Dynamics of complex systems
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Complex Systems and Cognitive Processes
Complex Systems and Cognitive Processes
How the Body Shapes the Way We Think: A New View of Intelligence (Bradford Books)
How the Body Shapes the Way We Think: A New View of Intelligence (Bradford Books)
Evolution of discrete gene regulatory models
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Probabilistic Boolean Networks: The Modeling and Control of Gene Regulatory Networks
Probabilistic Boolean Networks: The Modeling and Control of Gene Regulatory Networks
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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Dynamical systems theory and complexity science provide powerful tools for analysing artificial agents and robots. Furthermore, they have been recently proposed also as a source of design principles and guidelines. Boolean networks are a prominent example of complex dynamical systems and they have been shown to effectively capture important phenomena in gene regulation. From an engineering perspective, these models are very compelling, because they can exhibit rich and complex behaviours, in spite of the compactness of their description. In this paper, we propose the use of Boolean networks for controlling robots' behaviour. The network is designed by means of an automatic procedure based on stochastic local search techniques. We show that this approach makes it possible to design a network which enables the robot to accomplish a task that requires the capability of navigating the space using a light stimulus, as well as the formation and use of an internal memory.