Search

One of the most important issues that must be taken in mind to optimize the design and the generalization abilities of trained artificial neural networks (ANN) is the architecture of the net. In this paper Symbiotic_RBF is proposed, a method to do automatically the process to design models for classification using symbiosis. For it, there are two populations who evolve together by means of coevolution. One of the populations is the method EvRBF, which provides the design of radial basis function neural nets by means of evolutionary algorithms. The second population evolves sets of parameters for the method EvRBF, being every individual of the population a configuration of parameters for the method. Thus, the main goal of Symbiotic_RBF is to find a suitable configuration of parameters necessary for the method EvRBF, which is adapted automatically to every problem. [ABSTRACT FROM AUTHOR]

The service economy calls for a new, interdisciplinary methodology for defining and valuing information technology services outsourcing needs. Parameters such as ill-informed provider selection and poor contract management have hitherto dominated the IT consulting literature, yet have offered inadequate explanations to the high failure rates in global outsourcing arrangements. This paper takes a different approach in examining the causes of the problem; we discuss the knowledge and power asymmetries that appear to prevent both parties from realizing potential benefits in the market. The concept of self-knowledge as opposed to relationship management is suggested. We posit that knowledge/power asymmetries can be better comprehended when the two parties are considered as interacting entities that influence each other in a dynamic way. Under this spectrum, we discuss the value of a client-focused maturity assessment in realizing potential outsourcing benefits. [ABSTRACT FROM AUTHOR]

Adapting to changing situations and objectives and selforganazing without a central controller in order to achieve an objective has become one of the main challenges in the design and operation of multirobot systems. The Asynchronous Situated Coevolution (ASiCO) algorithm has been successfully applied in surveillance tasks defined by just one global objective. In this paper we present the results obtained with ASiCO in more complex multirobot problems with several objectives that require a heterogeneous population of robot controllers that autonomously distribute the tasks. The paper focuses on the benefits of evolving an affinity coefficient that characterizes the individual genotypes. [ABSTRACT FROM AUTHOR]

One of the main challenges in the operation of multirobot systems is to find ways for them to adapt to changing situations and even objectives without any type of central control. In this work we propose a real time coevolutionary strategy based on Embodied Evolution (EE) approaches that provides a means to achieve this end. The main inspiration for this approach comes from the field of artificial life combined with some of the notions on the distribution of utility functions as proposed by the multiagent systems literature. The solution has been tested on different real life problems involving robot teams. In particular, in this paper the work is aimed at the coordination of sets of robots for performing monitoring and surveillance operations such as the ones required on ship tanks and hulls. Nevertheless, the approach is general enough to be applied to many other tasks in several fields. [ABSTRACT FROM AUTHOR]

This chapter introduces individual evolution as a strategy for problem solving. This strategy proposes to partition the original problem into a set of homogeneous elements, whose individual contribution to the problem solution can be evaluated separately. A population comprised of these homogeneous elements is evolved with the goal of creating a single solution by a process of aggregation. The goal of individual evolution is to locally build better individuals that jointly form better global solutions. The implementation of the proposed approach requires addressing aspects such as problem decomposition and representation, local and global fitness integration, as well as diversity preservation mechanisms. The benefit of applying the individual evolution approach for problem solving is a substantial reduction in computational effort expended in the evolutionary optimization process. This chapter shows an example from vision metrology where experimental results coincide with previous state of the art photogrammetric network design methodologies, while incurring in only a fraction of the computational cost. [ABSTRACT FROM AUTHOR]

Chapter 4 of the book "Nature: An Economic History," by Geerat J. Vermeij, is presented. It focuses on two economic activities, consumption and production, and the role of enemies in nature. It discusses defense methods of potential victims from predators, how predators, whose energy-demanding performance exceeds that of the potential prey, exercise greater control over the characteristics of living things such as behavior, form and distribution, and the reciprocal adaptation or coevolution.