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» Adaptive learning in evolving task allocation networks
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NPL
2000
105views more  NPL 2000»
13 years 7 months ago
Online Interactive Neuro-evolution
In standard neuro-evolution, a population of networks is evolved in a task, and the network that best solves the task is found. This network is then fixed and used to solve future...
Adrian K. Agogino, Kenneth O. Stanley, Risto Miikk...
ATAL
2007
Springer
14 years 1 months ago
Dynamic task allocation within an open service-oriented MAS architecture
A MAS architecture consisting of service centers is proposed. Within each service center, a mediator coordinates service delivery by allocating individual tasks to corresponding t...
Ivan Jureta, Stéphane Faulkner, Youssef Ach...
ICES
2003
Springer
125views Hardware» more  ICES 2003»
14 years 17 days ago
Evolving Reinforcement Learning-Like Abilities for Robots
Abstract. In [8] Yamauchi and Beer explored the abilities of continuous time recurrent neural networks (CTRNNs) to display reinforcementlearning like abilities. The investigated ta...
Jesper Blynel
DATE
2008
IEEE
100views Hardware» more  DATE 2008»
14 years 1 months ago
User-Aware Dynamic Task Allocation in Networks-on-Chip
In this paper, we propose a run-time strategy for allocating the application tasks to platform resources in homogeneous Networks-on-Chip (NoCs). As novel contribution, we incorpor...
Chen-Ling Chou, Radu Marculescu
EVOW
2003
Springer
14 years 18 days ago
Exploring the T-Maze: Evolving Learning-Like Robot Behaviors Using CTRNNs
Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...
Jesper Blynel, Dario Floreano