Difference between revisions of "Apprenticeship Learning - Inverse Reinforcement Learning (IRL)"
(→Imitation Learning) |
|||
| Line 1: | Line 1: | ||
[http://www.youtube.com/results?search_query=Inverse+Reinforcement+Machine+Learning+Apprenticeship YouTube search...] | [http://www.youtube.com/results?search_query=Inverse+Reinforcement+Machine+Learning+Apprenticeship YouTube search...] | ||
| + | * [[Imitation Learning]] | ||
* [[Reinforcement Learning]] | * [[Reinforcement Learning]] | ||
* [[Inside Out - Curious Optimistic Reasoning]] | * [[Inside Out - Curious Optimistic Reasoning]] | ||
| Line 18: | Line 19: | ||
<youtube>xNvNeg7JGSM</youtube> | <youtube>xNvNeg7JGSM</youtube> | ||
<youtube>fu7uBNWTzU8</youtube> | <youtube>fu7uBNWTzU8</youtube> | ||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
Revision as of 10:10, 29 October 2018
- Imitation Learning
- Reinforcement Learning
- Inside Out - Curious Optimistic Reasoning
- Generative Adversarial Network (GAN)
- A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress | Saurabh Arora, Prashant Doshi 18 Jun 2018
- Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications | Daniel S. Brown, Scott Niekum 23 Jun 2018
Inverse reinforcement learning (IRL) infers/derives a reward function from observed behavior/demonstrations, allowing for policy improvement and generalization. While ordinary "reinforcement learning" involves using rewards and punishments to learn behavior, in IRL the direction is reversed, and a robot observes a person's behavior to figure out what goal that behavior seems to be trying to achieve.
