# Document changes of the master branch here ...
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Release 3.2.1, 2021-06-23

1) Single-line command to start experiments from yaml
2) Various Bug fixes
3) Improvement of documentation

The documentation can be found at: http://docs.palaestr.ai/
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Release 3.2, 2021-06-03

Increased system usability and introduced changes to experiment files.

1) Changed term "experiment" to "run" throughout the project to better reflect DOE terminology.
2) Enabled multiple run phases to allow for, e.g., a training and a test phase (breaking: the run yaml file structure was modified from the old experient yaml structure and needs to be updated)
3) Introduction for an abstract Reward class to allow for implementation of customized rewards in environments (breaking: the reward in environment implementations have to be modified to the new structure)
4) Cleaned up bloated log messages and alllowed for better configurability of logs through finer grained log levels
5) Removed requirement of docker and postgreSQL to run palaestrai - no database is required to run palaestrai and an sqlite fallback was implemented
6) Changed multiprocessing from fork to spawn to avoid compatibility issues with CUDA
7) Updated the README file to reflect the current state of the project
8) Improved performance and fixed various bugs

The documentation can be found at: http://docs.palaestr.ai/

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Release 3.1, 2021-05-03

Updated to a state where palaestrAI can be used as a tool in scientific publications. The experimentation process is now in a state that experiments are reproducible, testable, and trained agents can be stored/loaded.

1) Added possibility for the muscle to send different actions to environment and brain (breaking change: the muscle must now return two actuator lists).
2) Enabled environment episodes. Environment gets restarted after `done`. (breaking: the `start_environment` method now needs to do the initialization of environment variables, otherwise the restart may cause errors)
3) Added methods to store/load agents (breaking: existing brain/muscle implementations need the respective methods).
4) Added a test mode to test agents after training.
5) The muscle now receives the id of its respective brain (breaking: `brain_id` must be added to the muscle's `__init__()`).
6) The vanilla_sim_controller was moved from experiment folder to simulation (breaking: needs to be udpated in `experiment.yaml` files)
7) Added the tic-tac-toe environment as one of the standard environments. It is located in the palaestrai-environments repo: https://gitlab.com/arl2/palaestrai-environments
8) Improved performance and fixed various bugs

The documentation can now be found at: http://docs.palaestr.ai/

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