This paper steps back from the standard infinite horizon formulation of reinforcement learning problems to consider the simpler case of finite horizon problems. Although finite ho...
We present a concept to use off-line learning approaches to achieve on-line learning of cooperative behavior of agents and instantiate this concept for evolutionary learning with ...
A critical challenge to creating effective open multi-agent systems is allowing them to operate effectively in the face of potential failures. In this paper we present an experimen...
Online auctions are becoming an increasingly important channel for electronic commerce. There exist more than 150 online auction sites on the Internet. It is difficult for users t...
Our goal is to build knowledge acquisition tools that support users in modifying knowledge-based systems. These modi cations may require several individual changes to various comp...
The use of heuristics as a means to improve constraint solver performance has been researched widely. However, most work has been on problem-independentheuristics (e.g., variable ...
Lise Getoor, Greger Ottosson, Markus P. J. Fromher...
We show that a resealed constrainedness parameter provides the basis for accurate numerical models of search cost for both backtracking and local search algorithms. In the past, t...
Ian P. Gent, Ewan MacIntyre, Patrick Prosser, Toby...