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by Rina Azoulay-schwartz, Sarit Kraus
In Proceedings of the 6th International Workshop on Cooperative Information Agents VI
http://www.umiacs.umd.edu/~sarit/./Articles/cia02azoulaykraus.ps
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Abstract:
Abstract. An agent operating in the real world must often choose from among alternatives in incomplete information environments, and frequently it can obtain additional information about them. Obtaining information can result in a better decision, but the agent may incur expenses for obtaining each unit of information. The problem of finding an optimal strategy for obtaining information appears in many domains. For example, in ecommerce when choosing a seller, and in solving programming problems when choosing heuristics. We focus on cases where the agent has to decide in advance on how much information to obtain about each alternative. In addition, each unit of information about an alternative gives the agent only partial information about the alternative, and the range of each information unit is continues. We first formalize the problem of deciding how many information units to obtain about each alternative, and we specify the expected utility function of the agent, given a combination of information units. This function should be maximized by choosing the optimal number of information units. We proceed by suggesting methods for finding the optimal allocation of information units between the different alternatives. 1
Citations
|
295
|
Planning and control
– Dean, Wellman
- 1991
|
|
287
|
Artificial Intelligence: A Modern Approach, Second Edition
– Russel, Norvig
- 2003
|
|
111
|
Bandit Problems: Sequential Allocation of Experiments
– Berry, Fristedt
- 1985
|
|
79
|
Information value theory
– Howard
- 1966
|
|
75
|
Multi-armed bandit allocation indices
– Gittins
- 1989
|
|
32
|
An approximate nonmyopic computation for value of information
– Heckerman, Horvitz, et al.
- 1993
|
|
21
|
Probability and Statistics for Engineers
– Miller, Freund
- 1987
|
|
20
|
The Nature of Competition in Electronic Markets: An Empirical Investigation of Online Travel Agent Offerings.” Working Paper, The Wharton School of the
– Clemons, Hann, et al.
- 1998
|
|
15
|
Big: An agent for resource-bounded information gathering and decision making
– Lesser, Horling, et al.
- 2000
|
|
13
|
Handbook of The Normal Distribution
– Patel, Read
- 1996
|
|
11
|
ªA Value-Driven System for Autonomous Information Gathering,º
– Grass, Zilberstein
- 2000
|
|
8
|
The choice of sample size
– Lindley
- 1997
|
|
4
|
Sample Size Determination in Clinical Trials
– Pezeshk, Gittins
- 1999
|
|
3
|
Sophisticated information gathering in a marketplace of information providers
– Lesser, Horling, et al.
- 2000
|
|
3
|
Reasoning about the value of decision model refinement: Methods and application
– Poh, Horvitz
- 1993
|
|
3
|
Time sensitive sequential myopic information gathering
– Tseng, Gmytrasiewicz
- 1999
|
|
2
|
On selecting the largest of k normal population means
– Dunnett
- 1960
|
|
1
|
Interval-based versus decision theoretic criteria for the choice of sample size
– Joseph, Wolfson
- 1997
|
