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I built an OpenAI Gym Environment on top of `sapai` that can be used for reinforcement learning. I thought I would link it here since most people here are probably interested in building ML/AI for Sup…
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Hello everyone,
I would like to inquire about the change from the gym module to Gymnasium in the pybullet drone environment for reinforcement learning. The OpenAI gym environment has been discontin…
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### Feature Description
Given the capacities of Aerostack2, it would be very suitable to implement a reinforcement learning API with different environments by default to apply RL to control problem…
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# 1.3 Elements of Reinforcement Learning
- *Policy*
- A policy defines the learning agent’s way of behaving at a given time.
- Roughly speaking, a policy is a mapping from perceived states of…
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소스 : reinforcement-learning-kr/1-grid-world/1-policy-iteration/environment.py
12:POSSIBLE_ACTIONS = [0, 1, 2, 3] # 상, 하, 좌, 우
위 주석에서 [상,하,좌,우] -> [좌,우,상,하] 로 되어야 할듯 합니다~
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- [ ] [Q-learning - Wikipedia](https://en.wikipedia.org/wiki/Q-learning)
# Q-learning - Wikipedia
**Description:** Q-learning is a model-free reinforcement learning algorithm to learn the value of …
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How can I quickly implement your policy in a new scenario?
I am looking to apply your policy in a new scenario, but I noticed that your code loads a pre-trained reinforcement learning model. How can …
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Implement the best practices from multi-agent Rl community and stablebaselines3 into our algorithm. Further analyse similarities between petting zoo multi-agent implementation to current RL implementa…
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Hi,
Thanks for the wonderful work! I have a question regarding the hyperparameters in the paper. Are the default hyperparameters stored in config.locomotion the same as those used in Figures 2, 5,…
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- [ ] Definir colisiones que debe de haber entre jugadores y pelota.
- [ ] Crear un Env para el aprendizaje por medio de self-play.