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» Iterative Learning Control - Monotonicity and Optimization
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MIA
2010
170views more  MIA 2010»
14 years 4 months ago
Linear intensity-based image registration by Markov random fields and discrete optimization
We propose a framework for intensity-based registration of images by linear transformations, based on a discrete Markov Random Field (MRF) formulation. Here, the challenge arises ...
Darko Zikic, Ben Glocker, Oliver Kutter, Martin Gr...
EPIA
2007
Springer
15 years 4 months ago
Intelligent Farmer Agent for Multi-agent Ecological Simulations Optimization
Abstract. This paper presents the development of a bivalve farmer agent interacting with a realistic ecological simulation system. The purpose of the farmer agent is to determine t...
Filipe Cruz, António Pereira, Pedro Valente...
AAAI
2010
14 years 11 months ago
Towards Multiagent Meta-level Control
Embedded systems consisting of collaborating agents capable of interacting with their environment are becoming ubiquitous. It is crucial for these systems to be able to adapt to t...
Shanjun Cheng, Anita Raja, Victor R. Lesser
MP
2010
154views more  MP 2010»
14 years 8 months ago
A null-space primal-dual interior-point algorithm for nonlinear optimization with nice convergence properties
Abstract. We present a null-space primal-dual interior-point algorithm for solving nonlinear optimization problems with general inequality and equality constraints. The algorithm a...
Xinwei Liu, Yaxiang Yuan
GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
15 years 3 months ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen