Base classes for Off Policy Agents

[Sharad24]

This should make the code much more comprehensible, especially with the number of arguments we have. And at the same time resolve a lot of maintainability issues.

[sampreet-arthi]

There's also a lot of code duplication issues that show up pylint. Maybe work on that too.

[Sharad24]

Yup, that's the goal. Another thing to do would be properly decide the parameters to be kept/removed in agents and added/removed from the trainers.

[sampreet-arthi]

Since we already have the On Policy Agents, I'm renaming this to Off Policy. I'll raise a PR for this soon.

[sampreet-arthi]

I'm thinking of refactoring each of the individual off policy algorithms first so that the code is neater, more uniform and shorter.

[sampreet-arthi]

To-do:

• Refactor DDPG
• Refactor TD3
• Refactor SAC
• Finalise BaseAgent and Base OffPolicyAgent classes
• Refactor Trainer and OffPolicyTrainer (Trainer classes are also really long, would be a good idea to first shorten them then maybe we can separate them into multiple files if they're still too big)
• Add CUDA support for all of them
• Add support for Prioritized Experience Replay for all Off Policy algos

[Sharad24]

Tracking in separate issues now. #263, #162 and #264