Hierarchical reinforcement learning has been proposed as a solution to the problem of scaling up reinforcement learning. The RLTOPs Hierarchical Reinforcement Learning System is an...
In this paper the notion of a partial-order plan is extended to task-hierarchies. We introduce the concept of a partial-order taskhierarchy that decomposes a problem using multi-ta...
Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
This paper describes Icarus, an agent architecture that embeds a hierarchical reinforcement learning algorithm within a language for specifying agent behavior. An Icarus program e...
We describe an application of inductive logic programming to transfer learning. Transfer learning is the use of knowledge learned in a source task to improve learning in a related ...
Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richa...