Timezone: »
We introduce CST, an algorithm for constructing skill trees from demonstration trajectories in continuous reinforcement learning domains. CST uses a changepoint detection method to segment each trajectory into a skill chain by detecting a change of appropriate abstraction, or that a segment is too complex to model as a single skill. The skill chains from each trajectory are then merged to form a skill tree. We demonstrate that CST constructs an appropriate skill tree that can be further refined through learning in a challenging continuous domain, and that it can be used to segment demonstration trajectories on a mobile manipulator into chains of skills where each skill is assigned an appropriate abstraction.
Author Information
George Konidaris (Brown University)
Scott R Kuindersma (University of Massachusetts Amherst)
Andrew G Barto (University of Massachusetts)
Roderic A Grupen (UMass Amherst)
More from the Same Authors
-
2021 : Bayesian Exploration for Lifelong Reinforcement Learning »
Haotian Fu · Shangqun Yu · Michael Littman · George Konidaris -
2021 Poster: Learning Markov State Abstractions for Deep Reinforcement Learning »
Cameron Allen · Neev Parikh · Omer Gottesman · George Konidaris -
2017 Workshop: Hierarchical Reinforcement Learning »
Andrew G Barto · Doina Precup · Shie Mannor · Tom Schaul · Roy Fox · Carlos Florensa -
2011 Poster: TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning »
George Konidaris · Scott Niekum · Philip Thomas -
2011 Poster: Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery »
Scott Niekum · Andrew G Barto -
2009 Poster: Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining »
George Konidaris · Andrew G Barto -
2009 Spotlight: Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining »
George Konidaris · Andrew G Barto -
2008 Poster: Skill Characterization Based on Betweenness »
Özgür Şimşek · Andrew G Barto -
2007 Workshop: Hierarchical Organization of Behavior: Computational, Psychological and Neural Perspectives (Part 2) »
Yael Niv · Matthew Botvinick · Andrew G Barto -
2007 Workshop: Hierarchical Organization of Behavior: Computational, Psychological and Neural Perspectives (Part 1) »
Yael Niv · Matthew Botvinick · Andrew G Barto