The deep reinforcement learning (DRL) community has published remarkable results on complex strategic planning problems …

environmental stimuli (observational learning, reinforcement learning), organism cognition (self-efficacy, outcome expectancy) to … outcome expectancy. In contrast, reinforcement learning influenced the organism's cognition of contributors and partially …

reinforcement learning (DRL) implemented with OpenAI frameworks. In realistic manufacturing environments, dynamic events endanger …

for hybrid disassembly systems, based on reinforcement learning, alongside a comprehensive modeling approach is presented …

We apply Multi-Agent Deep Reinforcement Learning (MADRL) to inventory management problems with multiple echelons and … constructed by single-agent deep reinforcement learning and other heuristic policies. Also, the application of HAPPO results in a … less significant bullwhip effect than policies constructed by single-agent deep reinforcement learning where information is …