Welcome to the Multi-Agent Search Algorithms and Coordination project! This project is dedicated to helping you understand, visualize, and experiment with multi-agent search algorithms and coordination strategies in the context of artificial intelligence.
Multi-agent systems involve multiple intelligent agents working together to achieve common goals or solve complex problems. This project offers an interactive platform to explore and analyze how these agents cooperate, coordinate, and navigate through dynamic environments. You can gain insights into the workings of algorithms for tasks like pathfinding, task allocation, and coordination.
- Visualize multi-agent systems in action.
- Explore various coordination algorithms and strategies.
- Compare the performance of different multi-agent search techniques.
- Experiment with dynamic and challenging scenarios.
- Analyze the efficiency and effectiveness of coordination strategies.
- Clone this repository to your local machine.
- Open the project in your preferred development environment.
- Run the application to start visualizing multi-agent search algorithms.
- Launch the application.
- Select the multi-agent search algorithm or coordination strategy you want to explore.
- Define the environment and tasks for the multi-agent system.
- Observe how the agents collaborate, communicate, and navigate to achieve their objectives.
- Analyze the performance metrics and insights.
Happy exploring and experimenting with multi-agent search and coordination!