Sam Devlin

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 81

Top Venues

University of York, UK (PHD)

Education History

University of York, UK

PHD

Publications

Adam Jelley, Yuhan Cao, David Bignell, Sam Devlin, Tabish Rashid
Aligning Agents like Large Language Models. CoRR (2024)
Adam Jelley, Trevor McInroe, Sam Devlin, Amos J. Storkey
Efficient Offline Reinforcement Learning: The Critic is Critical. CoRR (2024)
Adam Jelley, Amos J. Storkey, Antreas Antoniou, Sam Devlin
Contrastive Meta-Learning for Partially Observable Few-Shot Learning. CoRR (2023)
Mingfei Sun, Sam Devlin, Jacob Beck, Katja Hofmann, Shimon Whiteson
Trust Region Bounds for Decentralized PPO Under Non-stationarity. AAMAS (2023)
Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Georgescu, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games. CHI (2023)
Adam Jelley, Amos J. Storkey, Antreas Antoniou, Sam Devlin
Contrastive Meta-Learning for Partially Observable Few-Shot Learning. ICLR (2023)
Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin
Imitating Human Behaviour with Diffusion Models. ICLR (2023)
Lukas Schäfer, Logan Jones, Anssi Kanervisto, Yuhan Cao, Tabish Rashid, Raluca Georgescu, David Bignell, Siddhartha Sen, Andrea Treviño Gavito, Sam Devlin
Visual Encoders for Data-Efficient Imitation Learning in Modern Video Games. CoRR (2023)
Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla
Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes. CoRR (2023)
Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin
Imitating Human Behaviour with Diffusion Models. CoRR (2023)
Mingfei Sun, Benjamin Ellis, Anuj Mahajan, Sam Devlin, Katja Hofmann, Shimon Whiteson
Trust-Region-Free Policy Optimization for Stochastic Policies. CoRR (2023)
Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Georgescu, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games. CoRR (2023)
Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca D. Dragan, Sam Devlin
Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers. CoRR (2022)
Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson
Monotonic Improvement Guarantees under Non-stationarity for Decentralized PPO. CoRR (2022)
Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca D. Dragan, Sam Devlin
UniMASK: Unified Inference in Sequential Decision Problems. CoRR (2022)
Mark Ferguson, Sam Devlin, Daniel Kudenko, James Alfred Walker
Imitating Playstyle with Dynamic Time Warping Imitation. FDG (2022)
Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla
Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes. AIED (1) (2022)
Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson
Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency. AAAI (2022)
Raluca D. Gaina, Sam Devlin, Simon M. Lucas, Diego Pérez-Liébana
Rolling Horizon Evolutionary Algorithms for General Video Game Playing. IEEE Trans. Games 14 (2) (2022)
Marko Tot, Michelangelo Conserva, Diego Perez Liebana, Sam Devlin
Turning Zeroes into Non-Zeroes: Sample Efficient Exploration with Monte Carlo Graph Search. CoG (2022)
Mingfei Sun, Vitaly Kurin, Guoqing Liu, Sam Devlin, Tao Qin, Katja Hofmann, Shimon Whiteson
You May Not Need Ratio Clipping in PPO. CoRR (2022)
Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin
Uni[MASK]: Unified Inference in Sequential Decision Problems. NeurIPS (2022)
Daniel Hernández, Kevin Denamganaï, Sam Devlin, Spyridon Samothrakis, James Alfred Walker
A Comparison of Self-Play Algorithms Under a Generalized Framework. IEEE Trans. Games 14 (2) (2022)
Evelyn Zuniga, Stephanie Milani, Guy Leroy, Jaroslaw Rzepecki, Raluca Georgescu, Ida Momennejad, David Bignell, Mingfei Sun, Alison Shaw, Gavin Costello, Mikhail Jacob, Sam Devlin, Katja Hofmann
