Sam Devlin - RankMe

104 papers A* 10A 16B 2C 8Journal 55Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Hyperagents. CoRR Jenny Zhang, Bingchen Zhao, Wannan Yang, Jakob N. Foerster, Jeff Clune, Minqi Jiang, Sam Devlin, Tatiana Shavrina
2025	J	`jnl`	Adapting Vision-Language Models for Evaluating World Models. CoRR Mariya Hendriksen, Tabish Rashid, David Bignell, Raluca Georgescu, Abdelhak Lemkhenter, Katja Hofmann, Sam Devlin, Sarah Parisot
2025	J	`jnl`	Adapting a World Model for Trajectory Following in a 3D Game. CoRR Marko Tot, Shu Ishida, Abdelhak Lemkhenter, David Bignell, Pallavi Choudhury, Chris Lovett, Luis França, Matheus Ribeiro Furtado de Mendonca, Tarun Gupta, Darren Gehring, Sam Devlin, Sergio Valcarcel Macua, Raluca Georgescu
2025	J	`jnl`	Difference rewards policy gradients. Neural Comput. Appl. Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani
2025	A*	`conf`	Scaling Laws for Pre-training Agents and World Models. ICML Tim Pearce, Tabish Rashid, David Bignell, Raluca Georgescu, Sam Devlin, Katja Hofmann
2025	J	`jnl`	World and Human Action Models towards gameplay ideation. Nat. Anssi Kanervisto, David Bignell, Linda Yilin Wen, Martin Grayson, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Tabish Rashid, Tim Pearce, Yuhan Cao, Abdelhak Lemkhenter, Chentian Jiang, Gavin Costello, Gunshi Gupta, Marko Tot, Shu Ishida, Tarun Gupta, Udit Arora, Ryen W. White, Sam Devlin, Cecily Morrison, Katja Hofmann
2024	J	`jnl`	Aligning Agents like Large Language Models. CoRR Adam Jelley, Yuhan Cao, David Bignell, Sam Devlin, Tabish Rashid
2024	J	`jnl`	Efficient Offline Reinforcement Learning: The Critic is Critical. CoRR Adam Jelley, Trevor McInroe, Sam Devlin, Amos J. Storkey
2024	J	`jnl`	Scaling Laws for Pre-training Agents and World Models. CoRR Tim Pearce, Tabish Rashid, David Bignell, Raluca Georgescu, Sam Devlin, Katja Hofmann
2023	J	`jnl`	Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes. CoRR Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla
2023	A*	`conf`	Contrastive Meta-Learning for Partially Observable Few-Shot Learning. ICLR Adam Jelley, Amos J. Storkey, Antreas Antoniou, Sam Devlin
2023	J	`jnl`	Contrastive Meta-Learning for Partially Observable Few-Shot Learning. CoRR Adam Jelley, Amos J. Storkey, Antreas Antoniou, Sam Devlin
2023	A*	`conf`	Imitating Human Behaviour with Diffusion Models. ICLR Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin
2023	J	`jnl`	Imitating Human Behaviour with Diffusion Models. CoRR Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin
2023	A*	`conf`	Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games. CHI Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Georgescu, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann
2023	J	`jnl`	Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games. CoRR Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Georgescu, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann
2023	A	`conf`	Trust Region Bounds for Decentralized PPO Under Non-stationarity. AAMAS Mingfei Sun, Sam Devlin, Jacob Beck, Katja Hofmann, Shimon Whiteson
2023	J	`jnl`	Trust-Region-Free Policy Optimization for Stochastic Policies. CoRR Mingfei Sun, Benjamin Ellis, Anuj Mahajan, Sam Devlin, Katja Hofmann, Shimon Whiteson
2023	J	`jnl`	Visual Encoders for Data-Efficient Imitation Learning in Modern Video Games. CoRR Lukas Schäfer, Logan Jones, Anssi Kanervisto, Yuhan Cao, Tabish Rashid, Raluca Georgescu, David Bignell, Siddhartha Sen, Andrea Treviño Gavito, Sam Devlin
2022	J	`jnl`	A Comparison of Self-Play Algorithms Under a Generalized Framework. IEEE Trans. Games Daniel Hernández, Kevin Denamganaï, Sam Devlin, Spyridon Samothrakis, James Alfred Walker
2022	—	`conf`	Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes. AIED (1) Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla
2022	A*	`conf`	Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency. AAAI Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson
2022	—	`conf`	How Humans Perceive Human-like Behavior in Video Game Navigation. CHI Extended Abstracts 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
