Deep Reinforcement Algorithms for OpenAI Minigrid
Budget: $30 – $250 USD
Looking for an expert in reinforcement learning to implement DQN, Policy Gradient, and Actor Critic algorithms for the Open AI Minigrid problem. The purpose of this project is to increase overall performance in navigation tasks.
Key Requirements:
- Implement the three reinforcement algorithms: DQN, Policy Gradient, Actor Critic
- Scope of the problem should be simple - few obstacles
- Measure and document the increase in the performance of navigation tasks
Ideal freelancer would have:
- Proven experience in implementing reinforcement learning algorithms
- Familiarity with OpenAI's Gym environments.
- Clear understanding of Policy Gradient and Actor-Critic methods
- Ability to simplify complex ideas for testing purposes.
Please provide examples of similar projects you have completed. Your bid will be more effectively considered if you propose a clear plan on how you'll approach the problem.
Key Requirements:
- Implement the three reinforcement algorithms: DQN, Policy Gradient, Actor Critic
- Scope of the problem should be simple - few obstacles
- Measure and document the increase in the performance of navigation tasks
Ideal freelancer would have:
- Proven experience in implementing reinforcement learning algorithms
- Familiarity with OpenAI's Gym environments.
- Clear understanding of Policy Gradient and Actor-Critic methods
- Ability to simplify complex ideas for testing purposes.
Please provide examples of similar projects you have completed. Your bid will be more effectively considered if you propose a clear plan on how you'll approach the problem.