In this paper, the advantages of introducing an additional amount of tests when evolving parameters for specific purposes is discussed. A set of optimal PID-controller parameters...
Divide-and-Evolve (DaE) is an original “memeticization” of Evolutionary Computation and Artificial Intelligence Planning. However, like any Evolutionary Algorithm, DaE has se...
The reality gap, that often makes controllers evolved in simulation inefficient once transferred onto the real system, remains a critical issue in Evolutionary Robotics (ER); it p...
This paper describes a study of the evolution of distributed behavior, specifically the control of agents in a mobile ad hoc network, using neuroevolution. In neuroevolution, a p...
David B. Knoester, Heather Goldsby, Philip K. McKi...
Genetic algorithms—a class of stochastic population-based optimization techniques—have been widely realized as the effective tools to solve complicated optimization problems ...