Scaling Laws for Pre-training Agents and World Models
Tim Pearce, Tabish Rashid, Dave Bignell, Raluca Stevenson, Sam Devlin, Katja Hofmann
November 2024
Research for Industry
Project Paidia: a Microsoft Research & Ninja Theory Collaboration
论文与出版物
按年份分类的论文与出版物
-
Toward Human-AI Alignment in Large-Scale Multi-Player Games
Sugandha Sharma, Guy Davidson, Khimya Khetarpal, Anssi Kanervisto, Udit Arora, Katja Hofmann, Ida Momennejad
arXiv:2402.03575 | February 2024
作者：Microsoft
-
Contrastive Meta-Learning for Partially Observable Few-Shot Learning
Adam Jelley, Amos Storkey, Antreas Antoniou, Sam Devlin
ICLR | May 2023
Trust Region Bounds for Decentralized PPO Under Non-stationarity
Mingfei Sun, Sam Devlin, Jacob Beck, Katja Hofmann, Shimon Whiteson
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | May 2023
Best Paper Award
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games
Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Stevenson, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann
CHI | April 2023
-
Uni[MASK]: Unified Inference in Sequential Decision Problems
Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, Dave Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin
2022 Neural Information Processing Systems | November 2022
How Humans Perceive Human-like Behavior in Video Game Navigation
Evelyn Zuniga, Stephanie Milani, Guy Leroy, Jaroslaw Rzepecki, Raluca Stevenson, Ida Momennejad, Dave Bignell, Mingfei Sun, Alison Shaw, Gavin Costello, Mikhail Jacob, Sam Devlin, Katja Hofmann
CHI 2022 | April 2022
-
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Stevenson, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
2021 International Conference on Machine Learning | July 2021
Source code available at: https://github.com/microsoft/NTT
Acting with Style: Towards Designer-centred Reinforcement Learning for the Video Games Industry
Batu Aytemiz, Mikhail Jacob, Sam Devlin
CHI 2021 Workshop on Reinforcement Learning for Humans, Computer, and Interaction (RL4HCI) | May 2021
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning
Luisa Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
Difference Rewards Policy Gradients
Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
Evaluating the Robustness of Collaborative Agents
Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca Dragan, Rohin Shah
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
Estimating α-Rank by Maximizing Information Gain.
Tabish Rashid, Cheng Zhang, Kamil Ciosek
AAAI Conference on Artificial Intelligence (AAAI 2021) | January 2021
-
“It’s Unwieldy and It Takes a Lot of Time.” Challenges and Opportunities for Creating Agents in Commercial Games
Mikhail Jacob, Sam Devlin, Katja Hofmann
16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment | October 2020
AIIDE 2020 BEST PAPER AWARD
Best paper award winner.
AMRL: Aggregated Memory For Reinforcement Learning
Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann
Eighth International Conference on Learning Representations (ICLR) | April 2020
Conservative Uncertainty Estimation By Fitting Prior Networks
Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard Turner
Eighth International Conference on Learning Representations (ICLR) | April 2020
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning
Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson
Eighth International Conference on Learning Representations (ICLR) | April 2020
-
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
Better Exploration with Optimistic Actor-Critic
Kamil Ciosek, Quan Vuong, Robert Loftin, Katja Hofmann
33rd Conference on Neural Information Processing Systems (NeurIPS) | December 2019
按研究领域分类的论文与出版物
-
Scaling Laws for Pre-training Agents and World Models
Tim Pearce, Tabish Rashid, Dave Bignell, Raluca Stevenson, Sam Devlin, Katja Hofmann
November 2024
Toward Human-AI Alignment in Large-Scale Multi-Player Games
Sugandha Sharma, Guy Davidson, Khimya Khetarpal, Anssi Kanervisto, Udit Arora, Katja Hofmann, Ida Momennejad
arXiv:2402.03575 | February 2024
作者：Microsoft
Contrastive Meta-Learning for Partially Observable Few-Shot Learning
Adam Jelley, Amos Storkey, Antreas Antoniou, Sam Devlin
ICLR | May 2023
Trust Region Bounds for Decentralized PPO Under Non-stationarity
Mingfei Sun, Sam Devlin, Jacob Beck, Katja Hofmann, Shimon Whiteson
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | May 2023
Best Paper Award
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games
Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Stevenson, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann
CHI | April 2023
Uni[MASK]: Unified Inference in Sequential Decision Problems
Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, Dave Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin
2022 Neural Information Processing Systems | November 2022
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Stevenson, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
2021 International Conference on Machine Learning | July 2021
Source code available at: https://github.com/microsoft/NTT
Acting with Style: Towards Designer-centred Reinforcement Learning for the Video Games Industry
Batu Aytemiz, Mikhail Jacob, Sam Devlin
CHI 2021 Workshop on Reinforcement Learning for Humans, Computer, and Interaction (RL4HCI) | May 2021
Difference Rewards Policy Gradients
Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning
Luisa Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
Evaluating the Robustness of Collaborative Agents
Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca Dragan, Rohin Shah
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
Estimating α-Rank by Maximizing Information Gain.
