Oct 24, 2017 · In this paper, we consider agents under training and improve the IBE for the application to agents with changing policy.
In this paper, we consider agents under training and improve the IBE for the application to agents with changing policy. We conducted an experiment to verify if ...
In this paper, we propose Instruction-based Behavior Explanation (IBE), a method to explain an autonomous agent's future behavior. In IBE, an agent can ...
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IRL is a framework in which a machine learning agent receives expert's instructions to accelerate the agent's policy acquisition. The IBE reuses the ...
Oct 20, 2018 · In this paper, we propose Instruction-based Behavior Explanation (IBE), a method to explain an autonomous agent's future behavior.
Feb 1, 2024 · Off-policy methods like Q-learning allow one to predict what happens under another policy while behaving under a different policy. For Q- ...
Missing: Instruction- Based
In this paper, we apply an explainability method based on the creation of a Policy Graph (PG) based on discrete predicates that represent and explain a trained ...
Reinforcement learning methods are ways that the agent can learn behaviors to achieve its goal. ... Actions come from an agent according to its policy.
May 20, 2021 · This review looks to explore current approaches and limitations for XAI in the area of Reinforcement Learning (RL).
Aug 15, 2021 · In this paper, we start from deep deterministic policy gradient (DDPG) algorithm and then introduce multi-agent DDPG (MADDPG) to solve the multi-agent defense ...