0.2.4
Algorithm Implementation
- n_step returns for all Q-learning based algorithms; (#51)
- Auto alpha tuning in SAC (#80)
- Reserve
policy._state
to support saving hidden states in replay buffer (#19) - Add
sample_avail
argument in ReplayBuffer to sample only available index in RNN training mode (#19)
New Feature
- Batch.cat (#87), Batch.stack (#93), Batch.empty (#106, #110)
- Advanced slicing method of Batch (#106)
Batch(kwargs, copy=True)
will perform a deep copy (#110)- Add
random=True
argument in collector.collect to perform sampling with random policy (#78)
API Change
Batch.append
->Batch.cat
- Remove atari wrapper to examples, since it is not a key feature in tianshou (#124)
- Add some pre-defined nets in
tianshou.utils.net
. Since we only define API instead of a class, we do not present it intianshou.net
. (#123)
Docs
Add cheatsheet: https://tianshou.readthedocs.io/en/latest/tutorials/cheatsheet.html