How Humans Perceive Human-like Behavior in Video Game Navigation. CHI Extended Abstracts (2022)
Luisa M. Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning. CoRR (2021)
Victoria J. Hodge, Sam Devlin, Nick Sephton, Florian Block, Peter I. Cowling, Anders Drachen
Win Prediction in Multiplayer Esports: Live Professional Match Prediction. IEEE Trans. Games 13 (4) (2021)
William H. Guss, Mario Ynocente Castro, Sam Devlin, Brandon Houghton, Noboru Sean Kuno, Crissman Loomis, Stephanie Milani, Sharada P. Mohanty, Keisuke Nakata, Ruslan Salakhutdinov, John Schulman, Shinya Shiroshita, Nicholay Topin, Avinash Ummadisingu, Oriol Vinyals
The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors. CoRR (2021)
Robert Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann
Strategically Efficient Exploration in Competitive Multi-agent Reinforcement Learning. CoRR (2021)
Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation. CoRR (2021)
Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson
Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency. CoRR (2021)
Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah
Evaluating the Robustness of Collaborative Agents. AAMAS (2021)
Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani
Difference Rewards Policy Gradients. AAMAS (2021)
Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang
Meta-Learning Divergences for Variational Inference. AISTATS (2021)
Luisa M. Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning. AAMAS (2021)
Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation. ICML (2021)
Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah
Evaluating the Robustness of Collaborative Agents. CoRR (2021)
Robert Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann
Strategically efficient exploration in competitive multi-agent reinforcement learning. UAI (2021)
Mikhail Jacob, Sam Devlin, Katja Hofmann
"It's Unwieldy and It Takes a Lot of Time." Challenges and Opportunities for Creating Agents in Commercial Games. CoRR (2020)
Rika Antonova, Maksim Maydanskiy, Danica Kragic, Sam Devlin, Katja Hofmann
Analytic Manifold Learning: Unifying and Evaluating Representations for Continuous Control. CoRR (2020)
Mark Ferguson, Sam Devlin, Daniel Kudenko, James Alfred Walker
Player Style Clustering without Game Variables. FDG (2020)
Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang
Meta-Learning for Variational Inference. CoRR (2020)
Raluca D. Gaina, Sam Devlin, Simon M. Lucas, Diego Pérez-Liébana
Rolling Horizon Evolutionary Algorithms for General Video Game Playing. CoRR (2020)
Mikhail Jacob, Sam Devlin, Katja Hofmann
"It's Unwieldy and It Takes a Lot of Time" - Challenges and Opportunities for Creating Agents in Commercial Games. AIIDE (2020)
Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann
AMRL: Aggregated Memory For Reinforcement Learning. ICLR (2020)
Daniel Hernández, Kevin Denamganaï, Sam Devlin, Spyridon Samothrakis, James Alfred Walker
A Comparison of Self-Play Algorithms Under a Generalized Framework. CoRR (2020)
Mark Ferguson, Sebastian Deterding, Andreas Lieberoth, Marc Malmdorf Andersen, Sam Devlin, Daniel Kudenko, James Alfred Walker
Automatic Similarity Detection in LEGO Ducks. ICCC (2020)
Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani
Difference Rewards Policy Gradients. CoRR (2020)
Daniel Hernández, Kevin Denamganaï, Yuan Gao, Peter York, Sam Devlin, Spyridon Samothrakis, James Alfred Walker
A Generalized Framework for Self-Play Training. CoG (2019)
Dino Stephen Ratcliffe, Katja Hofmann, Sam Devlin
