Multiagent learning can be seen as applying ML techniques to the core issues of multiagent systems, like communication, coordination, and competition. In this paper, we address the...
The paradigm of advisable planning, in which a user provides guidance to influence the content of solutions produced by an underlying planning system, holds much promise for impro...
We describe a new approach to default reasoning, based on a principle of indi erence among possible worlds. We interpret default rules as extreme statistical statements, thus obta...
Fahiem Bacchus, Adam J. Grove, Joseph Y. Halpern, ...
This paper introduces a model for Distributed Employee Timetabling Problems (DisETPs) and proposes a general architecture for solving DisETPs by using a Multi Agent System (MAS) pa...
A stochastic formulation of the Analytic Hierarchy Process (AHP) using an approach based on Bayesian categorical data models has been developed. However, in categorical data model...