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added gif; updated docs
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Stefan Schneider committed Jun 24, 2020
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2 changes: 1 addition & 1 deletion README.md
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Using deep RL for mobility management.

![example](docs/gifs/v03.gif)
![example](docs/gifs/v04.gif)

The latest version uses the [RLlib](https://docs.ray.io/en/latest/rllib.html) library for multi-agent RL.
There is also an older version using [stable_baselines](https://stable-baselines.readthedocs.io/en/master/) for single-agent RL
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11 changes: 11 additions & 0 deletions docs/mdp.md
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# MDP Formulation

## [v0.4](https://github.com/CN-UPB/deep-rl-mobility-management/releases/tag/v0.4): Replaced stable_baselines with ray's RLlib (week 26)

* Replaced the RL framework: [RLlib](https://docs.ray.io/en/latest/rllib.html) instead of [stable_baselines](https://stable-baselines.readthedocs.io/en/master/)
* Benefit: RLlib is more powerful and supports multi-agent environments
* Refactored most parts of the existing code base to adjust to the new frameworks API
* Radio model and MDP remained unchanged

Example: Centralized PPO agent controlling two UEs after 20k training with RLlib

![v0.4 example](gifs/v04.gif)

## [v0.3](https://github.com/CN-UPB/deep-rl-mobility-management/releases/tag/v0.3): Centralized, single-agent, multi-UE-BS selection, basic radio model (week 25)

* Simple but improved radio load model:
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4 changes: 2 additions & 2 deletions drl_mobile/main.py
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Expand Up @@ -85,6 +85,6 @@ def create_env_config(env, eps_length, train_batch_size=1000, seed=None):
else:
sim.load_agent(path=agent_path, seed=seed)
# simulate one run
sim.run(render='video', log_steps=True)
sim.run(render='gif', log_steps=True)
# evaluate
sim.run(num_episodes=10, log_steps=False)
# sim.run(num_episodes=10, log_steps=False)

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