adaptive Multi-Agent System » ou AMAS en anglais). Dans ce cadre, la présente invention concerne particulièrement le mécanisme d’apprentissage coopératif mise en œuvre par les différents agents. Figure 1
FR1911581A 2019-10-17 2019-10-17 Apprentissage automatique multi-agents. Active FR3102260B1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
FR1911581A FR3102260B1 (fr) 2019-10-17 2019-10-17 Apprentissage automatique multi-agents.

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR1911581 2019-10-17
FR1911581A FR3102260B1 (fr) 2019-10-17 2019-10-17 Apprentissage automatique multi-agents.

Publications (2)

Publication Number Publication Date
FR3102260A1 FR3102260A1 (fr) 2021-04-23
FR3102260B1 true FR3102260B1 (fr) 2023-02-17

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ID=69190970

Family Applications (1)

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FR1911581A Active FR3102260B1 (fr) 2019-10-17 2019-10-17 Apprentissage automatique multi-agents.

Country Status (1)

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FR (1) FR3102260B1 (fr)

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR3079954B1 (fr) * 2018-04-10 2023-03-10 Continental Automotive France Apprentissage automatique predictif pour la prediction d'une vitesse future d'un vehicule automobile en mouvement sur une route
FR3074123A1 (fr) * 2018-05-29 2019-05-31 Continental Automotive France Evaluation d'un style de conduite d'un conducteur d'un vehicule routier en mouvement par apprentissage automatique

Also Published As

Publication number Publication date
FR3102260A1 (fr) 2021-04-23

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