Evolutionary Robots with on-line self-organization and behavioral fitness
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Evolutionary algorithms are widespread heuristic methods inspired by natural evolution to solve difficult problems for which analytical approaches are not suitable. In many domains experimenters are not only interested in discovering optimal solutions, but ...
Evolutionary robotics has been shown to be an effective technique for generating robot behaviors that are difficult to derive analytically from the robot’s mechanics and task environment. Moreover, augmenting evolutionary algorithms with environmental scaf ...
We introduce, analyze, and experimentally verify the concept of co-solvability, meant as the ability of a solution maintained by an evolutionary run to solve (correctly process) a pair of fitness cases (tests). The method based on this concept can be consi ...
The number of vehicles hitting the road each day is rapidly increasing, and several problems, such as traffic conges- tion or driver safety, can no longer be solved in the same fashion as before. Intelligent transportation systems could potentially solve p ...
Communication is fundamental to life on earth. All social organisms, from bacteria to humans, use communicative signals to coordinate their behaviors with members of their own and other species. Despite its key role in social organization, many questions r ...
It is generally challenging to design decentralized controllers for swarms of robots because there is often no obvious relation between the individual robot behaviors and the final behavior of the swarm. As a solution, we use artificial evolution to automa ...
We propose a crossover operator that works with genetic programming trees and is approximately geometric crossover in the semantic space. By defining semantic as program's evaluation profile with respect to a set of fitness cases and constraining to a spec ...
Evolutionary robotics–the use of evolutionary algorithms to automate the production of autonomous robots–has been an active area of research for two decades. However, previous work in this domain has been limited by the simplicity of the evolved robots and ...
Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using unsupervised learning techniques which allow robots to evolve their own controllers online in an automated fashion. In mult ...
Evolutionary robotics is a promising approach to overcoming the limitations and biases of human designers in producing control strategies for autonomous robots. However, most work in evolutionary robotics remains solely concerned with optimizing control st ...
