Abstract: This study focuses on the application of reinforcement learning in tactical military simulation environments involving heterogeneous multi-agent systems. Optimizing Heterogeneous Multi-Agent ...
Abstract: This paper presents a simulation-based benchmarking analysis of three reinforcement learning (RL) algorithms—Soft Actor-Critic (SAC), Deep Q-Network (DQN), and Proximal Policy Optimization ...
Even a JRPG's combat system needs to evolve alongside its characters if you want to go from rat hunting to god slaying.
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