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125c7ee38d
Main changes are detailed below: New features - * CARLA 0.7 simulator integration * Human control of the game play * Recording of human game play and storing / loading the replay buffer * Behavioral cloning agent and presets * Golden tests for several presets * Selecting between deep / shallow image embedders * Rendering through pygame (with some boost in performance) API changes - * Improved environment wrapper API * Added an evaluate flag to allow convenient evaluation of existing checkpoints * Improve frameskip definition in Gym Bug fixes - * Fixed loading of checkpoints for agents with more than one network * Fixed the N Step Q learning agent python3 compatibility
39 lines
1.8 KiB
YAML
39 lines
1.8 KiB
YAML
site_name: Reinforcement Learning Coach Documentation
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theme: readthedocs
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site_description: 'Reinforcement Learning Coach Documentation by Intel Nervana.'
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markdown_extensions:
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- mdx_math:
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enable_dollar_delimiter: True #for use of inline $..$
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extra_javascript: ['https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS_HTML']
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extra_css: [extra.css]
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pages:
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- Home : index.md
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- Design: design.md
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- Usage: usage.md
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- Algorithms:
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- 'DQN' : algorithms/value_optimization/dqn.md
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- 'Double DQN' : algorithms/value_optimization/double_dqn.md
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- 'Dueling DQN' : algorithms/value_optimization/dueling_dqn.md
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- 'Categorical DQN' : algorithms/value_optimization/categorical_dqn.md
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- 'Mixed Monte Carlo' : algorithms/value_optimization/mmc.md
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- 'Persistent Advantage Learning' : algorithms/value_optimization/pal.md
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- 'Neural Episodic Control' : algorithms/value_optimization/nec.md
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- 'Bootstrapped DQN' : algorithms/value_optimization/bs_dqn.md
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- 'N-Step Q Learning' : algorithms/value_optimization/n_step.md
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- 'Normalized Advantage Functions' : algorithms/value_optimization/naf.md
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- 'Policy Gradient' : algorithms/policy_optimization/pg.md
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- 'Actor-Critic' : algorithms/policy_optimization/ac.md
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- 'Deep Determinstic Policy Gradients' : algorithms/policy_optimization/ddpg.md
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- 'Proximal Policy Optimization' : algorithms/policy_optimization/ppo.md
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- 'Clipped Proximal Policy Optimization' : algorithms/policy_optimization/cppo.md
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- 'Direct Future Prediction' : algorithms/other/dfp.md
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- 'Behavioral Cloning' : algorithms/imitation/bc.md
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- Coach Dashboard : 'dashboard.md'
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- Contributing :
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- Adding a New Agent : 'contributing/add_agent.md'
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- Adding a New Environment : 'contributing/add_env.md'
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