Project Grant 2446527

This National Science Foundation (NSF) award under the Engineering program (CFDA 47.041) provides $356,488 to the Texas A&M Engineering Experiment Station (Tees) for the project "CAREER: REINFORCEMENT LEARNING-BASED CONTROL OF HETEROGENEOUS MULTI-AGENT SYSTEMS IN STRUCTURED ENVIRONMENTS: ALGORITHMS AND COMPLEXITY". The objective is to develop resilient reinforcement learning (RL) frameworks and scalable RL algorithms for managing heterogeneous multi-agent systems in complex, structured environments. The research aims to advance RL-based control for applications like interference management in wireless networks and energy control in power networks. The project will generate educational benefits by integrating the research into engineering courses and involving undergraduate/graduate students. No subawards are planned under this grant, which has an ultimate completion date of June 30, 2028.