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A Policy-Graph Approach to Explain Reinforcement Learning Agents: A Novel Policy-Graph Approach with Natural Language and Counterfactual Abstractions for Explaining Reinforcement Learning Agents

2023-01-02

Abstract excerpt

<title>Abstract</title> <p>As reinforcement learning (RL) continues to improve and be appliedin situations alongside humans, the need to explain the learned behaviorsof RL agents to end-users becomes more important. Strategies forexplaining the reasoning behind an agent’s policy, called policy-levelexplanations, can lead to important insights about both the task and theagent’s behaviors. Following this line of re...

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Literature Corpus work: 0d5a4ecb-eb09-5cb4-9dd8-9195ffc50465
DOI: 10.21203/rs.3.rs-2409910/v1

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