Choosing between heuristics and strategies: an enhanced model for decision-making

Authors:
Shavit Talman;Rotem Toister;Sarit Kraus
Affiliations:
Department of Computer Science, Bar-Ilan University, Ramat-Gan, Israel;Department of Computer Science, Bar-Ilan University, Ramat-Gan, Israel;Department of Computer Science, Bar-Ilan University, Ramat-Gan, Israel
Venue:
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Year:
2005

Citing 5
Cited 3

A Value-Driven System for Autonomous Information Gathering

Journal of Intelligent Information Systems
Acquiring an Optimal Amount of Information for Choosing from Alternatives

CIA '02 Proceedings of the 6th International Workshop on Cooperative Information Agents VI
Time Sensitive Sequential Myopic Information Gathering

HICSS '99 Proceedings of the Thirty-second Annual Hawaii International Conference on System Sciences-Volume 6 - Volume 6
The Influence of Social Dependencies on Decision-Making: Initial Investigations with a New Game

AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Adapting to agents' personalities in negotiation

Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems

A statistical decision-making model for choosing among multiple alternatives

Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Efficiently determining the appropriate mix of personal interaction and reputation information in partner choice

Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Efficiently gathering information in costly domains

Decision Support Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Often an agent that has to solve a problem must choose which heuristic or strategy will help it the most in achieving its objectives. Sometimes the agent wishes to obtain additional units of information on the possible heuristics and strategies in order to choose between them, but it may be costly. As a result, the agent's goal is to acquire enough units of information in order to make a decision while incurring minimal cost. We focus on situations where the agent must decide in advance how many units it would like to obtain. We present an algorithm for choosing between two options, and then formulate three methods for the general case where there are k 2 options to choose from. We investigate the 2-option algorithm and the general k-option methods effectiveness in two domains: the 3-SAT domain, and the CT computer game. In both domains we present the experimental performance of our models. Results will show that applying the 2-option algorithm is beneficial and provides the agent a substantial gain. In addition, applying the k-option method in the domains investigated results in a moderate gain.