Suggestion Strategies for Constraint-Based Matchmaker Agents

In this paper we describe a paradigm for contentfocused matchmaking, based on a recently proposed model for constraint acquisition-and-satisfaction. Matchmaking agents are conceived as constraintbased solvers that interact with other, possibly human, agents (Clients or Customers). The Matchmaker provides potential solutions (\suggestions") based on partial knowledge, while gaining further information about the problem itself from the other agent through the latter's evaluation of these suggestions. The dialog between Matchmaker and Customer results in iterative improvement of solution quality, as demonstrated in simple simulations. We also show empirically that this paradigm supports \suggestion strategies" for nding acceptable solutions more e ciently or for increasing the amount of information obtained from the Customer. This work also indicates some ways in which the tradeo between these two metrics for evaluating performance can be handled.

• Type: Conference
• Year: 1998
• Where: CP
• Authors: Eugene C. Freuder, Richard J. Wallace
• Keywords: Artificial Intelligence, Constraintbased Solvers, Contentfocused Matchmaking, CP 1998, Solutions