Swopper050 foundations-drl issues

Swopper050 / foundations-drl

Implementing the base algorithms of Deep Reinforcement Learning in Python

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Updated requirements and switched to gymnasium

#26 Swopper050 closed 11 months ago
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Having trouble running simple REINFORCE example

#25 aveshd closed 11 months ago
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Added PPO

#24 Swopper050 closed 3 years ago
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Add Proximal Policy Optimization

#23 Swopper050 closed 3 years ago
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Added the Advantage Actor-Critic (A2C) algorithm

#22 Swopper050 closed 3 years ago
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Implement A2C

#21 Swopper050 closed 3 years ago
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Improved parsers

#20 Swopper050 closed 3 years ago
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Improve parser for training and inspecting agents

#19 Swopper050 closed 3 years ago
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Written docs for all algorithms

#18 Swopper050 closed 3 years ago
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Added improved DQN implementation with PER and Double Q networks

#17 Swopper050 closed 3 years ago
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Add improved DQN

#16 Swopper050 closed 3 years ago
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Added vanilla DQN

#15 Swopper050 closed 3 years ago
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Implement vanilla DQN

#14 Swopper050 closed 3 years ago
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Makefile and lint

#13 Swopper050 closed 3 years ago
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Add Makefile

#12 Swopper050 closed 3 years ago
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Added the Sarsa algorithm

#11 Swopper050 closed 3 years ago
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Write good docs + code cleanup

#10 Swopper050 closed 3 years ago
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Do not overwrite the 'train' method on torch nn modules

#9 Swopper050 closed 3 years ago
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Implement SARSA algorithm

#8 Swopper050 closed 3 years ago
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Agents are now saved and possible to inspect them

#7 Swopper050 closed 3 years ago
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Utility for saving and inspecting agents

#6 Swopper050 closed 3 years ago
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Added continuous reinforce agent (although does not converge well)

#5 Swopper050 closed 3 years ago
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Added baseline for discrete reinforce agent and plots

#4 Swopper050 closed 3 years ago
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Baseline for reinforce agent traning

#3 Swopper050 closed 3 years ago
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Memory for reinforce agents

#2 Swopper050 closed 3 years ago
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Implement continuous reinforce agent

#1 Swopper050 closed 3 years ago
0