JP7155447B2 - ユーザが選択するアクションを予測するための学習済みモデルを生成するための方法等 - Google Patents
ユーザが選択するアクションを予測するための学習済みモデルを生成するための方法等 Download PDFInfo
- Publication number
- JP7155447B2 JP7155447B2 JP2022015807A JP2022015807A JP7155447B2 JP 7155447 B2 JP7155447 B2 JP 7155447B2 JP 2022015807 A JP2022015807 A JP 2022015807A JP 2022015807 A JP2022015807 A JP 2022015807A JP 7155447 B2 JP7155447 B2 JP 7155447B2
- Authority
- JP
- Japan
- Prior art keywords
- data
- action
- game state
- game
- user
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000009471 action Effects 0.000 title claims description 243
- 238000000034 method Methods 0.000 title claims description 33
- 230000004044 response Effects 0.000 claims description 6
- 230000000875 corresponding effect Effects 0.000 description 42
- 230000006870 function Effects 0.000 description 32
- 238000004891 communication Methods 0.000 description 19
- 238000013528 artificial neural network Methods 0.000 description 12
- 230000008569 process Effects 0.000 description 11
- 238000012549 training Methods 0.000 description 11
- 238000010586 diagram Methods 0.000 description 10
- 238000005516 engineering process Methods 0.000 description 10
- 238000006243 chemical reaction Methods 0.000 description 8
- 230000000694 effects Effects 0.000 description 6
- 238000003058 natural language processing Methods 0.000 description 6
- 230000002860 competitive effect Effects 0.000 description 3
- 230000010365 information processing Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 241000282412 Homo Species 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 239000000470 constituent Substances 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 238000003062 neural network model Methods 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- 239000013589 supplement Substances 0.000 description 2
- 230000006399 behavior Effects 0.000 description 1
- 230000002457 bidirectional effect Effects 0.000 description 1
- 230000001364 causal effect Effects 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000013136 deep learning model Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 230000000873 masking effect Effects 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000001537 neural effect Effects 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
- 239000013598 vector Substances 0.000 description 1
Images
Landscapes
- Electrically Operated Instructional Devices (AREA)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2022015807A JP7155447B2 (ja) | 2021-01-21 | 2022-02-03 | ユーザが選択するアクションを予測するための学習済みモデルを生成するための方法等 |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2021008098A JP7021378B1 (ja) | 2021-01-21 | 2021-01-21 | ユーザが選択するアクションを予測するための学習済みモデルを生成するための方法等 |
| JP2022015807A JP7155447B2 (ja) | 2021-01-21 | 2022-02-03 | ユーザが選択するアクションを予測するための学習済みモデルを生成するための方法等 |
Related Parent Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2021008098A Division JP7021378B1 (ja) | 2021-01-21 | 2021-01-21 | ユーザが選択するアクションを予測するための学習済みモデルを生成するための方法等 |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2022112513A JP2022112513A (ja) | 2022-08-02 |
| JP2022112513A5 JP2022112513A5 (enrdf_load_stackoverflow) | 2022-08-09 |
| JP7155447B2 true JP7155447B2 (ja) | 2022-10-18 |
Family
ID=87890830
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2022015807A Active JP7155447B2 (ja) | 2021-01-21 | 2022-02-03 | ユーザが選択するアクションを予測するための学習済みモデルを生成するための方法等 |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JP7155447B2 (enrdf_load_stackoverflow) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2019125154A (ja) | 2018-01-16 | 2019-07-25 | 株式会社日立ソリューションズ | 情報処理装置、会話データ処理方法及び情報処理システム |
| JP2019164753A (ja) | 2018-11-16 | 2019-09-26 | 株式会社Ｃｙｇａｍｅｓ | ゲームプログラムを検査するためのシステム、方法、プログラム、機械学習支援装置、及びデータ構造 |
| WO2019240047A1 (ja) | 2018-06-11 | 2019-12-19 | Ｎｅｃソリューションイノベータ株式会社 | 行動学習装置、行動学習方法、行動学習システム、プログラム、及び記録媒体 |
| US20200306638A1 (en) | 2019-03-29 | 2020-10-01 | Nvidia Corporation | Using playstyle patterns to generate virtual representations of game players |
