Recent Developments in Biologically Inspired Computing

Section II: Evolutionary Algorithms

Chapter List

Chapter II: Evolutionary Turing Machines: The Quest for Busy Beavers
Chapter III: Generalized Extremal Optimization: A New Meta-Heuristic Inspired by a Model of Natural Evolution
Chapter IV: Genetic Programming Using a Turing-Complete Representation: Recurrent Network Consisting of Trees
Chapter V: Gene Expression Programming and the Evolution of Computer Programs
Chapter VI: The Clonal Selection Principle for In Silico and In Vitro Computing

Overview

Penousal Machado, ISEC, Portugal

Francisco B. Pereira, ISEC, Portugal

Jorge Tavares, CISUC, Portugal

Ernesto Costa, CISUC, Portugal

Am lcar Cardoso, CISUC, Portugal

Abstract

In this chapter we study the feasibility of using Turing Machines as a model for the evolution of computer programs. To assess this idea we select, as test problem, the Busy Beaver a well-known theoretical problem of undisputed interest and difficulty proposed by Tibor Rado in 1962. We focus our research on representational issues and on the development of specific genetic operators, proposing alternative ways of encoding and manipulating Turing Machines. The results attained on a comprehensive set of experiments show that the proposed techniques bring significant performance improvements. Moreover, the use of a graph based crossover operator, in conjunction with new representation techniques, allowed us to establish new best candidates for the 6, 7, and 8 states instances of the 4-tuple Busy Beaver problem.

Introduction

In 1937 Alan Turing, while trying to solve one of the problems posed by Hilbert, developed a theoretical computational model that became known as Turing Machines (Turing, 1937). According to the Church-Turing thesis, these finite state...

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