most citedCollective eXplainable AI: Explaining Cooperative Strategies and Agent Contribution in Multiagent Reinforcement Learning with Shapley Values

1 citations · 1 across the 1 of their papers we have counts for

collaborators

2 papers

cs.AI2021★ 1 cited

Collective eXplainable AI: Explaining Cooperative Strategies and Agent Contribution in Multiagent Reinforcement Learning with Shapley Values

Alexandre Heuillet, Fabien Couthouis, Natalia Díaz-Rodríguez

While Explainable Artificial Intelligence (XAI) is increasingly expanding more areas of application, little has been applied to make deep Reinforcement Learning (RL) more comprehen…

cs.AI2020

Explainability in Deep Reinforcement Learning

Alexandre Heuillet, Fabien Couthouis, Natalia Díaz-Rodríguez

A large set of the explainable Artificial Intelligence (XAI) literature is emerging on feature relevance techniques to explain a deep neural network (DNN) output or explaining mode…