2022	C	`conf`	Imitating Playstyle with Dynamic Time Warping Imitation. FDG Mark Ferguson, Sam Devlin, Daniel Kudenko, James Alfred Walker
2022	J	`jnl`	Monotonic Improvement Guarantees under Non-stationarity for Decentralized PPO. CoRR Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson
2022	J	`jnl`	Rolling Horizon Evolutionary Algorithms for General Video Game Playing. IEEE Trans. Games Raluca D. Gaina, Sam Devlin, Simon M. Lucas, Diego Pérez-Liébana
2022	J	`jnl`	Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers. CoRR Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin
2022	C	`conf`	Turning Zeroes into Non-Zeroes: Sample Efficient Exploration with Monte Carlo Graph Search. CoG Marko Tot, Michelangelo Conserva, Diego Perez Liebana, Sam Devlin
2022	J	`jnl`	UniMASK: Unified Inference in Sequential Decision Problems. CoRR Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin
2022	A*	`conf`	Uni[MASK]: Unified Inference in Sequential Decision Problems. NeurIPS Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin
2022	J	`jnl`	You May Not Need Ratio Clipping in PPO. CoRR Mingfei Sun, Vitaly Kurin, Guoqing Liu, Sam Devlin, Tao Qin, Katja Hofmann, Shimon Whiteson
2021	A	`conf`	Deep Interactive Bayesian Reinforcement Learning via Meta-Learning. AAMAS Luisa M. Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
2021	J	`jnl`	Deep Interactive Bayesian Reinforcement Learning via Meta-Learning. CoRR Luisa M. Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
2021	J	`jnl`	Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency. CoRR Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson
2021	A	`conf`	Difference Rewards Policy Gradients. AAMAS Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani
2021	A	`conf`	Evaluating the Robustness of Collaborative Agents. AAMAS Paul A. Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah
2021	J	`jnl`	Evaluating the Robustness of Collaborative Agents. CoRR Paul A. Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah
2021	A	`conf`	Meta-Learning Divergences for Variational Inference. AISTATS Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang
2021	A*	`conf`	Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation. ICML Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
2021	J	`jnl`	Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation. CoRR Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
2021	J	`jnl`	Strategically Efficient Exploration in Competitive Multi-agent Reinforcement Learning. CoRR Robert Tyler Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann
2021	A	`conf`	Strategically efficient exploration in competitive multi-agent reinforcement learning. UAI Robert Tyler Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann
2021	J	`jnl`	The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors. CoRR 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
2021	J	`jnl`	Win Prediction in Multiplayer Esports: Live Professional Match Prediction. IEEE Trans. Games Victoria J. Hodge, Sam Devlin, Nick Sephton, Florian Block, Peter I. Cowling, Anders Drachen
2020	—	`conf`	"It's Unwieldy and It Takes a Lot of Time" - Challenges and Opportunities for Creating Agents in Commercial Games. AIIDE Mikhail Jacob, Sam Devlin, Katja Hofmann
2020	J	`jnl`	"It's Unwieldy and It Takes a Lot of Time." Challenges and Opportunities for Creating Agents in Commercial Games. CoRR Mikhail Jacob, Sam Devlin, Katja Hofmann
2020	J	`jnl`	A Comparison of Self-Play Algorithms Under a Generalized Framework. CoRR Daniel Hernández, Kevin Denamganaï, Sam Devlin, Spyridon Samothrakis, James Alfred Walker
2020	A*	`conf`	AMRL: Aggregated Memory For Reinforcement Learning. ICLR Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann
2020	J	`jnl`	Analytic Manifold Learning: Unifying and Evaluating Representations for Continuous Control. CoRR Rika Antonova, Maksim Maydanskiy, Danica Kragic, Sam Devlin, Katja Hofmann
2020	C	`conf`	Automatic Similarity Detection in LEGO Ducks. ICCC Mark Ferguson, Sebastian Deterding, Andreas Lieberoth, Marc Malmdorf Andersen, Sam Devlin, Daniel Kudenko, James Alfred Walker
2020	J	`jnl`	Difference Rewards Policy Gradients. CoRR Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani
2020	J	`jnl`	Meta-Learning for Variational Inference. CoRR Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang
2020	C	`conf`	Player Style Clustering without Game Variables. FDG Mark Ferguson, Sam Devlin, Daniel Kudenko, James Alfred Walker
2020	J	`jnl`	Rolling Horizon Evolutionary Algorithms for General Video Game Playing. CoRR Raluca D. Gaina, Sam Devlin, Simon M. Lucas, Diego Pérez-Liébana
2019	C	`conf`	A Generalized Framework for Self-Play Training. CoG Daniel Hernández, Kevin Denamganaï, Alex Yuan Gao, Peter York, Sam Devlin, Spyridon Samothrakis, James Alfred Walker
2019	J	`jnl`	Emulating Human Play in a Leading Mobile Card Game. IEEE Trans. Games Hendrik Baier, Adam Sattaur, Edward J. Powley, Sam Devlin, Jeff Rollason, Peter I. Cowling
2019	A*	`conf`	Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck. NeurIPS Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
2019	J	`jnl`	Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck. CoRR Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
2019	J	`jnl`	How the Business Model of Customizable Card Games Influences Player Engagement. IEEE Trans. Games Victoria J. Hodge, Feng Li, Nick Sephton, Sam Devlin, Peter I. Cowling, Nikolaos Goumagias, Jianhua Shao, Kieran Purvis, Ignazio Cabras, Kiran Jude Fernandes
2019	C	`conf`	MazeExplorer: A Customisable 3D Benchmark for Assessing Generalisation in Reinforcement Learning. CoG Luke Harries, Sebastian Lee, Jaroslaw Rzepecki, Katja Hofmann, Sam Devlin
2019	J	`jnl`	Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems. CoRR Kleanthis Malialis, Sam Devlin, Daniel Kudenko
2019	J	`jnl`	The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition. CoRR Diego Pérez-Liébana, Katja Hofmann, Sharada Prasanna Mohanty, Noburu Kuno, André Kramer, Sam Devlin, Raluca D. Gaina, Daniel Ionita
2019	J	`jnl`	The Text-Based Adventure AI Competition. IEEE Trans. Games Timothy Atkinson, Hendrik Baier, Tara Copplestone, Sam Devlin, Jerry Swan
2019	J	`jnl`	Type inference in flexible model-driven engineering using classification algorithms. Softw. Syst. Model. Athanasios Zolotas, Nicholas Matragkas, Sam Devlin, Dimitrios S. Kolovos, Richard F. Paige
2019	C	`conf`	Win or Learn Fast Proximal Policy Optimisation. CoG Dino Stephen Ratcliffe, Katja Hofmann, Sam Devlin
2018	—	`conf`	Narrative Bytes: Data-Driven Content Production in Esports. TVX Florian Block, Victoria J. Hodge, Stephen Hobson, Nick Sephton, Sam Devlin, Marian Florin Ursu, Anders Drachen, Peter I. Cowling
2018	J	`jnl`	Reward shaping for knowledge-based multi-objective multi-agent reinforcement learning. Knowl. Eng. Rev. Patrick Mannion, Sam Devlin, Jim Duggan, Enda Howley
2018	J	`jnl`	The Text-Based Adventure AI Competition. CoRR Timothy Atkinson, Hendrik Baier, Tara Copplestone, Sam Devlin, Jerry Swan
2017	—	`conf`	Clyde: A Deep Reinforcement Learning DOOM Playing Agent. AAAI Workshops Dino Stephen Ratcliffe, Sam Devlin, Udo Kruschwitz, Luca Citi
2017	B	`conf`	Exploration and Skill Acquisition in a Major Online Game. CogSci Tom Stafford, Sam Devlin, Rafet Sifa, Anders Drachen
2017	J	`jnl`	Multi-agent credit assignment in stochastic resource management games. Knowl. Eng. Rev. Patrick Mannion, Sam Devlin, Jim Duggan, Enda Howley
2017	J	`jnl`	Policy invariance under reward transformations for multi-objective reinforcement learning. Neurocomputing Patrick Mannion, Sam Devlin, Karl Mason, Jim Duggan, Enda Howley
2017	J	`jnl`	Win Prediction in Esports: Mixed-Rank Match Prediction in Multi-player Online Battle Arena Games. CoRR Victoria J. Hodge, Sam Devlin, Nick Sephton, Florian Block, Anders Drachen, Peter I. Cowling
2016	—	`conf`	Combining Gameplay Data with Monte Carlo Tree Search to Emulate Human Play. AIIDE Sam Devlin, Anastasija Anspoka, Nick Sephton, Peter I. Cowling, Jeff Rollason
2016	J	`jnl`	Context-sensitive reward shaping for sparse interaction multi-agent systems. Knowl. Eng. Rev. Yann-Michaël De Hauwere, Sam Devlin, Daniel Kudenko, Ann Nowé
2016	A	`conf`	Multi-Objective Dynamic Dispatch Optimisation using Multi-Agent Reinforcement Learning: (Extended Abstract). AAMAS Patrick Mannion, Karl Mason, Sam Devlin, Jim Duggan, Enda Howley