Win or Learn Fast Proximal Policy Optimisation. CoG (2019)
Timothy Atkinson, Hendrik Baier, Tara Copplestone, Sam Devlin, Jerry Swan
The Text-Based Adventure AI Competition. IEEE Trans. Games 11 (3) (2019)
Luke Harries, Sebastian Lee, Jaroslaw Rzepecki, Katja Hofmann, Sam Devlin
MazeExplorer: A Customisable 3D Benchmark for Assessing Generalisation in Reinforcement Learning. CoG (2019)
Kleanthis Malialis, Sam Devlin, Daniel Kudenko
Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems. CoRR (2019)
Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck. NeurIPS (2019)
Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck. CoRR (2019)
Hendrik Baier, Adam Sattaur, Edward J. Powley, Sam Devlin, Jeff Rollason, Peter I. Cowling
Emulating Human Play in a Leading Mobile Card Game. IEEE Trans. Games 11 (4) (2019)
Diego Pérez-Liébana, Katja Hofmann, Sharada Prasanna Mohanty, Noburu Kuno, André Kramer, Sam Devlin, Raluca D. Gaina, Daniel Ionita
The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition. CoRR (2019)
Victoria J. Hodge, Feng Li, Nick Sephton, Sam Devlin, Peter I. Cowling, Nikolaos Goumagias, Jianhua Shao, Kieran Purvis, Ignazio Cabras, Kiran Jude Fernandes
How the Business Model of Customizable Card Games Influences Player Engagement. IEEE Trans. Games 11 (4) (2019)
Athanasios Zolotas, Nicholas Matragkas, Sam Devlin, Dimitrios S. Kolovos, Richard F. Paige
Type inference in flexible model-driven engineering using classification algorithms. Softw. Syst. Model. 18 (1) (2019)
Patrick Mannion, Sam Devlin, Jim Duggan, Enda Howley
Reward shaping for knowledge-based multi-objective multi-agent reinforcement learning. Knowl. Eng. Rev. 33 (2018)
Florian Block, Victoria J. Hodge, Stephen Hobson, Nick Sephton, Sam Devlin, Marian Florin Ursu, Anders Drachen, Peter I. Cowling
Narrative Bytes: Data-Driven Content Production in Esports. TVX (2018)
Timothy Atkinson, Hendrik Baier, Tara Copplestone, Sam Devlin, Jerry Swan
The Text-Based Adventure AI Competition. CoRR (2018)
Dino Stephen Ratcliffe, Sam Devlin, Udo Kruschwitz, Luca Citi
Clyde: A Deep Reinforcement Learning DOOM Playing Agent. AAAI Workshops (2017)
Patrick Mannion, Sam Devlin, Karl Mason, Jim Duggan, Enda Howley
Policy invariance under reward transformations for multi-objective reinforcement learning. Neurocomputing 263 (2017)
Patrick Mannion, Sam Devlin, Jim Duggan, Enda Howley
Multi-agent credit assignment in stochastic resource management games. Knowl. Eng. Rev. 32 (2017)
Victoria J. Hodge, Sam Devlin, Nick Sephton, Florian Block, Anders Drachen, Peter I. Cowling
Win Prediction in Esports: Mixed-Rank Match Prediction in Multi-player Online Battle Arena Games. CoRR (2017)
Tom Stafford, Sam Devlin, Rafet Sifa, Anders Drachen
Exploration and Skill Acquisition in a Major Online Game. CogSci (2017)
Nick Sephton, Peter I. Cowling, Sam Devlin, Victoria J. Hodge, Nicholas H. Slaven
Using association rule mining to predict opponent deck content in android: Netrunner. CIG (2016)
Sam Devlin, Daniel Kudenko
Plan-based reward shaping for multi-agent reinforcement learning. Knowl. Eng. Rev. 31 (1) (2016)
Sam Devlin, Anastasija Anspoka, Nick Sephton, Peter I. Cowling, Jeff Rollason
Combining Gameplay Data with Monte Carlo Tree Search to Emulate Human Play. AIIDE (2016)
Yann-Michaël De Hauwere, Sam Devlin, Daniel Kudenko, Ann Nowé
Context-sensitive reward shaping for sparse interaction multi-agent systems. Knowl. Eng. Rev. 31 (1) (2016)
Kyriakos Efthymiadis, Sam Devlin, Daniel Kudenko
Overcoming incorrect knowledge in plan-based reward shaping. Knowl. Eng. Rev. 31 (1) (2016)
Kleanthis Malialis, Sam Devlin, Daniel Kudenko
Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems. AAMAS (2016)
