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When I have a code like this:
class PongRamEnvironment(Environment):
def __init__(self):
self.base_env=Environment.create(
environment='gym', level='Pong-ram-v4',max_episode…
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In line 276 of CCM_MADDPG.py, I wonder why " newactor_action_var = self.actors[agent_id](states_var[:, agent_id, :]" instead of "newactor_action_var = self.actors[agent_id](next_states_var[:, agent_id…
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Mobile Reconfigurable Intelligent Surfaces for NOMA Networks: Federated Learning Approaches. (arXiv:2105.09462v1 [cs.NI])
https://ift.tt/3oxru0U
A novel framework of reconfigurable intelligent surface…
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**Learning**
- We learn by interacting with our environment.
- In any learning scenario for e.g. driving a car, we are acutely aware of how our environment responds to what we do, and we seek to inf…
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Hi @adysonmaia,
I'm currently working on a problem that has variable observation and action sizes at every timestep depending on the action and observation from the previous timestep. For instance, s…
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## 🚀 Feature
Support parallelized/asynchronous execution of ops on CPU.
PyTorch currently supports [asynchronous execution on GPU](https://pytorch.org/docs/master/notes/cuda.html#asynchronous-e…
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## Prequest
![image](https://user-images.githubusercontent.com/1320252/123796714-fdc5b580-d917-11eb-9371-3e852a8a8051.png)
- https://deepmind.com/learning-resources/-introduction-reinforcement-l…
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# Trending repositories for C#
1. [**Unity-Technologies / ml-agents**](https://github.com/Unity-Technologies/ml-agents)
__The Unity Machine Learning Agents Toolkit (ML-Agents) is …
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This issue proposes a pyro.contrib.agents module for building agent-based models and using control to guide their actions to maximize rewards.
This modeling task is commonly described as model-bas…
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This issue is for us to document how we will use reinforcement learning to train our rl-agent to avoid obstacles. The goal of this issue is:
- Learn more about the reward function
- Help decide wh…