Deep Reinforcement Learning (DRL) uses the best of both Reinforcement Learning and Deep Learning for solving problems which cannot be addressed by them individually. Deep Reinforcement Learning has been used widely for games, robotics etc. Limited work ...
In this paper we propose a novel, phenomenological approach to explainable Reinforcement Learning (RL). While the ever-increasing performance of RL agents surpasses human capabilities on many problems, it falls short concerning explainability, ...
New double beam algorithms for subgroup discovery (SD) and classification rules (RL).Algorithms can use different heuristics for rule refinement and rule selection.Variants of new SD algorithm give more interesting rules than state-of-the-art.RL ...
Association for Computing Machinery
New York, NY, United States
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