A demand adjustment process

The aspiration approach to cooperative games, which has been studied by a number of authors, including Cross, Turbay, Albers, Selten and Bennett, presumes that players in a game bargain over their reservation prices, or aspirations. A number of aspiration-based solution concepts have been put forth, and aspiration solutions have been connected to non-cooperative bargaining models. Missing in this approach has been theory of how aspirations themselves arise. The present paper is an attempt to fill this gap. It describes a very general demand adjustment process, using the framework of set-valued dynamical systems developed by Maschler and Peleg. This demand adjustment process always converges; sufficient conditions are given in order that it converge to an aspiration, and that it converge in a finite number of steps.     

多人多目标资源分配协商对策

资源分配问题,一直是决策分析理论研究的核心问题之一.从对各种经济系统进行决策分析中,可得出一类多人多目标资源分配问题的数学描述如下:     

A projected gradient dynamical system modelling the dynamics of bargaining

We propose a projected gradient dynamical system as a model for a bargaining scheme for an asset for which the two interested agents have personal valuations that do not initially coincide. The personal valuations are formed using subjective beliefs concerning the future states of the world, and the reservation prices are calculated using expected utility theory. The agents are not rigid concerning their subjective probabilities and are willing to update them under the pressure to reach finally an agreement concerning the asset. The proposed projected dynamical system, on the space of probability measures, provides a model for the evolution of the agents, beliefs during the bargaining period and is constructed so that an agreement is reached under the minimum possible deviation of both agents from their initial beliefs. The convergence results are shown using techniques from convex dynamics and Lyapunov function theory.     

On numerical approaches to the analysis of topology of the phase space for dynamical integrability

In this paper we consider the possibility to use numerical simulations for a computer assisted qualitative analysis of dynamical systems. We formulate a rather general method of recovering the obstructions to dynamical integrability for the systems that after reduction have a small number of degrees of freedom. We generalize this method using the results of KAM theory and stochastic approaches to the families of parameter depending systems. This permits to localize possible integrability regions in the parameter space. We give some examples of application of this approach to dynamical systems having a mechanical origin.     

Multicriteria optimization of convex dynamical systems

We suggest an approach to the solution of multicriteria optimization problems for dynamical systems described by differential inclusions. The investigation is restricted to dynamical systems with concave differential inclusion, for which the trajectory tube is convex. Such systems are typical of economic models. We assume that the criteria for the choice of the solution depend on the system state at a given terminal time and are related to it by sufficiently arbitrary functions. The approach is based on the interactive visualization of the Pareto frontier, which is carried out by approximating the reachable set of the dynamical system and the Edgeworth-Pareto set of feasible criteria vectors.     

On the uniqueness of solutions to a class of discontinuous dynamical systems

The study of uniqueness of solutions of discontinuous dynamical systems has an important implication: multiple solutions to the initial value problem could not be found in real dynamical systems; also the (attracting or repulsive) sliding mode is inherently linked to the uniqueness of solutions. In this paper a strengthened Lipschitz-like condition for differential inclusions and a geometrical approach for the uniqueness of solutions for a class of Filippov dynamical systems are introduced as tools for uniqueness. Several theoretical and practical examples are discussed.     

Mean topological dimension

In this paper we present some results and applications of a new invariant for dynamical systems that can be viewed as a dynamical analogue of topological dimension. This invariant has been introduced by M. Gromov, and enables one to assign a meaningful quantity to dynamical systems of infinite topological dimension and entropy. We also develop an alternative approach that is metric dependent and is intimately related to topological entropy.     

Sample-Path Stability of Non-Stationary Dynamic Economic Systems

The goal of this paper is to introduce and illustrate a new approach to the stability analysis of sample-paths of non-linear stochastic economic models with non-stationary components. We place our study within the mathematical theory of random dynamical systems and apply the concept of a random fixed point which is tailor-made for the study of the long-term behavior of sample-paths in stochastic systems. The main tool for the application of this approach is a Banach-type fixed point theorem for non-stationary random dynamical systems which is proved here. The concept and the theorem are thoroughly explained and illustrated by examples from stochastic growth theory.     

Application of mode decomposition approach to the synchronization of the non-identical dynamical systems

The synchronization problem of two different dynamical systems is considered by employing mode decomposition approach in this paper. Synchronization of non-identical coupled dynamical systems with non-chaotic attractors, i.e., equilibria, periodic and quasi-periodic solutions, is investigated analytically and numerically. Some results are obtained by this method. Some examples, supported by numerical simulation, are presented to illustrate the conciseness and effectiveness of the approach.     

Robust dynamical compensator design for discrete-time linear periodic systems

This paper considers dynamical compensators design for purpose of pole assignment for discrete-time linear periodic systems. Similar to linear time-invariant systems, it is pointed out that the design of a periodic dynamical compensator can be converted into the design of a periodic output feedback controller for an augmented system. Utilizing the recent result on output feedback pole assignment, parametric solutions for this problem are obtained. The design approach can be used as a basis for the robust dynamical compensator design for this type of systems. Combined with a robustness index presented in this paper, robust dynamical compensator design problem is converted into a constrainted optimization problem. A numerical example is employed to illustrate the validity and feasibility of the methods.     

Convention evolution in organizations and markets

Conventions are essential for the coordination of multi-agent systems. However, in many systems conventions can not be legislated in advance and need to emerge during the system's activity. As designers of such systems we may wish to ensure that conventions will evolve rapidly. Given a classical model for convention evolution where agents tend to mimic agents they interact with, the designer can control the organizational structure of the system in order to speedup the evolution of conventions. This paper introduces a study of convention evolution in the context of basic organizational structures. Our study sheds light on a basic aspect of organizational design which has not been discussed in the literature, and which is crucial for efficient design of non-trivial multi-agent systems.     

An approach of partial control design for system control and synchronization

In this paper, a general approach of partial control design for system control and synchronization is proposed. It turns control problems into simpler ones by reducing their control variables. This is realized by utilizing the dynamical relations between variables, which are described by the dynamical relation matrix and the dependence–influence matrix. By adopting partial control theory, the presented approach provides a simple and general way to stabilize systems to their partial or whole equilibriums, or to synchronize systems with their partial or whole states. Further, based on this approach, the controllers can be simplified. Two examples of synchronizing chaotic systems are given to illustrate its effectiveness.     

Dynamics and axiomatics of the equal area bargaining solution

We present an alternative formulation of the two-person equal area bargaining solution based on a dynamical process describing the disagreement point set. This alternative formulation provides an interpretation of the idea of equal concessions. Furthermore, it leads to an axiomatic characterization of the solution. Received: November 1998/Revised version: September 1999     

A method of continuous time approximation of delayed dynamical systems

This paper presents a new method to analyze response of linear and nonlinear dynamical systems with time delay. The method proposes a continuous time approximation of the delayed portion of the response. This leads to a high and finite dimensional state space formulation of the time-delayed system. The advantage of the current method lies in that the resulting finite dimensional state equations are in the standard state space form, making all the existing analysis methods and control design tools for linear and nonlinear dynamical systems amenable to the current approach. The method can also handle multiple independent time delays in a natural way. One- and two-dimensional dynamical systems with time delay are used to demonstrate the effectiveness of the method.     

Estimates for Correlation in Dynamical Systems: From Hölder Continuous Functions to General Observables

For many dynamical systems that are popular in applications, estimates are known for the decay of correlation in the case of Hölder continuous functions. In the present article, we suggest an approach that allows us to obtain estimates for correlation in dynamical systems in the case of arbitrary functions. This approach is based on approximation and estimates are obtained with the use of known estimates for Hölder continuous functions. We apply our approach to transitive Anosov diffeomorphisms and derive the central limit theorem for the characteristic functions of certain sets with boundary of zero measure.     

Stability of random attractors under perturbation and approximation

The comparison of the long-time behaviour of dynamical systems and their numerical approximations is not straightforward since in general such methods only converge on bounded time intervals. However, one can still compare their asymptotic behaviour using the global attractor, and this is now standard in the deterministic autonomous case. For random dynamical systems there is an additional problem, since the convergence of numerical methods for such systems is usually given only on average. In this paper the deterministic approach is extended to cover stochastic differential equations, giving necessary and sufficient conditions for the random attractor arising from a random dynamical system to be upper semi-continuous with respect to a given family of perturbations or approximations.     

Differential-algebraic approach to constructing representations of commuting differentiations in functional spaces and its application to nonlinear integrable dynamical systems

There is developed a differential-algebraic approach to studying the representations of commuting differentiations in functional differential rings under nonlinear differential constraints. An example of the differential ideal with the only one conserved quantity is analyzed in detail, the corresponding Lax type representations of differentiations are constructed for an infinite hierarchy of nonlinear dynamical systems of the Burgers and Korteweg–de Vries type. A related infinite bi-Hamiltonian hierarchy of Lax type dynamical systems is constructed.     

Hybrid decentralized maximum entropy control for large-scale dynamical systems

In the analysis of complex, large-scale dynamical systems it is often essential to decompose the overall dynamical system into a collection of interacting subsystems. Because of implementation constraints, cost, and reliability considerations, a decentralized controller architecture is often required for controlling large-scale interconnected dynamical systems. In this paper, a novel class of fixed-order, energy-based hybrid decentralized controllers is proposed as a means for achieving enhanced energy dissipation in large-scale lossless and dissipative dynamical systems. These dynamic decentralized controllers combine a logical switching architecture with continuous dynamics to guarantee that the system plant energy is strictly decreasing across switchings. The general framework leads to hybrid closed-loop systems described by impulsive differential equations. In addition, we construct hybrid dynamic controllers that guarantee that each subsystem–subcontroller pair of the hybrid closed-loop system is consistent with basic thermodynamic principles. Special cases of energy-based hybrid controllers involving state-dependent switching are described, and an illustrative combustion control example is given to demonstrate the efficacy of the proposed approach.     

Stability Analysis for Discrete Biological Models Using Algebraic Methods

This paper is concerned with stability analysis of biological networks modeled as discrete and finite dynamical systems. We show how to use algebraic methods based on quantifier elimination, real solution classification and discriminant varieties to detect steady states and to analyze their stability and bifurcations for discrete dynamical systems. For finite dynamical systems, methods based on Gr?bner bases and triangular sets are applied to detect steady states. The feasibility of our approach is demonstrated by the analysis of stability and bifurcations of several discrete biological models using implementations of algebraic methods.     

The Dynamical System Approach to Multivariate Data Analysis

In this survey a number of problems arising in multivariate data analysis (MDA) are listed and reformulated as matrix fitting (e.g., least-squares, maximum likelihood, etc.) constrained optimization problems (OPs). The goal is to demonstrate that consideration and solution of these diverse MDA problems can be unified by means of the dynamical system approach. The approach transforms the MDA problems into dynamical systems on a manifold defined by the constraints of the original OP.