Abstract:
A gene expression programming genetic algorithm for performing symbolic regression is provided. The algorithm avoids expression bloating and over fitting by employing a fitness function that depends inversely on the mathematical expression complexity. Members of a population that are evolved by the algorithm are represented as a set arrays (e.g., in the form of a matrix) of indexes that reference operands and operators, thus facilitating selection, mutation, and cross over operations conducted in the course of evolving the population. The algorithm comprises a syntax checking part that may be applied to population members without their having to be converted to executable programs first. An object-oriented programming language data structure is providing for encapsulating basic data for each codon (e.g., operand, operator) used by the algorithm.
Abstract:
A method (100) of electronically determining a group preference in a social network from multiple individual preferences of members of the social network is provided. One embodiment of the method (100) uses a combination of an individual's importance to a social network and a social network's importance to the individual as weighting factors when combining the individual preferences to generate a shared set of preferences. This group preference may be used to select content for broadcast to the network, including audio content and video content. A social network group preference determination apparatus (401) can determine the individual's importance to the social network by interrogating or monitoring the communication activity of portable electronic communication devices (402) belonging to the members of the social network.
Abstract:
A gene expression programming genetic algorithm for performing symbolic regression is provided. The algorithm avoids expression bloating and over fitting by employing a fitness function that depends inversely on the mathematical expression complexity. Members of a population that are evolved by the algorithm are represented as a set arrays of indexed that reference operands and operators, thus facilitating selection, mutation, and cross over operations conducted in the course of evolving the population. The algorithm comprises a syntax checking part [108, 110, 112] that may be applied to population members without their having to be converted to executable programs first. An object-oriented programming language data structure is providing for encapsulating basic data for each condon used by the algorithm.