2024
Safe Multiagent Coordination via Entropic Exploration.
CoRR, 2024
Adversarial Inception for Bounded Backdoor Poisoning in Deep Reinforcement Learning.
CoRR, 2024
An Introduction to Centralized Training for Decentralized Execution in Cooperative Multi-Agent Reinforcement Learning.
CoRR, 2024
On Stateful Value Factorization in Multi-Agent Reinforcement Learning.
CoRR, 2024
(A Partial Survey of) Decentralized, Cooperative Multi-Agent Reinforcement Learning.
CoRR, 2024
Shield Decomposition for Safe Reinforcement Learning in General Partially Observable Multi-Agent Environments.
RLJ, 2024
SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Robot Navigation in Unseen Environments using Coarse Maps.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024
Shield Decentralization for Safe Reinforcement Learning in General Partially Observable Multi-Agent Environments.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024
Entropy Seeking Constrained Multiagent Reinforcement Learning.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024
2023
On Centralized Critics in Multi-Agent Reinforcement Learning.
J. Artif. Intell. Res., 2023
Vision and Language Navigation in the Real World via Online Visual Language Mapping.
CoRR, 2023
Multi-Agent Reinforcement Learning Based on Representational Communication for Large-Scale Traffic Signal Control.
IEEE Access, 2023
On-Robot Bayesian Reinforcement Learning for POMDPs.
IROS, 2023
Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023
Improving Deep Policy Gradients with Value Function Search.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Equivariant Reinforcement Learning under Partial Observability.
Proceedings of the Conference on Robot Learning, 2023
Safe Deep Reinforcement Learning by Verifying Task-Level Properties.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023
2022
Deep Transformer Q-Networks for Partially Observable Reinforcement Learning.
CoRR, 2022
Hierarchical Reinforcement Learning Under Mixed Observability.
Proceedings of the Algorithmic Foundations of Robotics XV, 2022
Asymmetric DQN for partially observable reinforcement learning.
Proceedings of the Uncertainty in Artificial Intelligence, 2022
Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Shield Decentralization for Safe Multi-Agent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Safety-informed mutations for evolutionary deep reinforcement learning.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022
Leveraging Fully Observable Policies for Learning under Partial Observability.
Proceedings of the Conference on Robot Learning, 2022
BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022
Unbiased Asymmetric Reinforcement Learning under Partial Observability.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022
A Deeper Understanding of State-Based Critics in Multi-Agent Reinforcement Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Improving the Efficiency of Off-Policy Reinforcement Learning by Accounting for Past Decisions.
CoRR, 2021
Human-Level Control without Server-Grade Hardware.
CoRR, 2021
Investigating Alternatives to the Root Mean Square for Adaptive Gradient Methods.
CoRR, 2021
Unbiased Asymmetric Actor-Critic for Partially Observable Reinforcement Learning.
CoRR, 2021
End-to-end grasping policies for human-in-the-loop robots via deep reinforcement learning.
CoRR, 2021
Decentralized Reinforcement Learning for Multi-Target Search and Detection by a Team of Drones.
CoRR, 2021
Multi-agent reinforcement learning with directed exploration and selective memory reuse.
Proceedings of the SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing, 2021
Local Advantage Actor-Critic for Robust Multi-Agent Deep Reinforcement Learning.
Proceedings of the International Symposium on Multi-Robot and Multi-Agent Systems, 2021
Reconciling Rewards with Predictive State Representations.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021
End-to-end grasping policies for human-in-the-loop robots via deep reinforcement learning<sup>*</sup>.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021
Contrasting Centralized and Decentralized Critics in Multi-Agent Reinforcement Learning.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021
Safe Multi-Agent Reinforcement Learning via Shielding.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021
Stratified Experience Replay: Correcting Multiplicity Bias in Off-Policy Reinforcement Learning.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021
2020
Special Issue on the 2018 Robotics: Science and Systems Conference.
Int. J. Robotics Res., 2020
Expectigrad: Fast Stochastic Optimization with Robust Convergence Properties.
CoRR, 2020
To Ask or Not to Ask: A User Annoyance Aware Preference Elicitation Framework for Social Robots.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020
Learning Multi-Robot Decentralized Macro-Action-Based Policies via a Centralized Q-Net.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020
Hybrid Independent Learning in Cooperative Markov Games.
Proceedings of the Distributed Artificial Intelligence - Second International Conference, 2020
Hierarchical Robot Navigation in Novel Environments using Rough 2-D Maps.
Proceedings of the 4th Conference on Robot Learning, 2020
Belief-Grounded Networks for Accelerated Robot Learning under Partial Observability.
Proceedings of the 4th Conference on Robot Learning, 2020
Towards End-to-End Control of a Robot Prosthetic Hand via Reinforcement Learning.
Proceedings of the 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2020
Likelihood Quantile Networks for Coordinating Multi-Agent Reinforcement Learning.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020
Learning Complementary Representations of the Past using Auxiliary Tasks in Partially Observable Reinforcement Learning.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020
Multi-Agent/Robot Deep Reinforcement Learning with Macro-Actions (Student Abstract).
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Modeling and Planning with Macro-Actions in Decentralized POMDPs.
J. Artif. Intell. Res., 2019
Multi-Robot Deep Reinforcement Learning with Macro-Actions.
CoRR, 2019
AAAI/ACM SIGAI job fair 2019: a retrospective.
