Automatically assigned DDC number:

Manually assigned DDC number: 00633

Title: ___________________________

Author:

Author:

Subject: Helen G. Cobb,John J. Grefenstette ___________________________

Description: This paper explores the effect of explicitly searching for the persistence of each decision in a time-dependent sequential decision task. In prior studies, Grefenstette, et al, show the effectiveness of SAMUEL, a genetic algorithm-based system, in solving a simulation problem where an agent learns how to evade a predator that is in pursuit. In their work, an agent applies a control action at each time step. This paper examines a reformulation of the problem: the agent learns not only the level of response of a control action, but also how long to apply that control action. By examining this problem, the work shows that it is appropriate to choose a representation of the state space that compresses time information when solving a time-dependent sequential decision problem. By compressing time information, critical events in the decision sequence become apparent. 1 INTRODUCTION The problem of learning to perform a decision task presents us with several learning objectives. One objectiv...

Contributor: The Pennsylvania State University CiteSeer Archives

Publisher: unknown

Date: 1992-04-08

Pubyear: 1991

Format: ps

Identifier: http://citeseer.ist.psu.edu/140064.html

Source: http://www.aic.nrl.navy.mil/papers/1991/AIC-91-002.ps.Z

Language: en

Rights: unrestricted