Deterministic dynamics of distributional multi-agent reinforcement learning
Clémence Bergerot, Paweł Romańczuk, Wolfram Barfuß
This paper develops a computational framework for distributional multi-agent reinforcement learning, showing how optimism, reward discretization, and temporal discounting interact to shape decision-making.
PLoS Computational Biology · Sep 23, 2026Peer-reviewedNeuroscience