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# tianshou
-Tianshou(天授) is a reinforcement learning platform.
+Tianshou(天授) is a reinforcement learning platform. The following image illustrate its architecture.
-
+
-## data
-TODO:
+## agent
+ Examples
-Replay Memory
-
-Multiple wirter/reader
-
-Importance sampling
-
-## simulator
-go(for AlphaGo)
-
-## environment
-gym
+ Self-play Framework
## core
-TODO:
-Optimizer
+### Model
+ DQN, Policy-Value Network of AlphaGo Zero, PPO-specific, TROP-specific
-MCTS
+### Algorithm
-## agent (optional)
+#### Loss design
+ Actor-Critic (Variations), DQN (Variations), DDPG, TRPO, PPO
-DQNAgent etc.
+#### Optimization method
+ SGD, ADAM, TRPO, natural gradient, etc.
-## Pontential Bugs:
+### Planning
+ MCTS
-0. Wrong calculation of eval value
+## data
+ Training style - Monte Carlo or Temporal Difference
-UCTNode.cpp
-```
-106 if (to_move == FastBoard::WHITE) {
-107 net_eval = 1.0f - net_eval;
-108 }
+ Reward Reshaping/ Advantage Estimation Function
-309 if (tomove == FastBoard::WHITE) {
-310 score = 1.0f - score;
-311 }
-```
+ Importance weight
-1. create children only on leaf node
+ Multithread Read/Write
-UCTSearch.cpp
-```
- 60 if (!node->has_children() && m_nodes < MAX_TREE_SIZE) {
- 61 float eval;
- 62 auto success = node->create_children(m_nodes, currstate, eval);
- 63 if (success) {
- 64 result = SearchResult(eval);
- 65 }
- 66 }
-```
+## environment
+ DQN repeat frames etc.
+## simulator
+ Go, Othello/Reversi, Warzone
+
+## TODO
+Search based method parallel.
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