TA-Shaim-12/Multi-Agent-Intelligent-Chase-Game

Repository implements a simulated chase game where multiple AI-controlled police agents pursue a thief to demonstrate real-time decision-making with classic search algorithms and measurement tools. Intended for researchers, students, instructors and developers working on multi-agent systems, game AI, and algorithm comparison. Key features: - Multi-agent pursuit-evasion scenario (police vs. thief). - Integration of classic search methods for agent planning (configurable algorithm selection). - Real-time decision loop to compare responsiveness and behavior under different strategies. - Performance analytics and logs for runtime, path quality, and success metrics. - Configurable maps and scenarios to reproduce experiments and evaluate algorithmic tradeoffs.

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