abstract
We propose BlastPursuit for the Multi-Agent Systems project. This innovative project aims to create an augmented version of the classic Bomberman game, showcasing advanced concepts of multi-agent systems, including agent autonomy, strategic interaction, and adaptive learning within a complex environment. Our primary objective is to develop a multi-agent system where two squads of agents, Bombermen and Killers, each with distinct goals, navigate and interact within a grid-based environment. By employing various Reinforcement Learning (RL) algorithms, we aim to investigate their efficacy in enabling these agents to develop successful strategies and autonomously make decisions in different scenarios.
outcomes
