A survey on algorithms for Nash equilibria in finite normal-form games.
Comput. Sci. Rev., 2024
Stochastic Games with Minimally Bounded Action Costs.
CoRR, 2024
All Language Models Large and Small.
CoRR, 2024
A Summary of Online Markov Decision Processes with Non-oblivious Strategic Adversary.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024
Online Markov decision processes with non-oblivious strategic adversary.
Auton. Agents Multi Agent Syst., June, 2023
Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models.
CoRR, 2023
MANSA: Learning Fast and Slow in Multi-Agent Systems.
CoRR, 2023
Ensemble Value Functions for Efficient Exploration in Multi-Agent Reinforcement Learning.
CoRR, 2023
ChessGPT: Bridging Policy Learning and Language Modeling.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems.
Proceedings of the International Conference on Machine Learning, 2023
MANSA: Learning Fast and Slow in Multi-Agent Systems.
Proceedings of the International Conference on Machine Learning, 2023
Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Learning to Shape Rewards Using a Game of Two Partners.
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Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
Trans. Mach. Learn. Res., 2022
Semi-Centralised Multi-Agent Reinforcement Learning with Policy-Embedded Training.
CoRR, 2022
Learning Risk-Averse Equilibria in Multi-Agent Systems.
CoRR, 2022
SEREN: Knowing When to Explore and When to Exploit.
CoRR, 2022
On the Convergence of Fictitious Play: A Decomposition Approach.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation.
Proceedings of the International Conference on Machine Learning, 2022
LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Socially-Attentive Policy Optimization in Multi-Agent Self-Driving System.
Proceedings of the Conference on Robot Learning, 2022
On the Complexity of Computing Markov Perfect Equilibrium in General-Sum Stochastic Games.
Electron. Colloquium Comput. Complex., 2021
DESTA: A Framework for Safe Reinforcement Learning with Markov Games of Intervention.
CoRR, 2021
Learning to Shape Rewards using a Game of Switching Controls.
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CoRR, 2021
Modelling Behavioural Diversity for Learning in Open-Ended Games.
CoRR, 2021
Settling the Variance of Multi-Agent Policy Gradients.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Modelling Behavioural Diversity for Learning in Open-Ended Games.
Proceedings of the 38th International Conference on Machine Learning, 2021
Learning in Nonzero-Sum Stochastic Games with Potentials.
Proceedings of the 38th International Conference on Machine Learning, 2021
Multi-Agent Determinantal Q-Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020
Cutting Your Losses: Learning Fault-Tolerant Control and Optimal Stopping under Adverse Risk.
CoRR, 2019
Coordinating the Crowd: Inducing Desirable Equilibria in Non-Cooperative Systems.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019
Decentralised Learning in Systems With Many, Many Strategic Agents.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018