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AI Plays (Classical Methods)

This repository is a collection of various Classical AI and Reinforcement Learning algorithms for building agents that can play simple games or solve problems. This repo is a precursor to a future collection of Deep Reinforcement Learning Algorithms.

Contents

  1. Implementation of Two Player TicTacToe Game
  2. Solving N-Queens (a Constraint Satisfaction Problem) with Backtracking
  3. Solving Mazes with Various Search Algorithms

TODO

A checklist of things to do in this repository.

  • Code a Normal 2 Player TicTacToe Terminal Game
  • Solving a Constraint Satisfaction Problem (NQueens) using Backtracking
  • Maze Solving with DFS and BFS
  • Maze Solving with A* Search
  • Monte Carlo Methods for Blackjack
  • Create Gym Environment for TicTacToe
  • MinMax Algorithm and Self-Play
  • NeuroEvolution
  • Classical Q Learning