This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...
POIROT is an integration framework for combining machine learning mechanisms to learn hierarchical models of web services procedures from a single or very small set of demonstrati...
Mark H. Burstein, Robert Laddaga, David McDonald, ...
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). ...
In this paper, we consider the problem of assisting a busy user in managing her workload of pending tasks. We assume that our user is typically oversubscribed, and is invariably j...
The current evaluation functions for heuristic planning are expensive to compute. In numerous domains these functions give good guidance on the solution, so it worths the computat...