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EPS
1998
Springer
14 years 25 days ago
Genetic Programming for Automatic Target Classification and Recognition
We use the genetic programming (GP) paradigm for two tasks. The first task given a GP is the generation of rules for the target / clutter classification of a set of synthetic apert...
Stephen A. Stanhope, Jason M. Daida
ROBOCOMM
2007
IEEE
14 years 2 months ago
Distributed control diffusion: towards a flexible programming paradigm for modular robots
—A self-reconfigurable robot is a robotic device that can change its own shape. Self-reconfigurable robots are commonly built from multiple identical modules that can manipulat...
Ulrik Pagh Schultz
GECCO
2005
Springer
183views Optimization» more  GECCO 2005»
14 years 2 months ago
802.11 network intrusion detection using genetic programming
Genetic Programming (GP) based Intrusion Detection Systems (IDS) use connection state network data during their training phase. These connection states are recorded as a set of fe...
Patrick LaRoche, A. Nur Zincir-Heywood
GECCO
2007
Springer
163views Optimization» more  GECCO 2007»
14 years 2 months ago
Exploring medical data using visual spaces with genetic programming and implicit functional mappings
Two medical data sets (Breast cancer and Colon cancer) are investigated within a visual data mining paradigm through the unsupervised construction of virtual reality spaces using ...
Julio J. Valdés, Robert Orchard, Alan J. Ba...
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
14 years 7 days ago
Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state GP
In contrast with the diverse array of genetic algorithms, the Genetic Programming (GP) paradigm is usually applied in a relatively uniform manner. Heuristics have developed over t...
L. Darrell Whitley, Marc D. Richards, J. Ross Beve...