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» Learning to Optimize Plan Execution in Information Agents
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AAAI
2011
12 years 8 months ago
Combining Learned Discrete and Continuous Action Models
Action modeling is an important skill for agents that must perform tasks in novel domains. Previous work on action modeling has focused on learning STRIPS operators in discrete, r...
Joseph Z. Xu, John E. Laird
GECCO
2007
Springer
214views Optimization» more  GECCO 2007»
14 years 2 months ago
Portfolio allocation using XCS experts in technical analysis, market conditions and options market
Schulenburg [15] first proposed the idea to model different trader types by supplying different input information sets to a group of homogenous LCS agent. Gershoff [12] investigat...
Sor Ying (Byron) Wong, Sonia Schulenburg
ATAL
2009
Springer
14 years 3 months ago
From DPS to MAS to ...: continuing the trends
The most important and interesting of the computing challenges we are facing are those that involve the problems and opportunities afforded by massive decentralization and disinte...
Michael N. Huhns
ICDE
2012
IEEE
304views Database» more  ICDE 2012»
11 years 11 months ago
Learning-based Query Performance Modeling and Prediction
— Accurate query performance prediction (QPP) is central to effective resource management, query optimization and query scheduling. Analytical cost models, used in current genera...
Mert Akdere, Ugur Çetintemel, Matteo Rionda...
ATAL
2010
Springer
13 years 9 months ago
Heuristic search for identical payoff Bayesian games
Bayesian games can be used to model single-shot decision problems in which agents only possess incomplete information about other agents, and hence are important for multiagent co...
Frans A. Oliehoek, Matthijs T. J. Spaan, Jilles St...