- Added test_seeded_learning test and test_deterministic_evaluation test.
- Passed config values seed and deterministic to ppo agent
- Dropped deterministic override in evaluate functions
- TempPrimaiteSession now writes files to a UUID folder rather than datetime
- Added seed to Ray RLlib agent setup in rllib.py
- Added seed to SB3 agent setup in sb3.py
## Summary
* Brought over the RLlib, hardcoded agents, and simple agents from ADSP 1.1.0. This opened a can of worms... ADSP got their stuff working in notebooks (***_stares at data scientists!_** 😂) but hadn't integrated it into the PrimAITE package or made the other PrimAITE functionality work with it.
* RLlib agents have been fully integrated with the wider PrimAITE package. This was done by:
* The creation of an `AgentSessionABC` and `HardCodedAgentSessionABC` classes.
* `SB3Agent` and `RLlibAgent` classes then inherited from `AgentSessionABC`.
* The ADSP hardcoded agents were integrated into subclasses of `HardCodedAgentSessionABC`.
* The random and dummy agents were also integrated into subclasses of `HardCodedagentSessionABC`.
* A set of session output directories were created and managed by the agent session to enable consistent storage of session outputs in a common format regardless of the agent type.
* The main config was rafactored so that it had
* **agent_framework** - To identify whether SB3, RLlib, or Custom.
* **agent_identifier** - To identify whether PPO, A2C, hardcoded, random, or dummy.
* **deep_learning_framework** - To identify which framework to use for RLlib.
* Transactions have been overhauled to simplify the process. It also means that they're written in real time so they're not lost if the agent crashes.
* Tests completely overhauled to use `PrimaiteSession`, or at least a test subclass, `TempPrimaiteSession`. It's temp because it uses temp directory rather than main primaite session directory, and it cleans up after itself.
* All the crap removed from `main.py` and made it so that it just runs `PrimaiteSession`.
Now this is where I went off on a tangent...
* CLI added to just make my life and everyone else's life easier.
* Primaite app config added to hold things like logging format, levels etc.
* A `primaite.data_viz.session_plots` module added so that the average reward per episode for each session is plotted and saves for each session (this helped while we were testing and bug fixing).
## Test process
* All tests use `TempPrimaiteSession`, which uses `PrimaiteSession`.
* I still need to write a tests that runs the RLlib, hardcoded, and random/dummy agents. I'll do that now while this is being reviewed.
## Still to do
* Update docs. I'm getting this PR up now so we can get it in to make use of the features. I'll get the docs updated today either on this branch or another branch (depending on how long this review takes).
## Checklist
- [X] This PR is linked to a **work item**
- [X] I have performed **self-review** of the code
- [X] I have written **tests** for any new functionality added with this PR
- [ ] I have updated the **documentation** if this PR changes or adds functionality
- [X] I have run **pre-commit** checks for code style
Related work items: #917, #1563
## Summary
Just splits the install primaite step into two depending if agent is using windows or not.
## Test process
Ran a build successfully.
## Checklist
- [ ] This PR is linked to a **work item**
- [ ] I have performed **self-review** of the code
- [ ] I have written **tests** for any new functionality added with this PR
- [ ] I have updated the **documentation** if this PR changes or adds functionality
- [ ] I have run **pre-commit** checks for code style
