H2 Optimal Coordination of Homogeneous Agents Subject to Limited Information Exchange

Controllers with a diagonal-plus-low-rank structure constitute a scalable class of controllers for multi-agent systems. Previous research has shown that diagonal-plus-low-rank control laws appear as the optimal solution to a class of multi-agent H2 coordination problems, which arise in the control of wind farms. In this paper we show that this result extends to the case where the information exchange between agents is subject to limitations. We also show that the computational effort required to obtain the optimal controller is independent of the number of agents and provide analytical expressions that quantify the usefulness of information exchange

The Division of Labor, Coordination Costs and the Growth of Government

The paper develops a dynamic, general equilibrium model of specialization-driven growth in which the private cost of coordinating among specialists is a function of public expenditure on physical and institutional infrastructure. Growth is characterized by endogenous increases in labor specialization, the capital-labor ratio, coordination costs, market size, and the interdependence of economic agents. In addition, model provides an explanation for a frequently ignored stylized fact of economic growth, the secular rise of government's share of output, in terms of the economic role of the government.development; endogenous growth; labor specialization; dynamic model; institutions; division of labor; growth; transactions costs; coordination; coordination costs; contract enforcement; organization; neoinstitutionalism; traditional economy; interpersonal exchange; government; transaction sector; public investment; public capital

MAKE-OR-BUY THEORIES: WHERE DO WE STAND?

The aim of this paper is to discuss the state-of-the art and the directions for research on the make-orbuy problem. After thirty years of research efforts, we now have numerous contributions explaining different aspects of the nature and existence of the firm. The search for a unified theory, however, still remains, at a theoretical level, a challenge. The task is not easy, perhaps because the theory of the firm develops along two different strands, one analyzing the factors influencing the boundaries, and the other one relating to the internal structure; or because, even inside the same research strand, it is not really easy to grasp the similarities and differences between contributions that have followed one another in rapid succession over the last few years. This paper examines the theories concerning the make-or-buy problem, focusing on recent contributions that have tried to develop a unified framework and emphasizes the role of incomplete contracts as a common and significant trait of the theories discussed

Consensus-based control for a network of diffusion PDEs with boundary local interaction

In this paper the problem of driving the state of a network of identical agents, modeled by boundary-controlled heat equations, towards a common steady-state profile is addressed. Decentralized consensus protocols are proposed to address two distinct problems. The first problem is that of steering the states of all agents towards the same constant steady-state profile which corresponds to the spatial average of the agents initial condition. A linear local interaction rule addressing this requirement is given. The second problem deals with the case where the controlled boundaries of the agents dynamics are corrupted by additive persistent disturbances. To achieve synchronization between agents, while completely rejecting the effect of the boundary disturbances, a nonlinear sliding-mode based consensus protocol is proposed. Performance of the proposed local interaction rules are analyzed by applying a Lyapunov-based approach. Simulation results are presented to support the effectiveness of the proposed algorithms

Formation Shape Control Based on Distance Measurements Using Lie Bracket Approximations

We study the problem of distance-based formation control in autonomous multi-agent systems in which only distance measurements are available. This means that the target formations as well as the sensed variables are both determined by distances. We propose a fully distributed distance-only control law, which requires neither a time synchronization of the agents nor storage of measured data. The approach is applicable to point agents in the Euclidean space of arbitrary dimension. Under the assumption of infinitesimal rigidity of the target formations, we show that the proposed control law induces local uniform asymptotic stability. Our approach involves sinusoidal perturbations in order to extract information about the negative gradient direction of each agent's local potential function. An averaging analysis reveals that the gradient information originates from an approximation of Lie brackets of certain vector fields. The method is based on a recently introduced approach to the problem of extremum seeking control. We discuss the relation in the paper

