Recent contributions to advancing planning from the classical model to more realistic problems include using temporal logic such as LTL to express desired properties of a solution ...
There are two major approaches to activity coordination in multiagent systems. First, by endowing the agents with the capability to jointly plan, that is, to jointly generate hypot...
Eligibility traces have been shown to speed reinforcement learning, to make it more robust to hidden states, and to provide a link between Monte Carlo and temporal-difference meth...
Doina Precup, Richard S. Sutton, Satinder P. Singh
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
A central problem in multistrategy learning systems is the selection and sequencing of machine learning algorithms for particular situations. This is typically done by the system ...