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At least 559 records · Page 31Linked to original sources
arXiv2000

Self-organized Networks of Competing Boolean Agents

A model of Boolean agents competing in a market is presented where each agent bases his action on information obtained from a small group of other agents. The agents play a competitive game that rewards those in the minority. After a long time interval, the poorest player's strategy is changed randomly, and the process is repeated. Eventually the network evolves to a stationary but intermittent state where random mutation of the worst strategy can change the behavior of the entire network, often causing a switch in the dynamics between attractors of vastly different lengths.

cond-mat.stat-mech↗
arXiv1999

Enhancement of Stochastic Resonance in distributed systems due to a selective coupling

Recent massive numerical simulations have shown that the response of a "stochastic resonator" is enhanced as a consequence of spatial coupling. Similar results have been analytically obtained in a reaction-diffusion model, using "nonequilibrium potential" techniques. We now consider a field-dependent diffusivity and show that the "selectivity" of the coupling is more efficient for achieving stochastic-resonance enhancement than its overall value in the constant-diffusivity case.

cond-mat.stat-mech↗
arXiv1993

Dynamics of Earthquake Faults

We present an overview of our ongoing studies of the rich dynamical behavior of the uniform, deterministic Burridge--Knopoff model of an earthquake fault. We discuss the behavior of the model in the context of current questions in seismology. Some of the topics considered include: (1) basic properties of the model, such as the magnitude vs. frequency distribution and the distinction between small and large events; (2) dynamics of individual events, including dynamical selection of rupture propagation speeds; (3) generalizations of the model to more realistic, higher dimensional models; (4) studies of predictability, in which artificial catalogs generated by the model are used to test and determine the limitations of pattern recognition algorithms used in seismology.

adap-org↗
arXiv2012

Stable Adaptive Control Using New Critic Designs

Classical adaptive control proves total-system stability for control of linear plants, but only for plants meeting very restrictive assumptions. Approximate Dynamic Programming (ADP) has the potential, in principle, to ensure stability without such tight restrictions. It also offers nonlinear and neural extensions for optimal control, with empirically supported links to what is seen in the brain. However, the relevant ADP methods in use today -- TD, HDP, DHP, GDHP -- and the Galerkin-based versions of these all have serious limitations when used here as parallel distributed real-time learning systems; either they do not possess quadratic unconditional stability (to be defined) or they lead to incorrect results in the stochastic case. (ADAC or Q-learning designs do not help.) After explaining these conclusions, this paper describes new ADP designs which overcome these limitations. It also addresses the Generalized Moving Target problem, a common family of static optimization problems, and describes a way to stabilize large-scale economic equilibrium models, such as the old long-term energy model of DOE.

adap-org↗
arXiv1996

Why Do Proteins Look Like Proteins?

Protein structures in nature often exhibit a high degree of regularity (secondary structures, tertiary symmetries, etc.) absent in random compact conformations. We demonstrate in a simple lattice model of protein folding that structural regularities are related to high designability and evolutionary stability. We measure the designability of each compact structure by the number of sequences which can design the structure, i.e., which possess the structure as their nondegenerate ground state. We find that compact structures are drastically different in terms of their designability; highly designable structures emerge with a number of associated sequences much larger than the average. These structures are found to have ``protein like'' secondary structure and even tertiary symmetries. In addition, they are also thermodynamically more stable than ordinary structures. These results suggest that protein structures are selected because they are easy to design and stable against mutations, and that such a selection simutaneously leads to thermodynamic stability.

cond-mat↗
arXiv1999

Emergence of scaling in random networks

Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites. A model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.

