q-values-tracking

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ChaitanyaC22 / Deep-RL-Project---Maximize-total-profits-earned-by-cab-driver
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 formulated as a Markov Decision Process i.e. MDP.
mdp-framework markov-decision-process dqn deep-reinforcement-learning rl training-dqn-agent q-values-tracking actions states rewards hyperparameter-tuning model-building model-evaluation prediction minibatch-gradient-descent convergence data-visualization optimal-policy epsilon-decay epsilon-greedy
Language:Jupyter Notebook 9

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