The L-CAPS system is a functional interface for learning group behavior using Cultural Algorithms in the land bridge simulation example. It enables the Cultural Algorithms process to implicitly communicate with, modify and evaluate, autonomous game agents restricted to an external virtual world. The L-CAPS system is described and used to learn the group behavior of caribou herds in the virtual ...

Reinforcement Learning algorithms such as SARSA with an eligibility trace, and Evolutionary Computation methods such as genetic algorithms, are competing approaches to solving Partially Observable Markov Decision Processes (POMDPs) which occur in many fields of Artificial Intelligence. A powerful form of evolutionary algorithm that has not previously been applied to POMDPs is the cultural algor...

In this paper, a parallel cultural algorithm for designing functional network structure method is proposed. This method can get the basis function and its parameters with random optimal searching strategy obtained the learning between functional network structure and the functional parameters. Finally, the simulation experiment results show that the proposed constructive functional network opti...

Evolutionary algorithms have been widely used to solve large and complex optimisation problems. Cultural algorithms (CAs) are evolutionary algorithms that have been used to solve both single and, to a less extent, multiobjective optimisation problems. In order to solve these optimisation problems, CAs make use of different strategies such as normative knowledge, historical knowledge, circumstan...

Abstract— The air traffic conflict resolution represents a real time problem. Thus, it must be interesting to apply methods which their computing time is negligible. In this study, we use cultural algorithms to solve an artificial conflict involving five aircrafts. These algorithms present the advantage to evolve 10 times faster than genetic algorithms. We assume that the trajectories of all ai...

In this paper, we present the first proposal to use a cultural algorithm to solve multiobjective optimization problems. Our proposal uses evolutionary programming, Pareto ranking and elitism (i.e., an external population). The approach proposed is validated using several examples taken from the specialized literature. Our results are compared with respect to the NSGA-II, which is an algorithm r...

In order to overcome prematurity of ant colony algorithm, the conception of belief space originated in cultural algorithm is introduced, and a new cultural ant algorithm is proposed for continuous optimization problems. Firstly, the coding scheme for ant colony algorithm to solve continuous optimization problems is discussed. Then belief space is brought in, and designed as the form of two part...