cond-mat.dis-nn↗
arXiv1994

Asymptotic Exit Location Distributions in the Stochastic Exit Problem

Consider a two-dimensional continuous-time dynamical system, with an attracting fixed point $S$. If the deterministic dynamics are perturbed by white noise (random perturbations) of strength $ε$, the system state will eventually leave the domain of attraction $Ω$ of $S$. We analyse the case when, as $ε\to0$, the exit location on the boundary $\partialΩ$ is increasingly concentrated near a saddle point $H$ of the deterministic dynamics. We show that the asymptotic form of the exit location distribution on $\partialΩ$ is generically non-Gaussian and asymmetric, and classify the possible limiting distributions. A key role is played by a parameter $μ$, equal to the ratio $|λ_s(H)|/λ_u(H)$ of the stable and unstable eigenvalues of the linearized deterministic flow at $H$. If $μ<1$ then the exit location distribution is generically asymptotic as $ε\to0$ to a Weibull distribution with shape parameter $2/μ$, on the $O(ε^{μ/2})$ length scale near $H$. If $μ>1$ it is generically asymptotic to a distribution on the $O(ε^{1/2})$ length scale, whose moments we compute. The asymmetry of the asymptotic exit location distribution is attributable to the generic presence of a `classically forbidden' region: a wedge-shaped subset of $Ω$ with $H$ as vertex, which is reached from $S$, in the $ε\to0$ limit, only via `bent' (non-smooth) fluctuational paths that first pass through the vicinity of $H$. We deduce from the presence of this forbidden region that the classical Eyring formula for the small-$ε$ exponential asymptotics of the mean first exit time is generically inapplicable.

adap-org↗
arXiv1999

Correlated random walks with a finite memory range

We study a family of correlated one-dimensional random walks with a finite memory range M.These walks are extensions of the Taylor's walk as investigated by Goldstein, which has a memory range equal to one. At each step, with a probability p, the random walker moves either to the right or to the left with equal probabilities, or with a probability q=1-p performs a move, which is a stochastic Boolean function of the M previous steps. We first derive the most general form of this stochastic Boolean function, and study some typical cases which ensure that the average value of the walker's location after n steps is zero for all values of n. In each case, using a matrix technique, we provide a general method for constructing the generating function of the probability distribution of R_n; we also establish directly an exact analytic expression for the step-step correlations and the variance of the walk. From the expression of , which is not straightforward to derive from the probability distribution, we show that, for n going to infinity, the variance of any of these walks behaves as n, provided p>0. Moreover, in many cases, for a very small fixed value of p, the variance exhibits a crossover phenomenon as $n$ increases from a not too large value. The crossover takes place for values of $n$ around 1/p. This feature may mimic the existence of a non-trivial Hurst exponent, and induce a misleading analysis of numerical data issued from mathematical or natural sciences experiments.

adap-org↗
arXiv1993

Life-Times of Simulated Traffic Jams

We study a model for freeway traffic which includes strong noise taking into account the fluctuations of individual driving behavior. The model shows emergent traffic jams with a self-similar appearance near the throughput maximum of the traffic. The lifetime distribution of these jams shows a short scaling regime, which gets considerably longer if one reduces the fluctuations for driving at maximum speed but leaves the fluctuations for slowing down or accelerating unchanged. The outflow from a traffic jam self-organizes into this state of maximum throughput.

cond-mat↗
arXiv1996

Power Laws are Logarithmic Boltzmann Laws

Multiplicative random processes in (not necessaryly equilibrium or steady state) stochastic systems with many degrees of freedom lead to Boltzmann distributions when the dynamics is expressed in terms of the logarithm of the normalized elementary variables. In terms of the original variables this gives a power-law distribution. This mechanism implies certain relations between the constraints of the system, the power of the distribution and the dispersion law of the fluctuations. These predictions are validated by Monte Carlo simulations and experimental data. We speculate that stochastic multiplicative dynamics might be the natural origin for the emergence of criticality and scale hierarchies without fine-tuning.