Tabish Rashid, Cheng Zhang, Kamil Ciosek
AAAI Conference on Artificial Intelligence (AAAI 2021) | January 2021
“It’s Unwieldy and It Takes a Lot of Time.” Challenges and Opportunities for Creating Agents in Commercial Games
Mikhail Jacob, Sam Devlin, Katja Hofmann
16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment | October 2020
AIIDE 2020 BEST PAPER AWARD
Best paper award winner.
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning
Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson
Eighth International Conference on Learning Representations (ICLR) | April 2020
Conservative Uncertainty Estimation By Fitting Prior Networks
Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard Turner
Eighth International Conference on Learning Representations (ICLR) | April 2020
AMRL: Aggregated Memory For Reinforcement Learning
Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann
Eighth International Conference on Learning Representations (ICLR) | April 2020
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
Better Exploration with Optimistic Actor-Critic
Kamil Ciosek, Quan Vuong, Robert Loftin, Katja Hofmann
33rd Conference on Neural Information Processing Systems (NeurIPS) | December 2019
-
How Humans Perceive Human-like Behavior in Video Game Navigation
Evelyn Zuniga, Stephanie Milani, Guy Leroy, Jaroslaw Rzepecki, Raluca Stevenson, Ida Momennejad, Dave Bignell, Mingfei Sun, Alison Shaw, Gavin Costello, Mikhail Jacob, Sam Devlin, Katja Hofmann
CHI 2022 | April 2022
Acting with Style: Towards Designer-centred Reinforcement Learning for the Video Games Industry
Batu Aytemiz, Mikhail Jacob, Sam Devlin
CHI 2021 Workshop on Reinforcement Learning for Humans, Computer, and Interaction (RL4HCI) | May 2021
按类型分类的论文与出版物
-
Scaling Laws for Pre-training Agents and World Models
Tim Pearce, Tabish Rashid, Dave Bignell, Raluca Stevenson, Sam Devlin, Katja Hofmann
November 2024
-
Toward Human-AI Alignment in Large-Scale Multi-Player Games
Sugandha Sharma, Guy Davidson, Khimya Khetarpal, Anssi Kanervisto, Udit Arora, Katja Hofmann, Ida Momennejad
arXiv:2402.03575 | February 2024
作者：Microsoft
-
Contrastive Meta-Learning for Partially Observable Few-Shot Learning
Adam Jelley, Amos Storkey, Antreas Antoniou, Sam Devlin
ICLR | May 2023
Trust Region Bounds for Decentralized PPO Under Non-stationarity
Mingfei Sun, Sam Devlin, Jacob Beck, Katja Hofmann, Shimon Whiteson
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | May 2023
Best Paper Award
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games
Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Stevenson, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann
CHI | April 2023
Uni[MASK]: Unified Inference in Sequential Decision Problems
Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, Dave Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin
2022 Neural Information Processing Systems | November 2022
How Humans Perceive Human-like Behavior in Video Game Navigation
Evelyn Zuniga, Stephanie Milani, Guy Leroy, Jaroslaw Rzepecki, Raluca Stevenson, Ida Momennejad, Dave Bignell, Mingfei Sun, Alison Shaw, Gavin Costello, Mikhail Jacob, Sam Devlin, Katja Hofmann
CHI 2022 | April 2022
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Stevenson, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
2021 International Conference on Machine Learning | July 2021
Source code available at: https://github.com/microsoft/NTT
Acting with Style: Towards Designer-centred Reinforcement Learning for the Video Games Industry
Batu Aytemiz, Mikhail Jacob, Sam Devlin
CHI 2021 Workshop on Reinforcement Learning for Humans, Computer, and Interaction (RL4HCI) | May 2021
Difference Rewards Policy Gradients
Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning
Luisa Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
Evaluating the Robustness of Collaborative Agents
Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca Dragan, Rohin Shah
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
Estimating α-Rank by Maximizing Information Gain.
Tabish Rashid, Cheng Zhang, Kamil Ciosek
AAAI Conference on Artificial Intelligence (AAAI 2021) | January 2021
“It’s Unwieldy and It Takes a Lot of Time.” Challenges and Opportunities for Creating Agents in Commercial Games
Mikhail Jacob, Sam Devlin, Katja Hofmann
16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment | October 2020
AIIDE 2020 BEST PAPER AWARD
Best paper award winner.
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning
Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson
Eighth International Conference on Learning Representations (ICLR) | April 2020
Conservative Uncertainty Estimation By Fitting Prior Networks
Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard Turner
Eighth International Conference on Learning Representations (ICLR) | April 2020
AMRL: Aggregated Memory For Reinforcement Learning
Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann
Eighth International Conference on Learning Representations (ICLR) | April 2020
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
Better Exploration with Optimistic Actor-Critic
Kamil Ciosek, Quan Vuong, Robert Loftin, Katja Hofmann
33rd Conference on Neural Information Processing Systems (NeurIPS) | December 2019