Our paper titled Combining Planning and Reinforcement Learning for Solving Relational Multiagent Domains has been accepted to AAMAS 2025

Our paper titled “Combining Planning and Reinforcement Learning for Solving Relational Multiagent Domains” has been accepted to the 24th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS) 2025! This work focuses on sequential-decision making in Multiagent Reinforcement Learning (MARL) which is challenging because of several issues like the curse of dimensionality, non-stationarity of the environment and credit assignment, thus, introduces a novel framework MaRePReL (Multiagent Relational Planning and Reinforcement Learning) that is designed to address these challenges by integrating hierarchical relational planning with reinforcement learning.