2 papers
cs.LG2019
Planning with Abstract Learned Models While Learning Transferable Subtasks
John Winder, Stephanie Milani, Matthew Landen +5
We introduce an algorithm for model-based hierarchical reinforcement learning to acquire self-contained transition and reward models suitable for probabilistic planning at multiple…
cs.AI2013
Representing and Reasoning With Probabilistic Knowledge: A Bayesian Approach
Marie desJardins
PAGODA (Probabilistic Autonomous Goal-Directed Agent) is a model for autonomous learning in probabilistic domains [desJardins, 1992] that incorporates innovative techniques for usi…