Causal Reinforcement Learning using Observational and Interventional Data

Autor: Gasse, Maxime, Grasset, Damien, Gaudron, Guillaume, Oudeyer, Pierre-Yves

Learning efficiently a causal model of the environment is a key challenge of model-based RL agents operating in POMDPs. We consider here a scenario where the learning agent has the ability to collect online experiences through direct interactions wit

Externí odkaz: http://arxiv.org/abs/2106.14421

Autonomous drone interception with Deep Reinforcement Learning

Autor: Bertoin, David, Gauffriau, Adrien, Grasset, Damien, Gupta, Jayant Sen

Publikováno v: ATT 2022: Agents in Traffic and Transportation-Twelfth International Workshop on Agents in Traffic and Transportation co-located with the the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022) Vienna, Austria, July 25, 2022.
12th International Workshop on Agents in Traffic and Transportation (ATT 2022) in conjunction with IJCAI-ECAI 2022
12th International Workshop on Agents in Traffic and Transportation (ATT 2022) in conjunction with IJCAI-ECAI 2022, Jul 2022, Vienne, Austria

co-located with the the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022); International audience; Driven by recent successes in artificial intelligence, new a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______4074::4ff9f9d53df1b40b3a165e114d644311
https://hal.science/hal-03930080