https://github.com/chaitanyac22/numerical_tictactoe_agent_using_reinforcement_learning
Build an RL (Reinforcement Learning) agent that learns to play Numerical Tic-Tac-Toe. The agent learns the game by Q-Learning.
https://github.com/chaitanyac22/numerical_tictactoe_agent_using_reinforcement_learning
actions convergence episodes epsilon-decay epsilon-greedy hyperparameter-tuning learning-rate markov-decision-process mdp-framework model-building policy q-learning q-learning-algorithm q-value q-value-iteration reinforcement-learning rewards rl states
Last synced: about 1 month ago
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Build an RL (Reinforcement Learning) agent that learns to play Numerical Tic-Tac-Toe. The agent learns the game by Q-Learning.
- Host: GitHub
- URL: https://github.com/chaitanyac22/numerical_tictactoe_agent_using_reinforcement_learning
- Owner: ChaitanyaC22
- License: mit
- Created: 2021-03-11T19:46:30.000Z (about 4 years ago)
- Default Branch: chai_main
- Last Pushed: 2021-07-09T18:28:08.000Z (almost 4 years ago)
- Last Synced: 2025-02-01T12:13:18.732Z (3 months ago)
- Topics: actions, convergence, episodes, epsilon-decay, epsilon-greedy, hyperparameter-tuning, learning-rate, markov-decision-process, mdp-framework, model-building, policy, q-learning, q-learning-algorithm, q-value, q-value-iteration, reinforcement-learning, rewards, rl, states
- Language: Jupyter Notebook
- Homepage:
- Size: 23.2 MB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0