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107
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NIPS
1998
15 years 2 months ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch
GECCO
2008
Springer
107views Optimization» more  GECCO 2008»
15 years 1 months ago
The influence of scaling and assortativity on takeover times in scale-free topologies
In evolving systems, the topological characteristics of population structure have a pronounced impact on the rate of spread of advantageous alleles, and therefore affect selective...
Joshua L. Payne, Margaret J. Eppstein
105
Voted
GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
15 years 1 months ago
Managing team-based problem solving with symbiotic bid-based genetic programming
Bid-based Genetic Programming (GP) provides an elegant mechanism for facilitating cooperative problem decomposition without an a priori specification of the number of team member...
Peter Lichodzijewski, Malcolm I. Heywood
DAC
2010
ACM
15 years 29 days ago
A correlation-based design space exploration methodology for multi-processor systems-on-chip
Given the increasing complexity of multi-processor systems-onchip, a wide range of parameters must be tuned to find the best trade-offs in terms of the selected system figures of ...
Giovanni Mariani, Aleksandar Brankovic, Gianluca P...
109
Voted
ICASSP
2010
IEEE
15 years 29 days ago
Distributed learning in cognitive radio networks: Multi-armed bandit with distributed multiple players
—We consider a cognitive radio network with distributed multiple secondary users, where each user independently searches for spectrum opportunities in multiple channels without e...
Keqin Liu, Qing Zhao