Adaptation Noise And Self Organizing Systems

An approach to description of interactive psychoinformation systems, based on the concept of "virtualization" and essentially using the technique of the "secondary image synthesis" (adap-org/9409002), is sketched. The article has a rather discussional character and maybe considered as a comment to some statements of the introduction to the author's paper "Complex projective geometry and quantum projective field theory" (Theor. Math. Phys., 1994).

We use a very simple description of human driving behavior to simulate traffic. The regime of maximum vehicle flow in a closed system shows near-critical behavior, and as a result a sharp decrease of the predictability of travel time. Since Advanced Traffic Management Systems (ATMSs) tend to drive larger parts of the transportation system towards this regime of maximum flow, we argue that in consequence the traffic system as a whole will be driven closer to criticality, thus making predictions much harder. A simulation of a simplified transportation network supports our argument.

We present a two-level model of organizational training and agent production. Managers decide whether or not to train based on both the costs of training compared to the benefits and on their expectations and observations of the number of other firms that also train. Managers also take into account the sum of their employees' contributions and the average tenure length within their organization. Employees decide whether or not to contribute to production based on their expectations as to how other employees will act. Trained workers learn over time and fold their increased productivity into their decision whether or not to contribute. We find that the dynamical behavior at the two levels is closely coupled: the evolution of the industry over time depends not only on the characteristics of training programs, learning curves, and cost-benefit analyses, but on the vagaries of chance as well. For example, in one case, the double dilemma can be resolved for the industry as a whole and productivity then increases steadily over time. In another, the organizational level dilemma may remain unresolved and workers may contribute at fluctuating levels. In this case the overall productivity stays low. We also find a correlation between high productivity and low turnover and show that a small increase in training rates can lead to explosive growth in productivity.

A two-dimensional cellular automaton model of traffic flow with open boundaries are investigated by computer simulations. The outflow of cars from the system and the average velocity are investigated. The time sequences of the outflow and average velocity have flicker noises in a jamming phase. The low density behavior are discussed with simple jam-free approximation.

In most models of traffic flow, the car density p is the only free parameter in determining the average car velocity ⟨v⟩ . The critical car density p c , which is defined to be the car density separating the jamming phase (with ⟨v⟩=0 ) and the moving phase (with ⟨v⟩>0 ), is an important physical quantity to investigate. By means of simple statistical argument, we show that p c <1 for the Biham-Middleton-Levine model of traffic flow in two or higher spatial dimensions. In particular, we show that p c ≤11/12 in 2 dimension and p c ≤1− ( D−1 2D ) D in D ( D>2 ) dimensions.

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.

The most abundant biological particles in the atmosphere are pollen grains and spores. Self protection of pollen allergy is possible through the information of future pollen contents in the air. In spite of the importance of airborne pol len concentration forecasting, it has not been possible to predict the pollen concentrations with great accuracy, and about 25% of the daily pollen forecasts have resulted in failures. Previous analysis of the dynamic characteristics of atmospheric pollen time series indicate that the system can be described by a low dimensional chaotic map. We apply the wavelet transform to study the multifractal characteristics of an a irborne pollen time series. We find the persistence behaviour associated to low pollen concentration values and to the most rare events of highest pollen co ncentration values. The information and the correlation dimensions correspond to a chaotic system showing loss of information with time evolution.

We examine the line-wrap feature of text processors and show that adding characters to previously formatted lines leads to the cascading of words to subsequent lines and forms a state of self-organized criticality. We show the connection to one-dimensional random walks and diffusion problems, and we examine the predictability of catastrophic cascades.