| JP6812583B1 (ja) | 2020-02-28 | 2021-01-13 | 株式会社Ｃｙｇａｍｅｓ | ゲームスクリプトの作成を支援するためのシステム及び方法 |
-
2022
- 2022-02-03 JP JP2022015807A patent/JP7155447B2/ja active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2019125154A (ja) | 2018-01-16 | 2019-07-25 | 株式会社日立ソリューションズ | 情報処理装置、会話データ処理方法及び情報処理システム |
| WO2019240047A1 (ja) | 2018-06-11 | 2019-12-19 | Ｎｅｃソリューションイノベータ株式会社 | 行動学習装置、行動学習方法、行動学習システム、プログラム、及び記録媒体 |
| JP2019164753A (ja) | 2018-11-16 | 2019-09-26 | 株式会社Ｃｙｇａｍｅｓ | ゲームプログラムを検査するためのシステム、方法、プログラム、機械学習支援装置、及びデータ構造 |
| US20200306638A1 (en) | 2019-03-29 | 2020-10-01 | Nvidia Corporation | Using playstyle patterns to generate virtual representations of game players |
| JP6812583B1 (ja) | 2020-02-28 | 2021-01-13 | 株式会社Ｃｙｇａｍｅｓ | ゲームスクリプトの作成を支援するためのシステム及び方法 |
Also Published As
| Publication number | Publication date |
|---|---|
| JP2022112513A (ja) | 2022-08-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Côté et al. | Textworld: A learning environment for text-based games | |
| Liapis et al. | Orchestrating game generation | |
| Smith | Understanding procedural content generation: a design-centric analysis of the role of PCG in games | |
| Zhu et al. | Player-AI interaction: What neural network games reveal about AI as play | |
| Zagal et al. | Towards an ontological language for game analysis | |
| Zook et al. | Automated scenario generation: toward tailored and optimized military training in virtual environments | |
| Freiknecht et al. | Procedural generation of interactive stories using language models | |
| US20240058704A1 (en) | Method, etc. for generating trained model for predicting action to be selected by user | |
| Taveekitworachai et al. | Chatgpt4pcg competition: character-like level generation for science birds | |
| KR102751930B1 (ko) | 숙련도 조절이 가능한 npc 생성 장치 및 방법 | |
| Yu et al. | Data-driven personalized drama management | |
| Font et al. | Constrained level generation through grammar-based evolutionary algorithms | |
| Purnomo et al. | Ludic Linguistics: A Revisited Taxonomy of Fictional Constructed Language Design Approach for Video Games. | |
| JP7493664B1 (ja) | プログラム、及び、システム | |
| Cook | Formalizing non-formalism: Breaking the rules of automated game design | |
| WO2022158512A1 (ja) | ユーザが選択するアクションを予測するための学習済みモデルを生成するための方法等 | |
| Karpouzis et al. | AI in (and for) Games | |
| Rezapour et al. | A methodology for using players’ chat content for dynamic difficulty adjustment in metaverse multiplayer games | |
| Malazita | The material undermining of magical feminism in Bioshock infinite: burial at sea | |
| Eladhari et al. | Interweaving story coherence and player creativity through story-making games | |
| Horswill | Game design for classical AI | |
| JP7155447B2 (ja) | ユーザが選択するアクションを予測するための学習済みモデルを生成するための方法等 | |
| Plähn | A Prototype Quest Generator for Simulating Human-Authored Narrative | |
| Karth et al. | Generating playable rpg roms for the game boy | |
| Huang | Word2Minecraft: Generating 3D Game Levels through Large Language Models |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A523 Effective date: 20220729 |
|
| A621 | Written request for application examination |
Free format text: JAPANESE INTERMEDIATE CODE: A621 Effective date: 20220729 |
|
| A871 | Explanation of circumstances concerning accelerated examination |
Free format text: JAPANESE INTERMEDIATE CODE: A871 Effective date: 20220729 |
|
| TRDD | Decision of grant or rejection written | ||
| A01 | Written decision to grant a patent or to grant a registration (utility model) |
Free format text: JAPANESE INTERMEDIATE CODE: A01 Effective date: 20220905 |
|
| A61 | First payment of annual fees (during grant procedure) |
Free format text: JAPANESE INTERMEDIATE CODE: A61 Effective date: 20221005 |
|
| R150 | Certificate of patent or registration of utility model |
Ref document number: 7155447 Country of ref document: JP Free format text: JAPANESE INTERMEDIATE CODE: R150 |