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GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
14 years 27 days ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone
ICMI
2010
Springer
141views Biometrics» more  ICMI 2010»
13 years 7 months ago
Learning and evaluating response prediction models using parallel listener consensus
Traditionally listener response prediction models are learned from pre-recorded dyadic interactions. Because of individual differences in behavior, these recordings do not capture...
Iwan de Kok, Derya Ozkan, Dirk Heylen, Louis-Phili...
GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
13 years 10 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
ATAL
2006
Springer
14 years 1 months ago
Learning the task allocation game
The distributed task allocation problem occurs in domains like web services, the grid, and other distributed systems. In this problem, the system consists of servers and mediators...
Sherief Abdallah, Victor R. Lesser
ACAL
2007
Springer
13 years 11 months ago
Modelling Architectural Visual Experience Using Non-linear Dimensionality Reduction
This paper addresses the topic of how architectural visual experience can be represented and utilised by a software system. The long-term aim is to equip an artificial agent with ...
Stephan K. Chalup, Riley Clement, Chris Tucker, Mi...