Advances in Complex Systems

Tartarus is a benchmark problem used to evaluate artificial intelligence techniques for solving problems in the field of non-Markovian agent motion planning. In this paper a fractal gene regulatory network with inputs is evolved to act as a virtual robot controller in the Tartarus environment. The proposed technique is compared and contrasted with other previously reported techniques and it is shown that the gene regulatory network that includes input information provides an excellent performance without using any explicit memory or environmental modeling. Detailed experimental studies are presented to illustrate the effectiveness and superiority of the proposed approach.

In the development of disciplines addressing dynamics, a major role was played by the assumption that processes can be modeled by introducing state properties, called potentialities, anticipating in which respect a next state will be different. A second assumption often made is that these state properties can be related to other state properties, called reducers. This paper proposes a philosophical framework in terms of potentialities and their reducers, which can be used to obtain a common philosophical foundation for methods in AI, cognitive science and beyond to model dynamics. Based on this framework a metamodel for dynamic modeling approaches is described. The philosophical framework and the metamodel together provide a unified foundation for numerical, symbolic, and hybrid dynamic modeling approaches used in a large variety of disciplines.

A spatial curdling index is presented for studying income concentration in two-dimensional fields originated by a cascade process, resembling resource allocation maps. Computational simulations of spatial distributions show that the relation between and measures of income inequality such as the Gini coefficient forms a concave area. Acknowledgment of this fact brings additional information for formulating geopolitical strategies for income inequality reduction, and for comparison purposes in a set of countries or across time within a country. With the aim of showing the importance of index , a prototype of the empirical application is shown based on the Peruvian and Swedish income maps.

Ethnic residential segregation is common in urban areas and is especially pronounced in metropolitan areas of the US. Many factors contribute to these residential patterns. The potential role of ethnic preferences has received increasing attention in recent years, but the development of theoretical models has been limited in many respects. This study seeks to extend the understanding of the possible role of ethnic preferences by investigating an agent-based model that introduces the concept of spatial potential — the desirability of particular spatial locations — as a competing preference. The distribution of spatial potential is varied from convex to concave distributions on the city landscape to investigate the resulting impact on patterns of segregation. Three types of zones are identified in the model city, namely the minority ghetto, the majority ring, and the integrated ring. The present model is considered to be an example of a discrete dynamic system that is characterized by its random move condition and its definition on the grid system. Insights from analytic approaches are explored in the context of the new dynamics to gain a better understanding of the emergent patterns of the system.

We study a complementarity game as a systematic tool for the investigation of the interplay between individual optimization and population effects and for the comparison of different strategy and learning schemes. The game randomly pairs players from opposite populations. It is symmetric at the individual level, but has many equilibria that are more or less favorable to the members of the two populations. Which of these equilibria is then attained is decided by the dynamics at the population level. Players play repeatedly, but in each round with a new opponent. They can learn from their previous encounters and translate this into their actions in the present round on the basis of strategic schemes. The schemes can be quite simple, or very elaborate. We can then break the symmetry in the game and give the members of the two populations access to different strategy spaces. Typically, simpler strategy types have an advantage because they tend to go more quickly toward a favorable equilibrium which, once reached, the other population is forced to accept. Also, populations with bolder individuals that may not fare so well at the level of individual performance may obtain an advantage toward ones with more timid players. By checking the effects of parameters such as the generation length or the mutation rate, we are able to compare the relative contributions of individual learning and evolutionary adaptations.

Minimum spanning trees and planar maximally filtered graphs are generated from correlations between the 300 most-capitalized NYSE stocks' daily returns, computed dynamically over moving windows of sizes between 1 and 12 months, in the period from 2001 to 2003. We study how different economic sectors differently populate the various regions of these graphs. We find that the financial sector is always at the center whereas the periphery is shared among different sectors. Four extremes are observed: stocks well-connected and central; stocks well-connected but at the same time peripheral; stocks poorly-connected but central; stocks poorly-connected and peripheral. Two principal components of centrality measures are individuated. The economic meaning of this hierarchical disposition is discussed.