2016	J	`jnl`	Overcoming incorrect knowledge in plan-based reward shaping. Knowl. Eng. Rev. Kyriakos Efthymiadis, Sam Devlin, Daniel Kudenko
2016	J	`jnl`	Plan-based reward shaping for multi-agent reinforcement learning. Knowl. Eng. Rev. Sam Devlin, Daniel Kudenko
2016	J	`jnl`	Potential-based reward shaping for finite horizon online POMDP planning. Auton. Agents Multi Agent Syst. Adam Eck, Leen-Kiat Soh, Sam Devlin, Daniel Kudenko
2016	A	`conf`	Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems. AAMAS Kleanthis Malialis, Sam Devlin, Daniel Kudenko
2016	—	`conf`	Using association rule mining to predict opponent deck content in android: Netrunner. CIG Nick Sephton, Peter I. Cowling, Sam Devlin, Victoria J. Hodge, Nicholas H. Slaven
2015	J	`jnl`	Distributed reinforcement learning for adaptive and robust network intrusion response. Connect. Sci. Kleanthis Malialis, Sam Devlin, Daniel Kudenko
2015	A*	`conf`	Expressing Arbitrary Reward Functions as Potential-Based Advice. AAAI Anna Harutyunyan, Sam Devlin, Peter Vrancx, Ann Nowé
2015	J	`jnl`	Player Preference and Style in a Leading Mobile Card Game. IEEE Trans. Comput. Intell. AI Games Peter I. Cowling, Sam Devlin, Edward Jack Powley, Daniel Whitehouse, Jeff Rollason
2015	—	`conf`	Predicting player disengagement and first purchase with event-frequency based data representation. CIG Hanting Xie, Sam Devlin, Daniel Kudenko, Peter I. Cowling
2015	J	`jnl`	Preface to the special issue: Adaptive Learning Agents Part 3. Connect. Sci. Sam Devlin, Daniel Hennes, Samuel Barrett
2015	—	`conf`	Type Inference Using Concrete Syntax Properties in Flexible Model-Driven Engineering. FlexMDE@MoDELS Athanasios Zolotas, Nicholas Drivalos Matragkas, Sam Devlin, Dimitrios S. Kolovos, Richard F. Paige
2015	B	`conf`	Type Inference in Flexible Model-Driven Engineering. ECMFA Athanasios Zolotas, Nicholas Drivalos Matragkas, Sam Devlin, Dimitrios S. Kolovos, Richard F. Paige
2014	C	`conf`	A Phylogenetic Classification of the Video-Game Industry's Business Model Ecosystem. PRO-VE Nikolaos Goumagias, Ignazio Cabras, Kiran Jude Fernandes, Feng Li, Alberto Nucciarelli, Peter I. Cowling, Sam Devlin, Daniel Kudenko
2014	A	`conf`	Coordinated Team Learning and Difference Rewards for Distributed Intrusion Response. ECAI Kleanthis Malialis, Sam Devlin, Daniel Kudenko
2014	—	`conf`	Game intelligence. CIG Sam Devlin, Peter I. Cowling, Daniel Kudenko, Nikolaos Goumagias, Alberto Nucciarelli, Ignazio Cabras, Kiran Jude Fernandes, Feng Li
2014	A	`conf`	Knowledge revision for reinforcement learning with abstract MDPs. AAMAS Kyriakos Efthymiadis, Sam Devlin, Daniel Kudenko
2014	A	`conf`	Potential-based difference rewards for multiagent reinforcement learning. AAMAS Sam Devlin, Logan Michael Yliniemi, Daniel Kudenko, Kagan Tumer
2014	—	`conf`	Predicting Player Disengagement in Online Games. CGW@ECAI Hanting Xie, Daniel Kudenko, Sam Devlin, Peter I. Cowling
2014	J	`jnl`	Preface to the special issue: Adaptive Learning Agents Part 2. Connect. Sci. Sam Devlin, Daniel Hennes, Enda Howley
2014	J	`jnl`	Preface to the special issue: Adaptive Learning Agents, Part 1. Connect. Sci. Sam Devlin, Daniel Hennes, Enda Howley
2013	A	`conf`	Overcoming erroneous domain knowledge in plan-based reward shaping. AAMAS Kyriakos Efthymiadis, Sam Devlin, Daniel Kudenko
2013	A	`conf`	Potential-based reward shaping for POMDPs. AAMAS Adam Eck, Leen-Kiat Soh, Sam Devlin, Daniel Kudenko
2013	—	`—`	Potential-based reward shaping for knowledge-based, multi-agent reinforcement learning. Sam Devlin
2012	A	`conf`	Dynamic potential-based reward shaping. AAMAS Sam Devlin, Daniel Kudenko
2011	J	`jnl`	An Empirical Study of Potential-Based Reward Shaping and Advice in Complex, Multi-Agent Systems. Adv. Complex Syst. Sam Devlin, Daniel Kudenko, Marek Grzes
2011	A	`conf`	Multi-agent, reward shaping for RoboCup KeepAway. AAMAS Sam Devlin, Marek Grzes, Daniel Kudenko
2011	A	`conf`	Theoretical considerations of potential-based reward shaping for multi-agent systems. AAMAS Sam Devlin, Daniel Kudenko
2009	—	`conf`	Reinforcement Learning in RoboCup KeepAway with Partial Observability. IAT Sam Devlin, Marek Grzes, Daniel Kudenko