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XAI4DRL 2024 : AAAI-2024 Workshop on eXplainable Artificial Intelligence for Deep Reinforcement Learning (XAI4DRL) | |||||||||
Link: https://xai4drl.github.io | |||||||||
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Call For Papers | |||||||||
Dear all,
We are pleased to announce the AAAI 2024 Workshop on eXplainable AI approaches for deep reinforcement learning (XAI4DRL). The workshop aims at collecting novel methods and discussing challenges, issues, and goals around the intersection of deep reinforcement learning with Explainable Artificial Intelligence (XAI). Indeed, despite recent progress in deep reinforcement learning (DRL), the black-box nature of deep neural networks and the complex interaction among various factors, such as the environment, reward policy, and state representation, raise challenges in understanding and interpreting DRL models’ decision-making processes. The workshop aims at collecting methods, techniques, and frameworks to enhance the explainability and interpretability of DRL algorithms, and to define standardized metrics and protocols to evaluate the performance and transparency of autonomous systems. === Topics === - XAI methods for Deep Learning - Evaluation of XAI methods - Self-Explainable Deep Reinforcement Learning - Post-hoc methods for Deep Reinforcement Learning - XAI-based Augmentation for Deep Reinforcement Learning - Policies Interpretation - Current-trend and Challenges in explaining Deep Reinforcement Learning - Reinforcement Learning-based XAI methods - Self-Explainable Deep Learning - Interpreting Reinforcement Learning - Debugging Deep Reinforcement Learning using XAI - Applications of Deep Reinforcement Learning combined with XAI to real-world tasks - Position papers on the topic of the workshop. === Tracks and Important dates === We solicit submissions of previously unpublished papers, both as short and full papers. Short papers are up to 4 pages max without any supplemental material associated with. Full papers are up to 7 pages and can be associated with supplementary materials (unlimited pages for supplemental material). Accepted papers will be presented as contributed talks during the workshop, or during a poster section. == Organizers == Alessio Ragno, Sapienza University of Rome Biagio La Rosa, Sapienza University of Rome Leilani Gilpin, University of California, Santa Cruz Michela Proietti, Sapienza University of Rome Oliver Chang, University of California, Santa Cruz Roberto Capobianco, Sony AI & Sapienza University of Rome == Contact == https://xai4drl.github.io/ Best regards, The workshop's organizers |
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