Patrick Mannion, Karl Mason, Sam Devlin, Jim Duggan, Enda Howley
Multi-Objective Dynamic Dispatch Optimisation using Multi-Agent Reinforcement Learning: (Extended Abstract). AAMAS (2016)
Adam Eck, Leen-Kiat Soh, Sam Devlin, Daniel Kudenko
Potential-based reward shaping for finite horizon online POMDP planning. Auton. Agents Multi Agent Syst. 30 (3) (2016)
Sam Devlin, Daniel Hennes, Samuel Barrett
Preface to the special issue: Adaptive Learning Agents Part 3. Connect. Sci. 27 (3) (2015)
Athanasios Zolotas, Nicholas Drivalos Matragkas, Sam Devlin, Dimitrios S. Kolovos, Richard F. Paige
Type Inference Using Concrete Syntax Properties in Flexible Model-Driven Engineering. FlexMDE@MoDELS (2015)
Anna Harutyunyan, Sam Devlin, Peter Vrancx, Ann Nowé
Expressing Arbitrary Reward Functions as Potential-Based Advice. AAAI (2015)
Peter I. Cowling, Sam Devlin, Edward Jack Powley, Daniel Whitehouse, Jeff Rollason
Player Preference and Style in a Leading Mobile Card Game. IEEE Trans. Comput. Intell. AI Games 7 (3) (2015)
Athanasios Zolotas, Nicholas Drivalos Matragkas, Sam Devlin, Dimitrios S. Kolovos, Richard F. Paige
Type Inference in Flexible Model-Driven Engineering. ECMFA (2015)
Hanting Xie, Sam Devlin, Daniel Kudenko, Peter I. Cowling
Predicting player disengagement and first purchase with event-frequency based data representation. CIG (2015)
Kleanthis Malialis, Sam Devlin, Daniel Kudenko
Distributed reinforcement learning for adaptive and robust network intrusion response. Connect. Sci. 27 (3) (2015)
Sam Devlin, Daniel Hennes, Enda Howley
Preface to the special issue: Adaptive Learning Agents Part 2. Connect. Sci. 26 (2) (2014)
Kyriakos Efthymiadis, Sam Devlin, Daniel Kudenko
Knowledge revision for reinforcement learning with abstract MDPs. AAMAS (2014)
Sam Devlin, Peter I. Cowling, Daniel Kudenko, Nikolaos Goumagias, Alberto Nucciarelli, Ignazio Cabras, Kiran Jude Fernandes, Feng Li
Game intelligence. CIG (2014)
Hanting Xie, Daniel Kudenko, Sam Devlin, Peter I. Cowling
Predicting Player Disengagement in Online Games. CGW@ECAI (2014)
Sam Devlin, Logan Michael Yliniemi, Daniel Kudenko, Kagan Tumer
Potential-based difference rewards for multiagent reinforcement learning. AAMAS (2014)
Nikolaos Goumagias, Ignazio Cabras, Kiran Jude Fernandes, Feng Li, Alberto Nucciarelli, Peter I. Cowling, Sam Devlin, Daniel Kudenko
A Phylogenetic Classification of the Video-Game Industry's Business Model Ecosystem. PRO-VE (2014)
Kleanthis Malialis, Sam Devlin, Daniel Kudenko
Coordinated Team Learning and Difference Rewards for Distributed Intrusion Response. ECAI (2014)
Sam Devlin, Daniel Hennes, Enda Howley
Preface to the special issue: Adaptive Learning Agents, Part 1. Connect. Sci. 26 (1) (2014)
Kyriakos Efthymiadis, Sam Devlin, Daniel Kudenko
Overcoming erroneous domain knowledge in plan-based reward shaping. AAMAS (2013)
Adam Eck, Leen-Kiat Soh, Sam Devlin, Daniel Kudenko
Potential-based reward shaping for POMDPs. AAMAS (2013)
Sam Devlin, Daniel Kudenko
Dynamic potential-based reward shaping. AAMAS (2012)
Sam Devlin, Daniel Kudenko, Marek Grzes
An Empirical Study of Potential-Based Reward Shaping and Advice in Complex, Multi-Agent Systems. Adv. Complex Syst. 14 (2) (2011)
Sam Devlin, Daniel Kudenko
Theoretical considerations of potential-based reward shaping for multi-agent systems. AAMAS (2011)
Sam Devlin, Marek Grzes, Daniel Kudenko
Multi-agent, reward shaping for RoboCup KeepAway. AAMAS (2011)
Sam Devlin, Marek Grzes, Daniel Kudenko
Reinforcement Learning in RoboCup KeepAway with Partial Observability. IAT (2009)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sam Devlin