* Currently this is specific to the case of discretizing a continuous action space. Can easily be adapted to other case by feeding the kNN otherwise, and removing the usage of a discretizing output action filter
* SAC algorithm
* SAC - updates to agent (learn_from_batch), sac_head and sac_q_head to fix problem in gradient calculation. Now SAC agents is able to train.
gym_environment - fixing an error in access to gym.spaces
* Soft Actor Critic - code cleanup
* code cleanup
* V-head initialization fix
* SAC benchmarks
* SAC Documentation
* typo fix
* documentation fixes
* documentation and version update
* README typo
* initial ACER commit
* Code cleanup + several fixes
* Q-retrace bug fix + small clean-ups
* added documentation for acer
* ACER benchmarks
* update benchmarks table
* Add nightly running of golden and trace tests. (#202)
Resolves#200
* comment out nightly trace tests until values reset.
* remove redundant observe ignore (#168)
* ensure nightly test env containers exist. (#205)
Also bump integration test timeout
* wxPython removal (#207)
Replacing wxPython with Python's Tkinter.
Also removing the option to choose multiple files as it is unused and causes errors, and fixing the load file/directory spinner.
* Create CONTRIBUTING.md (#210)
* Create CONTRIBUTING.md. Resolves#188
* run nightly golden tests sequentially. (#217)
Should reduce resource requirements and potential CPU contention but increases
overall execution time.
* tests: added new setup configuration + test args (#211)
- added utils for future tests and conftest
- added test args
* new docs build
* golden test update
* updating the documentation website
* adding the built docs
* update of api docstrings across coach and tutorials 0-2
* added some missing api documentation
* New Sphinx based documentation
