Difference between revisions of "Reinforcement Learning"
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== Reinforcement Learning (RL) == | == Reinforcement Learning (RL) == | ||
| − | Reinforcement Learning (RL) is a machine learning approach where an agent learns to perform tasks by interacting with an environment. It involves the agent receiving rewards or penalties based on its actions | + | Reinforcement Learning (RL) is a machine learning approach where an agent learns to perform tasks by interacting with an environment. It involves the agent receiving rewards or penalties based on its actions and using this feedback to improve its performance over time. RL is particularly useful in robotics for training robots to perform complex tasks autonomously. Here's how RL is applied in robotics, using simulation environments like Isaac Sim and MuJoCo: |
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Revision as of 19:56, 16 May 2024
Reinforcement Learning (RL)
Reinforcement Learning (RL) is a machine learning approach where an agent learns to perform tasks by interacting with an environment. It involves the agent receiving rewards or penalties based on its actions and using this feedback to improve its performance over time. RL is particularly useful in robotics for training robots to perform complex tasks autonomously. Here's how RL is applied in robotics, using simulation environments like Isaac Sim and MuJoCo:
Training algorithms
