An important question in neuroevolution is how to gain an advantage from evolving neural network topologies along with weights. We present a method, NeuroEvolution of Augmenting Topologies (NEAT), which outperforms the best fixed-topology method on a challenging benchmark reinforcement learning

Are Americans more individualistic and less collectivistic than members of other groups? The authors summarize plausible psychological implications of individualism–collectivism (IND-COL), meta-analyze cross-national and within-United States IND-COL differences, and review evidence for effects of IND-COL on self-concept, well-being, cognition, and relationality. European Americans were found to be both more individualistic—valuing personal independence more—and less collectivistic—feeling duty to in-groups less—than others. However, European Americans were not more individualistic than African Americans, or Latinos, and not less collectivistic than Japanese or Koreans. Among Asians, only Chinese showed large effects, being both less individualistic and more collectivistic. Moderate IND-COL effects were found on self-concept and relationality, and large effects were found on attribution and cognitive style. To contemporary Americans, being an individualist is not only a good thing; it is a quintessentially American thing. However, the term individualism itself appears to have its roots outside of the North American continent, namely in the French Revolution. It appears that individualism was first used to describe the negative

for the modeling and simulation of genetic regulatory networks will be indispensable. This paper reviews formalisms that have been employed in mathematical biology and bioinformatics to describe genetic regulatory systems, in particular directed graphs, Bayesian networks, Boolean networks and their generalizations

In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a

improve TCP performance. In this paper (Part I of the report), we present the problem and an analysis of our simulation results. In Part II of this report, we present the simulation and results in detail.

A number of library-based parallel and sequential network simulators have been designed. This paper describes a library, called GloMoSim (for Global Mobile system Simulator), for parallel simulation of wireless networks. GloMoSim has been designed to be extensible and composable: the communication

of the topology and branch lengths, only a few iterations are sufficient to reach an optimum. We used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximum-likelihood programs and much higher than the performance

. GAF moderates this policy using application- and system-level information; nodes that source or sink data remain on and intermediate nodes monitor and balance energy use. GAF is independent of the underlying ad hoc routing protocol; we simulate GAF over unmodified AODV and DSR. Analysis and simulation

changing. Results from theoretical analysis, simulations, and experiments show that Chord is scalable, with communication cost and the state maintained by each node scaling logarithmically with the number of Chord nodes.

accuracy: increased sensitivity in Analysis of Variance (ANOVA) tests; a standard error that decreased as both AUC and the number of test samples increased; decision threshold independent; and it is invariant to a priori class probabilities. The paper concludes with the recommendation that AUC be used