PULLULAN BASED DERIVATIVES: SYNTHESIS, ENHANCED PHYSICOCHEMICAL PROPERTIES, AND APPLICATIONS



Two-stage reward allocation with decay for multi-agent coordinated behavior for sequential cooperative task by using deep reinforcement learning

Abstract We propose a two-stage reward allocation method with decay using an extension of replay memory to adapt this rewarding method for deep reinforcement learning (DRL), to generate coordinated behaviors for tasks that can be completed by executing rike knife lamella a few subtasks sequentially by heterogeneous agents.An independent learner in

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