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02/07/2023
Ensemble Value Functions for Efficient Exploration in Multi-Agent Reinforcement Learning
Cooperative multi-agent reinforcement learning (MARL) requires agents to...
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09/02/2022
Semi-Centralised Multi-Agent Reinforcement Learning with Policy-Embedded Training
Centralised training (CT) is the basis for many popular multi-agent rein...
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05/31/2022
Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints
Many real-world settings involve costs for performing actions; transacti...
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05/30/2022
SEREN: Knowing When to Explore and When to Exploit
Efficient reinforcement learning (RL) involves a trade-off between "expl...
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02/14/2022
SAUTE RL: Almost Surely Safe Reinforcement Learning Using State Augmentation
Satisfying safety constraints almost surely (or with probability one) ca...
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03/16/2021
Learning to Shape Rewards using a Game of Switching Controls
Reward shaping (RS) is a powerful method in reinforcement learning (RL) ...
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05/27/2020
Stochastic Potential Games
Computing the Nash equilibrium (NE) for N-player non-zerosum stochastic ...
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01/30/2019
Coordinating the Crowd: Inducing Desirable Equilibria in Non-Cooperative Systems
Many real-world systems such as taxi systems, traffic networks and smart...
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03/13/2018