Lamarckian evolution, the Baldwin effect and function optimization -- Control of parallel population dynamics by social-like behavior of GA-individuals -- Studying genotype-phenotype interactions: A model of the evolution of the cell regulation network -- A diploid genetic algorithm for preserving population diversity - Pseudo-Meiosis GA -- Co-evolutionary constraint satisfaction -- Towards a theory of 'evolution strategies': Results for (1 , + ?)-strategies on (nearly) arbitrary fitness functions -- Advanced correlation analysis of operators for the traveling salesman problem -- Genetic algorithms with multi-parent recombination -- On the mean convergence time of evolutionary algorithms without selection and mutation -- Estimating the heritability by decomposing the genetic variance -- Analyzing hyperplane synthesis in genetic algorithms using clustered schemata -- Convergence models of genetic algorithm selection schemes -- Optimal population size under constant computation cost -- An evolutionary algorithm for integer programming -- Long path problems -- Evolution strategies on noisy functions how to improve convergence properties -- Selection schemes with spatial isolation for genetic optimization -- A modified edge recombination operator for the Travelling Salesman Problem -- Step-size adaptation based on non-local use of selection information -- Strategy adaptation by competing subpopulations -- Controlling crossover through inductive learning -- Derivative operators for preference predicate evolution -- Adaptive crossover using automata -- Controlling dynamics of GA through filtered evaluation function -- A cooperative coevolutionary approach to function optimization -- A fuzzy classifier system using the Pittsburgh approach -- Q-learning in Evolutionary Rule Based Systems -- On the complexity of learning in classifier systems -- A representation scheme to perform program induction in a canonical genetic algorithm -- Genetic Programming with local hill-climbing -- Dynamic training subset selection for supervised learning in Genetic Programming -- Genotype-phenotype-mapping and neutral variation - A case study in Genetic Programming -- Genetic L-System Programming -- A genetic algorithm discovers particle-based computation in cellular automata -- Simulation of exaptive behaviour -- Artificial spacing patterns in a network of interacting celloids -- Diffuse pattern learning with Fuzzy ARTMAP and PASS -- Different learning algorithms for Neural Networks - A comparative study -- Program search with a hierarchical variable length representation: Genetic Programming, simulated annealing and hill climbing -- Problem-independent Parallel Simulated Annealing using selection and migration -- Parallel optimization of evolutionary algorithms -- Parallel simulated annealing and genetic algorithms: A space of hybrid methods -- ENZO-M - A hybrid approach for optimizing neural networks by evolution and learning -- Genetic lander: An experiment in accurate neuro-genetic control -- Effects of Occam's razor in evolving Sigma-Pi neural nets -- Designing neural networks by adaptively building blocks in cascades -- Hybrid adaptive heuristic critic architectures for learning in mazes with continuous search spaces -- Mutation operators for structure evolution of neural networks -- Implementation of standard genetic algorithm on MIMD machines -- Loosely coupled distributed genetic algorithms -- Applying Evolvable Hardware to autonomous agents -- Genetic Algorithms on LAN-message passing architectures using PVM: Application to the Routing problem -- Genetic algorithm based design optimization of CMOS VLSI circuits -- Improving evolutionary timetabling with delta evaluation and directed mutation -- Genetic improvement of railway timetables -- Using a genetic algorithm to search for the representational bias of a collective reinforcement learner -- An evolutionary algorithm for the routing of multi-chip modules -- System design under uncertainty: Evolutionary optimization of the Gravity Probe-B spacecraft -- Soft selection in D-optimal designs -- The weighted graph bi-partitioning problem: A look at GA performance -- RPL2: A language and parallel framework for evolutionary computing.