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epsilon-decay

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ChaitanyaC22 / Deep-RL-Project---Maximize-total-profits-earned-by-cab-driver

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The goal of this project is to build an RL-based algorithm that can help cab drivers maximize their profits by improving their decision-making process on the field. Taking long-term profit as the goal, a method is proposed based on reinforcement learning to optimize taxi driving strategies for profit maximization. This optimization problem is fo…

actions deep-reinforcement-learning prediction data-visualization convergence dqn epsilon-greedy states rl rewards hyperparameter-tuning model-evaluation model-building optimal-policy markov-decision-process epsilon-decay mdp-framework training-dqn-agent q-values-tracking minibatch-gradient-descent
  • Updated Jul 9, 2021
  • Jupyter Notebook

ChaitanyaC22 / Numerical_TicTacToe_Agent_using_Reinforcement_Learning

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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.

reinforcement-learning actions q-learning policy episodes convergence epsilon-greedy states rl rewards hyperparameter-tuning learning-rate model-building q-value markov-decision-process q-learning-algorithm epsilon-decay q-value-iteration mdp-framework
  • Updated Jul 9, 2021
  • Jupyter Notebook

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