adap-org↗
arXiv1996

Spontaneous Scaling Emergence in Generic Stochastic Systems

We extend a generic class of systems which have previously been shown to spontaneously develop scaling (power law) distributions of their elementary degrees of freedom. While the previous systems were linear and exploded exponentially for certain parameter ranges, the new systems fulfill nonlinear time evolution equations similar to the ones encountered in Spontaneous Symmetry Breaking (SSB) dynamics and evolve spontaneously towards "fixed trajectories" indexed by the average value of their degrees of freedom (which corresponds to the SSB order parameter). The "fixed trajectories" dynamics evolves on the edge between explosion and collapse/extinction. The systems present power laws with exponents which in a wide range ($α< -2.$) are universally determined by the ratio between the minimal and the average values of the degrees of freedom. The time fluctuations are governed by Levy distributions of corresponding power. For exponents $α> -2$ there is no "thermodynamic limit" and the fluctuations are dominated by a few, largest degrees of freedom which leads to macroscopic fluctuations, chaos and bursts/intermitency.

adap-org↗
arXiv1997

Individual Adaption in a Path-Based Simulation of the Freeway Network of Northrhine-Westfalia

Traffic simulations are made more realistic by giving individual drivers intentions, i.e. an idea of where they want to go. One possible implementation of this idea is to give each driver an exact pre-computed path, that is, a sequence of roads this driver wants to follow. This paper shows, in a realistic road network, how repeated simulations can be used so that drivers can explore different paths, and how macroscopic quantities such as locations of jams or network throughput change as a result of this.

adap-org↗
arXiv1997

Experiences with a simplified microsimulation for the Dallas/Fort Worth area

We describe a simple framework for micro simulation of city traffic. A medium sized excerpt of Dallas was used to examine different levels of simulation fidelity of a cellular automaton method for the traffic flow simulation and a simple intersection model. We point out problems arising with the granular structure of the underlying rules of motion.

adap-org↗
arXiv1997

Using microsimulation feedback for trip adaptation for realistic traffic in Dallas

This paper presents a day-to-day re-routing relaxation approach for traffic simulations. Starting from an initial planset for the routes, the route-based microsimulation is executed. The result of the microsimulation is fed into a re-router, which re-routes a certain percentage of all trips. This approach makes the traffic patterns in the microsimulation much more reasonable. Further, it is shown that the method described in this paper can lead to strong oscillations in the solutions.

adap-org↗
arXiv1997

Generalized Deterministic Traffic Rules

We study a family of deterministic models for highway traffic flow which generalize cellular automaton rule 184. This family is parametrized by the speed limit $m$ and another parameter $k$ that represents a ``degree of aggressiveness'' in driving, strictly related to the distance between two consecutive cars. We compare two driving strategies with identical maximum throughput: ``conservative'' driving with high speed limit and ``aggressive'' driving with low speed limit. Those two strategies are evaluated in terms of accident probability. We also discuss fundamental diagrams of generalized traffic rules and examine limitations of maximum achievable throughput. Possible modifications of the model are considered.

adap-org↗
arXiv1998

One Dimensional $n$ary Density Classification Using Two Cellular Automaton Rules

Suppose each site on a one-dimensional chain with periodic boundary condition may take on any one of the states $0,1,..., n-1$, can you find out the most frequently occurring state using cellular automaton? Here, we prove that while the above density classification task cannot be resolved by a single cellular automaton, this task can be performed efficiently by applying two cellular automaton rules in succession.

adap-org↗
arXiv1999

Lattice three-species models of the spatial spread of rabies among foxes

Lattice models describing the spatial spread of rabies among foxes are studied. In these models, the fox population is divided into three-species: susceptible, infected or incubating, and infectious or rabid. They are based on the fact that susceptible and incubating foxes are territorial while rabid foxes have lost their sense of direction and move erratically. Two different models are investigated: a one-dimensional coupled-map lattice model, and a two-dimensional automata network model. Both models take into account the short-range character of the infection process and the diffusive motion of rabid foxes. Numerical simulations show how the spatial distribution of rabies, and the speed of propagation of the epizootic front depend upon the carrying capacity of the environment and diffusion of rabid foxes out of their territory.

adap-org↗