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» Function Optimization with Coevolutionary Algorithms
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121
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ICML
2009
IEEE
16 years 3 months ago
Predictive representations for policy gradient in POMDPs
We consider the problem of estimating the policy gradient in Partially Observable Markov Decision Processes (POMDPs) with a special class of policies that are based on Predictive ...
Abdeslam Boularias, Brahim Chaib-draa
GECCO
2007
Springer
149views Optimization» more  GECCO 2007»
15 years 8 months ago
Informative performance metrics for dynamic optimisation problems
Existing metrics for dynamic optimisation are designed primarily to rate an algorithm’s overall performance. These metrics show whether one algorithm is better than another, but...
Stefan Bird, Xiaodong Li
115
Voted
ISLPED
2005
ACM
111views Hardware» more  ISLPED 2005»
15 years 8 months ago
Peak temperature control and leakage reduction during binding in high level synthesis
Temperature is becoming a first rate design criterion in ASICs due to its negative impact on leakage power, reliability, performance, and packaging cost. Incorporating awareness o...
Rajarshi Mukherjee, Seda Ogrenci Memik, Gokhan Mem...
TWC
2010
14 years 9 months ago
Distributed Node Selection for Sequential Estimation over Noisy Communication Channels
This paper proposes a framework for distributed sequential parameter estimation in wireless sensor networks. In the proposed scheme, the estimator is updated sequentially at the c...
Thakshila Wimalajeewa, Sudharman K. Jayaweera
NIPS
1998
15 years 3 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