Summary of The Intrinsic Motivation Of Reinforcement and Imitation Learning For Sequential Tasks, by Sao Mai Nguyen
The intrinsic motivation of reinforcement and imitation learning for sequential tasks
by Sao Mai Nguyen
First submitted to arxiv on: 29 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Human-Computer Interaction (cs.HC); Machine Learning (cs.LG); Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a new approach to domain bridging between reinforcement learning and imitation learning, aiming to develop a model that motivates learning agents to learn multiple tasks, including sequential ones. The main contribution is the formulation of intrinsic motivation based on empirical progress, allowing agents to actively choose their learning strategy for simple or sequential tasks. This learner benefits from both passive tutoring and active requests for demonstrations, making it more robust to tutoring quality and faster-learning with fewer demonstrations. The framework combines machine learning algorithms with socially guided intrinsic motivation, leveraging generalisability properties of human demonstrations. The proposed reward function enables automatic curriculum learning in multi-task learning within the reinforcement learning framework. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about developing a new way for robots to learn from humans. It’s like when you’re trying to learn something new and you want someone to guide you, but you also want to learn it on your own. The researchers came up with a model that lets robots choose what they want to learn and how they want to learn it. This makes the learning process faster and more efficient. The goal is to create robots that can learn many things from humans and use that knowledge to help us in our daily lives. |
Keywords
» Artificial intelligence » Curriculum learning » Machine learning » Multi task » Reinforcement learning
