Embedded systems are often used in a safety-critical context, e.g. in airborne or vehicle systems. Typically, timing constraints must be satisfied so that real-time embedded syste...
In this paper we demonstrate that pressure for robustness combined with function sets containing redundant genes can cause an evolutionary system to avoid a more fit solution in f...
The AI optimization algorithm called "Squeaky-Wheel Optimization" (SWO) has proven very effective in a variety of real-world applications. Although the ideas behind SWO ...
In this paper, it is presented a new way to characterize the phenotype in the context of Genetic Algorithms through the use of Game Theory as a theoretical foundation to define a ...
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
In this paper, we propose the island model parallel memetic algorithm with diversity-based dynamic adaptive strategy (PMADLS) for controlling the local search frequency and demons...
We use probabilistic boolean networks to simulate the pathogenesis of Dengue Hemorraghic Fever (DHF). Based on Chaturvedi's work, the strength of cytokine influences are mode...
This paper compares the performance of the program evaluation phase of genetic programming using C and Common Lisp. A simple experiment is conducted, and the conclusion is that ge...
Particle Swarm Optimization (PSO) is a population-based optimization method in which search points employ a cooperative strategy to move toward one another. In this paper we show ...
Andrew M. Sutton, Darrell Whitley, Monte Lunacek, ...
Memetic algorithms are evolutionary algorithms incorporating local search to increase exploitation. This hybridization has been fruitful in countless applications. However, theory...