Adaptation to other initially unknown agents often requires computing an effective counter-strategy. In the Bayesian paradigm, one must find a good counterstrategy to the inferre...
Michael Johanson, Martin Zinkevich, Michael H. Bow...
Abstract. We consider the design of online master algorithms for combining the predictions from a set of experts where the absolute loss of the master is to be close to the absolut...
Jacob Abernethy, John Langford, Manfred K. Warmuth
Abstract. This paper presents one approach to acquire knowledge from multiple experts. The experts are grouped into multilevel hierarchical structure, according to the type of know...
In this paper, we examine on-line learning problems in which the target concept is allowed to change over time. In each trial a master algorithm receives predictions from a large ...
Active responses from experts play an essential role in the knowledge discovery of SAR (structure activity relationships) from drug data. Experts often think of hypotheses, and the...
Auctions have become an integral part of electronic commerce and a promising field for applying multi-agent technologies. Correctly judging the quality of auctioned items is ofte...
Abstract— In the resolution of group decision making problems the consensus process, that is, the process where experts discuss about the alternatives to narrow their differences...
Sergio Alonso, Enrique Herrera-Viedma, Francisco J...
We present a probabilistic formulation of UCS (a sUpervised Classifier System). UCS is shown to be a special case of mixture of experts where the experts are learned independentl...
Narayanan Unny Edakunni, Tim Kovacs, Gavin Brown, ...
Designing CSCW systems that support the widely varying needs of targeted users is difficult. There is no silver bullet technology that enables users to effectively collaborate wit...
Will Humphries, D. Scott McCrickard, Dennis C. Nea...