Symphony

System for Yielding Multi-dimensional Problem Heuristic Optimization and Navigation

This is a C++ project focused on implementing search algorithms for rational agent problems. It provides a flexible, extensible framework for defining states, actions, and search strategies, along with example problems and test cases to ensure correctness and performance.

The inspiration is drawn from a university course on Artificial Intelligence, where students learn about rational agents, search algorithms, and problem-solving techniques. By providing a structured, modular codebase, this project aims to help students and enthusiasts understand and experiment with these concepts in a practical, hands-on way.

Getting Started

Prerequisites

• C++20 Compiler:
  Ensure you have a modern C++ compiler that supports C++20 (e.g., g++ >= 10 or clang++ >= 12).

• CMake (3.29 or newer):
  Used for building the project.

• GoogleTest Library (optional for running tests):
  Make sure gtest and gtest_main libraries are installed on your system, or use the provided configuration if you have them in your environment.

Building the Project

1. Clone the Repository:

   git clone https://github.com/velocitatem/Symphony
   cd ai_rational_agents

2. Configure and Build:

   mkdir build && cd build
   cmake ..
   make

   After building, the executables will be located in the build directory:

Extending the Project

mindmap
  root((Symphony))
    SubSystem 1 [Search Algorithms]
      AStarSearch
      BeamSearch
      BreadthFirstSearch
    SubSystem 2 [Problems]
      MazeProblem
        MazeState
      StudyProblem
        StudyState
      TaskScheduler
        TaskSchedulerState
      VacuumCleaner
        VacuumState
    SubSystem 3 [Core Components]
      State
      Action
      Problem
      Solution
    SubSystem 4 [Utilities]
      Definitions.h
      Search.h
      TaskScheduler.h
      SimpleMaze.h
      StudyPath.h
      Vacuum.h

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• Add New Problems:
  Create classes extending Problem and State, defining domain-specific logic, actions, and heuristics.

• Implement Additional Search Algorithms:
  Extend Search with new search strategies (e.g., DepthFirstSearch, UniformCostSearch, AStarSearch) and integrate them into the problem-solving pipeline.

• Additional Testing and CI:
  Add more test cases and integrate Continuous Integration (CI) to ensure code quality and maintainability.

Contributing

Contributions are welcome! If you find issues or want to add features, feel free to:

1. Fork the repository
2. Create a new branch (git checkout -b feature/my-feature)
3. Commit your changes (git commit -am 'Add my feature')
4. Push the branch (git push origin feature/my-feature)
5. Create a new Pull Request

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symphony is designed to be a springboard for further exploration into rational agents, search algorithms, and AI problem-solving techniques. With its clean architecture and example-driven approach, you can quickly adapt and extend it for your own research or educational projects.