The book is a collection of cutting-edge research on the topic of explainable agency in artificial intelligence (XAI), including counterfactuals, fairness, human evaluations, and iterative and active communication among agents.
The book is a collection of cutting-edge research on the topic of explainable agency in artificial intelligence (XAI), including counterfactuals, fairness, human evaluations, and iterative and active communication among agents.
Dr. Silvia Tulli is an Assistant Professor at Sorbonne University. She received her Marie Curie ITN research fellowship and completed her Ph.D. at Instituto Superior Técnico. Her research interests lie at the intersection of explainable AI, interactive machine learning, and reinforcement learning. Dr. David W. Aha (UC Irvine, 1990) serves as the Director of the AI Center at the Naval Research Laboratory in Washington, DC. His research interests include goal reasoning agents, deliberative autonomy, case-based reasoning, explainable AI, machine learning (ML), reproducible studies, and related topics.
Inhaltsangabe
1. From Explainable to Justified Agency 2. A Survey of Global Explanations in Reinforcement Learning 3. Integrated Knowledge-Based Reasoning and Data-Driven Learning for Explainable Agency in Robotics 4. Explanation as Question Answering Based on User Guides 5. Interpretable Multi-Agent Reinforcement Learning with Decision-Tree Policies 6. Towards the Automatic Synthesis of Interpretable Chess Tactics 7. The Need for Empirical Evaluation of Explanation Quality
1. From Explainable to Justified Agency 2. A Survey of Global Explanations in Reinforcement Learning 3. Integrated Knowledge-Based Reasoning and Data-Driven Learning for Explainable Agency in Robotics 4. Explanation as Question Answering Based on User Guides 5. Interpretable Multi-Agent Reinforcement Learning with Decision-Tree Policies 6. Towards the Automatic Synthesis of Interpretable Chess Tactics 7. The Need for Empirical Evaluation of Explanation Quality
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