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https://github.com/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.
https://github.com/chaitanyac22/deep-rl-project---maximize-total-profits-earned-by-cab-driver
actions convergence data-visualization deep-reinforcement-learning dqn epsilon-decay epsilon-greedy hyperparameter-tuning markov-decision-process mdp-framework minibatch-gradient-descent model-building model-evaluation optimal-policy prediction q-values-tracking rewards rl states training-dqn-agent
Last synced: 3 days ago
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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 formulated as a Markov Decision Process i.e. MDP.
- Host: GitHub
- URL: https://github.com/chaitanyac22/deep-rl-project---maximize-total-profits-earned-by-cab-driver
- Owner: ChaitanyaC22
- License: mit
- Created: 2021-03-11T20:36:35.000Z (almost 4 years ago)
- Default Branch: chai_main
- Last Pushed: 2021-07-09T18:27:29.000Z (over 3 years ago)
- Last Synced: 2023-04-24T16:37:09.815Z (almost 2 years ago)
- Topics: actions, convergence, data-visualization, deep-reinforcement-learning, dqn, epsilon-decay, epsilon-greedy, hyperparameter-tuning, markov-decision-process, mdp-framework, minibatch-gradient-descent, model-building, model-evaluation, optimal-policy, prediction, q-values-tracking, rewards, rl, states, training-dqn-agent
- Language: Jupyter Notebook
- Homepage:
- Size: 1.61 MB
- Stars: 4
- Watchers: 1
- Forks: 3
- Open Issues: 0