Completed
Without Hierarchy
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Classroom Contents
Developing Robots that Autonomously Learn and Plan in the Real World
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- 1 Current Challenges
- 2 Learning Agents
- 3 Markov Decision Process (MDP)
- 4 Policy Improvement
- 5 Deep Reinforcement Learning
- 6 Learning Through Interaction
- 7 Task Decomposition
- 8 Low-Level Controller (LLC)
- 9 LLC Reward
- 10 High-Level Controller (HLC)
- 11 Dynamic Obstacles
- 12 Without Hierarchy
- 13 Lifelong Learning
- 14 How to train a cleaning robot
- 15 Curriculum: Train grasping first
- 16 Curriculum: Train grasping while navigating
- 17 ReALMM: Insights
- 18 Intrinsic Rewards
- 19 SMIRL: Surprise minimization
- 20 Representation Learning for Complex Observations
- 21 Future Work: Goals
- 22 Future Work: Methods
