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» Solving iterated functions using genetic programming
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131
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CEC
2008
IEEE
15 years 10 months ago
Policy evolution with Genetic Programming: A comparison of three approaches
— In the early days a policy was a set of simple rules with a clear intuitive motivation that could be formalised to good effect. However the world is now much more complex. Subt...
Yow Tzu Lim, Pau-Chen Cheng, John Andrew Clark, Pa...
TEC
2002
133views more  TEC 2002»
15 years 3 months ago
Learning and optimization using the clonal selection principle
The clonal selection principle is used to explain the basic features of an adaptive immune response to an antigenic stimulus. It establishes the idea that only those cells that rec...
Leandro Nunes de Castro, Fernando J. Von Zuben
EH
1999
IEEE
351views Hardware» more  EH 1999»
15 years 7 months ago
Evolvable Hardware or Learning Hardware? Induction of State Machines from Temporal Logic Constraints
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
107
Voted
EUROGP
2001
Springer
15 years 8 months ago
Polymorphism and Genetic Programming
Abstract. Types have been introduced to Genetic Programming (GP) by researchers with different motivation. We present the concept of types in GP and introduce a typed GP system, Po...
Tina Yu
118
Voted
FECS
2006
159views Education» more  FECS 2006»
15 years 4 months ago
Evolving Mathematical Functions with Genetic Algorithms - A Team Project on Artificial Intelligence
- In contrast to most of the senior level Artificial Intelligence (AI) courses where AI is taught in the jargon of theoretical computer science with crowd of complex matrix algebra...
Zhiguang Xu, Chris Neasbitt, Jared Summers, Bill C...