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ATAL
2004
Springer
15 years 10 months ago
Resource Allocation in the Grid Using Reinforcement Learning
One of the main challenges in Grid computing is efficient allocation of resources (CPU-hours, network bandwidth, etc.) to the tasks submitted by users. Due to the lack of centrali...
Aram Galstyan, Karl Czajkowski, Kristina Lerman
CHI
2007
ACM
16 years 4 months ago
Vio: a mixed-initiative approach to learning and automating procedural update tasks
Today many workers spend too much of their time translating their co-workers' requests into structures that information systems can understand. This paper presents the novel ...
John Zimmerman, Anthony Tomasic, Isaac Simmons, Ia...
ICCBR
2005
Springer
15 years 10 months ago
Advertising Strategies: Learning Competence through Cooperative Game Playing
In this paper we consider the competition on the Internet between information providers to maximise their exposure to a relevant audience. Spammers and Search engine gamers adopt a...
Paolo Avesani, Conor Hayes
AAAI
2006
15 years 5 months ago
On the Difficulty of Modular Reinforcement Learning for Real-World Partial Programming
In recent years there has been a great deal of interest in "modular reinforcement learning" (MRL). Typically, problems are decomposed into concurrent subgoals, allowing ...
Sooraj Bhat, Charles Lee Isbell Jr., Michael Matea...
GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
15 years 5 months ago
Multi-agent task allocation: learning when to say no
This paper presents a communication-less multi-agent task allocation procedure that allows agents to use past experience to make non-greedy decisions about task assignments. Exper...
Adam Campbell, Annie S. Wu, Randall Shumaker