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pro vyhledávání: '"Parac, Roko"'
Autor:
Parac, Roko, Nodari, Lorenzo, Ardon, Leo, Furelos-Blanco, Daniel, Cerutti, Federico, Russo, Alessandra
This paper presents PROB-IRM, an approach that learns robust reward machines (RMs) for reinforcement learning (RL) agents from noisy execution traces. The key aspect of RM-driven RL is the exploitation of a finite-state machine that decomposes the ag
Externí odkaz:
http://arxiv.org/abs/2408.14871
