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» Solving Demodulation as an Optimization Problem
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GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
15 years 10 months ago
Transgenetic algorithm: a new evolutionary perspective for heuristics design
Transgenetic algorithms are evolutionary computing techniques based on living processes where cooperation is the main evolutionary strategy. Those processes contain the movement o...
Elizabeth Ferreira Gouvea Goldbarg, Marco Cé...
130
Voted
IROS
2006
IEEE
97views Robotics» more  IROS 2006»
15 years 10 months ago
Probabilistic Search for a Moving Target in an Indoor Environment
– We consider a search for a target moving within a known indoor environment partitioned into interconnected regions of varying sizes. The knowledge of target location is describ...
Haye Lau, Shoudong Huang, Gamini Dissanayake
ICML
1996
IEEE
15 years 8 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
ATAL
2006
Springer
15 years 8 months ago
Adaptive Pricing for Customers with Probabilistic Valuations
Abstract. In this paper, we examine the problem of choosing discriminatory prices for customers with probabilistic valuations and a seller with indistinguishable copies of a good. ...
Michael Benisch, James Andrews, Norman M. Sadeh
GECCO
2006
Springer
170views Optimization» more  GECCO 2006»
15 years 7 months ago
Combining simplex with niche-based evolutionary computation for job-shop scheduling
We propose a hybrid algorithm (called ALPINE) between Genetic Algorithm and Dantzig's Simplex method to approximate optimal solutions for the Flexible Job-Shop Problem. Local...
Syhlin Kuah, Joc Cing Tay