1. Evolving Virtual Creatures B2.2 Vincent Visser | Complexity through simplicity

2. Environment Body Brain References: Sims, K., 1994. “Evolving Virtual Creatures”, Thinking Machines Corporation. Lessin, D.G., 2015. “Evolved Virtual Creatures as Content: Increasing Behavioral and Morphological Complexity”, University of Texas at Austin Evolving Virtual Creatures SensorsNeuronsEffectors Genotype Phenotyp e

3. A population of genotypes are individually expressed to produce a phenotype, which can then be evaluated by a fitness function. This produces a fitness value for each genotype, which determines the survival and reproduction of genotypes to produce the next generation. As the cycle is repeated, fitness in the population tends to improve. B2.2 Vincent Visser | Complexity through simplicity Emergence Evolutionary Algorithm Algorithm: 1.Initialization (P(0); i = 1); 2.Evaluate fitness of each individual in P(0); 3.Repeat Generation (Variation, Evaluation, Selection) Characteristics: Flexible Robust Adaptive Autonomous Decentralized

4. Values by Sims: Population Sizes: 300 Survival-ratio: 1/5 B2.2 Vincent Visser | Complexity through simplicity Emergence Evolutionary Algorithm

5. Transfer Example B2.2 Vincent Visser | Complexity through simplicity Multiple Applications Evolutionary Algorithm (Planning, Design, Simulation, Identification, Control, Classification) Infinite Monkey Theorem Travelling Salesman Problem