A key goal in machine learning and artificial intelligence is to automatically and dynamically decompose problems into simpler problems in order to facilitate their solution. This paper describes two extensions to genetic programming, called "automatic" function definition and "hierarchical automatic" function definition, wherein functions that might be… (More)
This paper describes six new architecture-altering operations that provide a way to dynamically determine the architecture of a multi-part program during a run of genetic programming. The new operations are patterned after the naturally occurring operations of gene duplication and gene deletion and are motivated by Ohno's provocative book Evolution by Means… (More)
– The design (synthesis) of analog electrical circuits starts with a high-level statement of the circuit's desired behavior and requires creating a circuit that satisfies the specified design goals. Analog circuit synthesis entails the creation of both the topology and the sizing (numerical values) of all of the circuit's components. The difficulty of the… (More)
This paper describes the application of the recently developed "genetic programming" paradigm to the problem of concept formation and decision tree induction.
Genetic programming has now been used to produce at least 76 instances of results that are competitive with human-produced results. These human-competitive results come from a wide variety of fields, including quantum model discovery. This paper observes that, despite considerable variation in the techniques employed by the various researchers and research… (More)