Abstract: This paper presents a deep reinforcement learning (RL) approach for training mobile robots to navigate complex environments using the Twin Delayed Deep Deterministic Policy Gradient (TD3) ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...

Abstract: Cooperative multi-agent reinforcement learning (MARL) is a key technology for enabling cooperation in complex multi-agent systems. It has achieved remarkable progress in areas such as gaming ...

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It is often possible to separate the reinforcement from the matrix by physical processes. For example, reinforced concrete can be broken up using machinery. This is one stage in recycling the ...