AI Matters, 2019
Reconciling λ-Returns with Experience Replay.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Online Planning for Target Object Search in Clutter under Partial Observability.
Proceedings of the International Conference on Robotics and Automation, 2019
Macro-Action-Based Deep Multi-Agent Reinforcement Learning.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019
Bayesian RL in Factored POMDPs.
Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019
Bayesian Reinforcement Learning in Factored POMDPs.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019
Learning to Teach in Cooperative Multiagent Reinforcement Learning.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
2018
On Improving Decentralized Hysteretic Deep Reinforcement Learning.
CoRR, 2018
Efficient Eligibility Traces for Deep Reinforcement Learning.
CoRR, 2018
Reports on the 2018 AAAI Spring Symposium Series.
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AI Mag., 2018
The art of drafting: a team-oriented hero recommendation system for multiplayer online battle arena games.
Proceedings of the 12th ACM Conference on Recommender Systems, 2018
Decision-Making Under Uncertainty in Multi-Agent and Multi-Robot Systems: Planning and Learning.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018
Q-DeckRec: A Fast Deck Recommendation System for Collectible Card Games.
Proceedings of the 2018 IEEE Conference on Computational Intelligence and Games, 2018
2017
Decentralized control of multi-robot partially observable Markov decision processes using belief space macro-actions.
Int. J. Robotics Res., 2017
Learning for multi-robot cooperation in partially observable stochastic environments with macro-actions.
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017
COG-DICE: An Algorithm for Solving Continuous-Observation Dec-POMDPs.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017
Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017
Scalable accelerated decentralized multi-robot policy search in continuous observation spaces.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability.
Proceedings of the 34th International Conference on Machine Learning, 2017
Learning in POMDPs with Monte Carlo Tree Search.
Proceedings of the 34th International Conference on Machine Learning, 2017
2016
A Concise Introduction to Decentralized POMDPs
Springer Briefs in Intelligent Systems, Springer, ISBN: 978-3-319-28929-8, 2016
Optimally Solving Dec-POMDPs as Continuous-State MDPs.
J. Artif. Intell. Res., 2016
Policy search for multi-robot coordination under uncertainty.
Int. J. Robotics Res., 2016
Reports of the AAAI 2016 Spring Symposium Series.
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AI Mag., 2016
Graph-based Cross Entropy method for solving multi-robot decentralized POMDPs.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016
Learning for Decentralized Control of Multiagent Systems in Large, Partially-Observable Stochastic Environments.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016
2015
Stick-Breaking Policy Learning in Dec-POMDPs.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
Exploiting Separability in Multiagent Planning with Continuous-State MDPs (Extended Abstract).
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
Decentralized control of Partially Observable Markov Decision Processes using belief space macro-actions.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015
Planning for decentralized control of multiple robots under uncertainty.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015
Probabilistic Planning for Decentralized Multi-Robot Systems.
Proceedings of the 2015 AAAI Fall Symposia, Arlington, Virginia, USA, November 12-14, 2015, 2015
Scalable Planning and Learning for Multiagent POMDPs.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
2014
Exploiting separability in multiagent planning with continuous-state MDPs.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014
Planning with macro-actions in decentralized POMDPs.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014
2013
Incremental Clustering and Expansion for Faster Optimal Planning in Dec-POMDPs.
J. Artif. Intell. Res., 2013
Decentralized control of partially observable Markov decision processes.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013
Producing efficient error-bounded solutions for transition independent decentralized mdps.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2013
2012
Scaling Up Decentralized MDPs Through Heuristic Search.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012
Using POMDPs to Control an Accuracy-Processing Time Trade-Off in Video Surveillance.
Proceedings of the Twenty-Fourth Conference on Innovative Applications of Artificial Intelligence, 2012
2011
Scaling Up Optimal Heuristic Search in Dec-POMDPs via Incremental Expansion.
Proceedings of the IJCAI 2011, 2011
Decision Support in Organizations: A Case for OrgPOMDPs.
Proceedings of the 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2011
Adaptive decision support for structured organizations: a case for OrgPOMDPs.
Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), 2011
Decentralized Models for Use in a Real-World Personal Assistant Agent Scenario.
Proceedings of the Help Me Help You: Bridging the Gaps in Human-Agent Collaboration, 2011
2010
Optimizing fixed-size stochastic controllers for POMDPs and decentralized POMDPs.
Auton. Agents Multi Agent Syst., 2010
Heuristic search for identical payoff Bayesian games.
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), 2010
High-level reinforcement learning in strategy games.
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), 2010
Finite-State Controllers Based on Mealy Machines for Centralized and Decentralized POMDPs.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010
2009
Policy Iteration for Decentralized Control of Markov Decision Processes.
J. Artif. Intell. Res., 2009
Achieving goals in decentralized POMDPs.
Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), 2009
Incremental Policy Generation for Finite-Horizon DEC-POMDPs.
Proceedings of the 19th International Conference on Automated Planning and Scheduling, 2009
2007
Optimizing Memory-Bounded Controllers for Decentralized POMDPs.
Proceedings of the UAI 2007, 2007
Solving POMDPs Using Quadratically Constrained Linear Programs.
Proceedings of the IJCAI 2007, 2007
2006
Finding Optimal POMDP Controllers Using Quadratically Constrained Linear Programs.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2006