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» Adapting SME Learning Environments for Adaptivity
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ECSA
2010
Springer
15 years 2 days ago
Learning from the Cell Life-Cycle: A Self-adaptive Paradigm
In the software domain, self-adaptive systems are able to modify their behavior at run-time to respond to changes in the environment they run, to changes of the users' require...
Antinisca Di Marco, Francesco Gallo, Paola Inverar...
FLAIRS
1998
15 years 1 months ago
Learning to Race: Experiments with a Simulated Race Car
Our focus is on designing adaptable agents for highly dynamic environments. Wehave implementeda reinforcement learning architecture as the reactive componentof a twolayer control ...
Larry D. Pyeatt, Adele E. Howe
GECCO
2009
Springer
15 years 4 months ago
Novelty of behaviour as a basis for the neuro-evolution of operant reward learning
An agent that deviates from a usual or previous course of action can be said to display novel or varying behaviour. Novelty of behaviour can be seen as the result of real or appar...
Andrea Soltoggio, Ben Jones
AAAI
2007
15 years 2 months ago
RETALIATE: Learning Winning Policies in First-Person Shooter Games
In this paper we present RETALIATE, an online reinforcement learning algorithm for developing winning policies in team firstperson shooter games. RETALIATE has three crucial chara...
Megan Smith, Stephen Lee-Urban, Hector Muño...
NN
2002
Springer
113views Neural Networks» more  NN 2002»
14 years 11 months ago
Control of exploitation-exploration meta-parameter in reinforcement learning
In reinforcement learning (RL), the duality between exploitation and exploration has long been an important issue. This paper presents a new method that controls the balance betwe...
Shin Ishii, Wako Yoshida, Junichiro Yoshimoto