Reinforcement learning (RL) problems constitute an important class of learning and control problems faced by artificial intelligence systems. In these problems, one is faced with ...
Instance (or object) classification in a knowledgebase managementsystem is the very same problem as view determination in an object DBMS,whereviewsare subsets of classes intension...
Ana Simonet, Michel Simonet, Cyr Gabin Bassolet, X...
The increasing number of knowledge-based systems that build on a Bayesian belief network or influence diagram acknowledge the usefulness of these frameworks for addressing complex...
Weaddress the problemof generalizing temporal data concerning durations extracted from relational databases.Ourapproachisbasedona domaingenerMizationgraphthatdefinesa partialorder...
Dee Jay Randall, Howard J. Hamilton, Robert J. Hil...
The goal of the research being reported is the discovery of useful concepts in temporal medical databases. In this paper, we present a sequence building approach, based on the Gen...
Jorge C. G. Ramirez, Lynn L. Peterson, Dolores M. ...
Our focus is on designing adaptable agents for highly dynamic environments. Wehave implementeda reinforcement learning architecture as the reactive componentof a twolayer control ...
Manual generation of training examples for supervised learning is an expensive process. One way to reduce this cost is to produce training instances that are highly informative. T...
Justus H. Piater, Edward M. Riseman, Paul E. Utgof...
This work studies the control of robots in the adversarial world of "Hunt the Wumpus". The hybrid learning algorithm which controls the robots behavior is a combination ...