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Form generation or morphogenesis is one of the main stages of both artificial and natural development. This paper provides results from experiments in which a genetic algorithm (GA) was used to evolve cellular automata (CA) to produce predefined 2D and 3D shapes. The GA worked by evolving the CA rule table and the number of iterations that the model was to(More)
Wilson introduced XCSF as a successor to XCS. The major development of XCSF is the concept of a computed prediction. The efficiency of XCSF in dealing with numerical input and continuous payoff has been demonstrated. However, the possible actions must always be determined in advance. Yet domains such as robot control require numerical actions, so that(More)
OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. Abstract—Metamorphic robots are robots that can change their shape by reorganizing the connectivity of their modules to adapt to new environments, perform new tasks, or recover from damages. In this paper we present a(More)
In this paper a virtual ecosystem environment with basic physical law and energy concept has been proposed, this ecosystem is populated with 3D virtual creatures that are living in this environment in order to forage food. Artificial behaviours are developed to control virtual creatures. A genetic algorithm with an artificial neural network were implemented(More)
Cell pattern generation has a fundamental role in both artificial and natural development. This paper presents results from a model in which a genetic algorithm (GA) was used to evolve an artificial regulatory network (ARN) to produce predefined 2D cell patterns through the selective activation and inhibition of genes. The ARN used in this work is an(More)
In order to produce diversity in virtual creatures to populate virtual worlds, different techniques exist. Some of these use blocks or sticks. In this morphological approach, blocks and sticks can be considered as organs, which means body parts able to perform different functions. Another approach, artificial embryogenesis, consists in developing organisms(More)
This paper explores temporal and spatial dynamics of a population of Genetic Regulatory Networks (GRN). In order to so, a GRN model is spatially distributed to solve a multi-cellular Artificial Embryogeny problem, and Evolutionary Computation is used to optimize the developmental sequences. An in-depth analysis is provided and show that such a population of(More)