DK3552156T3 - Neural episodisk styring - Google Patents
Neural episodisk styring Download PDFInfo
- Publication number
- DK3552156T3 DK3552156T3 DK18707703.7T DK18707703T DK3552156T3 DK 3552156 T3 DK3552156 T3 DK 3552156T3 DK 18707703 T DK18707703 T DK 18707703T DK 3552156 T3 DK3552156 T3 DK 3552156T3
- Authority
- DK
- Denmark
- Prior art keywords
- neural
- episodic control
- episodic
- control
- neural episodic
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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
- G06N3/044—Recurrent networks, e.g. Hopfield networks
- G06N3/0442—Recurrent networks, e.g. Hopfield networks characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06N3/0464—Convolutional networks [CNN, ConvNet]
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/092—Reinforcement learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06N3/044—Recurrent networks, e.g. Hopfield networks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06N3/045—Combinations of networks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/01—Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Life Sciences & Earth Sciences (AREA)
- Molecular Biology (AREA)
- Artificial Intelligence (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- Image Analysis (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US201762463558P | 2017-02-24 | 2017-02-24 | |
| PCT/EP2018/054624 WO2018154100A1 (en) | 2017-02-24 | 2018-02-26 | Neural episodic control |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| DK3552156T3 true DK3552156T3 (da) | 2022-08-22 |
Family
ID=61386852
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| DK18707703.7T DK3552156T3 (da) | 2017-02-24 | 2018-02-26 | Neural episodisk styring |
Country Status (6)
| Country | Link |
|---|---|
| US (2) | US10664753B2 (da) |
| EP (2) | EP3552156B8 (da) |
| JP (2) | JP6817456B2 (da) |
| CN (1) | CN110235149B (da) |
| DK (1) | DK3552156T3 (da) |
| WO (1) | WO2018154100A1 (da) |
Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3523760B1 (en) * | 2016-11-04 | 2024-01-24 | DeepMind Technologies Limited | Reinforcement learning systems |
| CA3103470A1 (en) | 2018-06-12 | 2019-12-19 | Intergraph Corporation | Artificial intelligence applications for computer-aided dispatch systems |
| US11455530B2 (en) * | 2018-11-20 | 2022-09-27 | Google Llc | Controlling agents using scene memory data |
| WO2020132693A1 (en) * | 2018-12-21 | 2020-06-25 | Waymo Llc | Searching an autonomous vehicle sensor data repository |
| WO2022069747A1 (en) * | 2020-10-02 | 2022-04-07 | Deepmind Technologies Limited | Training reinforcement learning agents using augmented temporal difference learning |
| CN112476424B (zh) | 2020-11-13 | 2025-05-09 | 腾讯科技（深圳）有限公司 | 机器人控制方法、装置、设备及计算机存储介质 |
| US12197214B2 (en) * | 2021-03-23 | 2025-01-14 | Honda Motor Co., Ltd. | System and method for completing continual multi-agent trajectory forecasting |
| KR102821722B1 (ko) * | 2021-08-09 | 2025-06-17 | 한국전자통신연구원 | 에피소드 메모리 기반 인공 지능 학습 장치 및 방법 |
| CN117274732B (zh) * | 2023-09-18 | 2024-07-16 | 广东石油化工学院 | 一种基于情景记忆驱动构建优化扩散模型的方法和系统 |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9189409B2 (en) * | 2013-02-19 | 2015-11-17 | Avago Technologies General Ip (Singapore) Pte. Ltd. | Reducing writes to solid state drive cache memories of storage controllers |
| US9679258B2 (en) * | 2013-10-08 | 2017-06-13 | Google Inc. | Methods and apparatus for reinforcement learning |
| US10628733B2 (en) * | 2015-04-06 | 2020-04-21 | Deepmind Technologies Limited | Selecting reinforcement learning actions using goals and observations |
| US20180165602A1 (en) * | 2016-12-14 | 2018-06-14 | Microsoft Technology Licensing, Llc | Scalability of reinforcement learning by separation of concerns |
-
2018
- 2018-02-26 DK DK18707703.7T patent/DK3552156T3/da active
- 2018-02-26 CN CN201880008758.6A patent/CN110235149B/zh active Active
- 2018-02-26 EP EP18707703.7A patent/EP3552156B8/en active Active
- 2018-02-26 EP EP22170944.7A patent/EP4057189A1/en not_active Ceased
- 2018-02-26 WO PCT/EP2018/054624 patent/WO2018154100A1/en not_active Ceased
- 2018-02-26 JP JP2019546227A patent/JP6817456B2/ja active Active
-
2019
- 2019-06-19 US US16/445,523 patent/US10664753B2/en active Active
-
2020
- 2020-04-23 US US16/856,527 patent/US11720796B2/en active Active
- 2020-12-23 JP JP2020213556A patent/JP7038790B2/ja active Active
Also Published As
| Publication number | Publication date |
|---|---|
| US20190303764A1 (en) | 2019-10-03 |
| WO2018154100A1 (en) | 2018-08-30 |
| CN110235149A (zh) | 2019-09-13 |
| JP2020508527A (ja) | 2020-03-19 |
| US10664753B2 (en) | 2020-05-26 |
| EP3552156B8 (en) | 2022-08-03 |
| JP7038790B2 (ja) | 2022-03-18 |
| EP4057189A1 (en) | 2022-09-14 |
| EP3552156A1 (en) | 2019-10-16 |
| CN110235149B (zh) | 2023-07-07 |
| EP3552156B1 (en) | 2022-06-22 |
| US20200265317A1 (en) | 2020-08-20 |
| JP6817456B2 (ja) | 2021-01-20 |
| US11720796B2 (en) | 2023-08-08 |
| JP2021064387A (ja) | 2021-04-22 |
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