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GECCO
2011
Springer
276views Optimization» more  GECCO 2011»
13 years 20 days ago
Evolution of reward functions for reinforcement learning
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...
Scott Niekum, Lee Spector, Andrew G. Barto
CISIS
2008
IEEE
14 years 3 months ago
Hardware Software Partitioning Problem in Embedded System Design Using Particle Swarm Optimization Algorithm
Hardware/software partitioning is a crucial problem in embedded system design. In this paper, we provide an alternative approach to solve this problem using Particle Swarm Optimiz...
Alakananda Bhattacharya, Amit Konar, Swagatam Das,...
DATE
2007
IEEE
98views Hardware» more  DATE 2007»
14 years 3 months ago
Simulation-based reusable posynomial models for MOS transistor parameters
We present an algorithm to automatically design posynomial models for parameters of the MOS transistors using simulation data. These models improve the accuracy of the Geometric P...
Varun Aggarwal, Una-May O'Reilly
DAGSTUHL
2006
13 years 10 months ago
On Complexity of Optimized Crossover for Binary Representations
We consider the computational complexity of producing the best possible offspring in a crossover, given two solutions of the parents. The crossover operators are studied on the cla...
Anton V. Eremeev
GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
14 years 3 months ago
On the behavioral diversity of random programs
Generating a random sampling of program trees with specified function and terminal sets is the initial step of many program evolution systems. I present a theoretical and experim...
Moshe Looks