Sylvain Cussat-Blanc

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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)
We show in this article 1 how the Weighted CSP framework can be used to solve an optimisation version of numerical planning. The WCSP finds an optimal plan in the planning graph containing all solution plans of minimum length. Experimental trials were performed to study the impact of soft arc consistency techniques (FDAC and EDAC) on the efficiency of the(More)
Over the past two decades, many techniques have been elaborated to simulate artificial, robotic creatures at different scales. After behavioral models in the 1990s, researchers made the robot morphologies evolvable to be better adapted to their environment. More recently, developmental mechanisms of living beings have inspired " artificial embryogeny " and(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)
—Artificial Gene Regulatory Networks (GRN) usually simulate cell behavior in developmental models. However, since 2003, GRN based controllers have been applied to robots to solve problems with few sensors and actuators. In this paper, we present our first steps toward an effective GRN-based controller for intelligent agents in video games. We will also(More)
Optimizing a wind farm layout is a very complex problem that involves many local and global constraints such as inter-turbine wind interference or terrain peculiarities. Existing methods are either inefficient or, when efficient, take days or weeks to execute. Solutions are contextually sensitive to the specific values of the problem variables; when one(More)
This paper presents a new method to generate the body plans of modular robots. In this work, we use a developmental model where cells are controlled by a gene regulatory network. Instead of using morphogens as in many existing works, we evolve a more flexible "hormonal system" that controls the inputs of the regulatory network. By evolving the regulatory(More)
This paper proposes a new method to evaluate the complexity of a Gene Regulatory Network (GRN). It is based on the generation of pictures. In addition to being visually interesting , the pictures shows the capacity of the GRN to produce smooth and/or sudden transitions, fractal-like complexity and regularities. We also have studied the influence of the size(More)
— An important connection between evolution and learning was made over a century ago and is now termed as the Baldwin effect. Learning acts as a guide for an evolutionary search process. In this study reinforcement learning agents are trained to solve the robot coverage control problem. These agents are improved by evolving neuromodulatory gene regulatory(More)