This paper studies Genetic Programming (GP) and its relation to the Genetic Algorithm (GA). GP uses a GA approach to breed successive populations of programs, represented in the ch...
We provide an overview of using genetic programming (GP) to model stock returns. Our models employ GP terminals (model decision variables) that are financial factors identified by...
An agent population can be evolved in a complex environment to perform various tasks and optimize its job performance using Learning Classifier System (LCS) technology. Due to the...
For fading broadcast channels (BC), a throughput optimal scheduling policy called queue proportional scheduling (QPS) is presented via geometric programming (GP). QPS finds a data ...
Evaluating GP schema in context is considered to be a complex, and, at times impossible, task. The tightly linked nodes of a GP tree is the main reason behind its complexity. This...