Genetic learning as an explanation of stylized facts of foreign exchange markets

This paper revisits the Kareken-Wallace model of exchange rate formation in a two-country overlapping generations world. Following the seminal paper by Arifovic (Journal of Political Economy, 104, 1996, 510-541) we investigate a dynamic version of the model in which agents' decision rules are updated using genetic algorithms. Our main interest is in whether the equilibrium dynamics resulting from this learning process helps to explain the main stylized facts of free-floating exchange rates (unit roots in levels together with fat tails in returns and volatility clustering). Our time series analysis of simulated data indicates that for particular parameterizations, the characteristics of the exchange rate dynamics are, in fact, very similar to those of empirical data. The similarity appears to be quite insensitive with respect to some of the ingredients of the GA algorithm (i.e. utilitybased versus rank-based or tournament selection, binary or real coding). However, appearance or not of realistic time series characteristics depends crucially on the mutation probability (which should be low) and the number of agents (not more than about 1000). With a larger population, this collective learning dynamics looses its realistic appearance and instead exhibits regular periodic oscillations of the agents' choice variables. -- Dieses Papier betrachtet das Kareken-Wallace-Modell für die Wechselkursbildung in einer Welt mit 2 Ländern und sich überlappenden Generationen. In der Nachfolge des zukunftsweisenden Papiers von Arifovic (1996) untersuchen wir eine dynamische Version des Modells bei dem die Entscheidungsregeln mithilfe genetischer Algorithmen jeweils aktualisiert werden. Unser Hauptinteresse geht dahin, herauszufinden, ob die Gleichgewichtsdynamik, die aus diesem Lernprozess resultiert, dabei helfen kann, die wichtigsten stilisierten Fakten von flexiblen Wechselkursen zu erklären (Einheitswurzeln bei den Niveaus mit dicken Enden der Ertragsverteilung und Klumpenbildung bei den Volatilitäten). Unsere Analyse simulierter Daten weist darauf hin, dass für bestimmte Parametrisierungen der Charakter der Wechselkursdynamik tatsächlich dem von empirischen Daten sehr ähnlich ist. Die Ähnlichkeit scheint sehr wenig von speziellen Eigenschaften des gewählten GA-Algorithmus abzuhängen (z. B. nutzenbasiert versus rangbasiert, binäre oder reale Kodierung). Dagegen ist die Mutationswahrscheinlichkeit (die niedrig sein sollte) und die Anzahl der Agenten (die nicht größer als 1000 sein sollte) wichtig. Mit mehr Teilnehmern verliert die kollektive Lerndynamik ihr realistisches Aussehen und es kommt zu regelmäßigen periodischen Schwankungen bei den Variablen, die die Agenten auswählen.Learning,Genetic algorithms,Exchange rate dynamics

Genetic learning as an explanation of stylized facts of foreign exchange markets

This paper revisits the Kareken-Wallace model of exchange rate formation in a two-country overlapping generations world. Following the seminal paper by Arifovic (Journal of Political Economy, 104, 1996, 510 – 541) we investigate a dynamic version of the model in which agents? decision rules are updated using genetic algorithms. Our main interest is in whether the equilibrium dynamics resulting from this learning process helps to explain the main stylized facts of free-floating exchange rates (unit roots in levels together with fat tails in returns and volatility clustering). Our time series analysis of simulated data indicates that for particular parameterizations, the characteristics of the exchange rate dynamics are, in fact, very similar to those of empirical data. The similarity appears to be quite insensitive with respect to some of the ingredients of the GA algorithm (i.e. utility-based versus rank-based or tournament selection, binary or real coding). However, appearance or not of realistic time series characteristics depends crucially on the mutation probability (which should be low) and the number of agents (not more than about 1000). With a larger population, this collective learning dynamics looses its realistic appearance and instead exhibits regular periodic oscillations of the agents? choice variables. --learning , genetic algorithms , exchange rate dynamics

Consensus-based approach to peer-to-peer electricity markets with product differentiation

With the sustained deployment of distributed generation capacities and the more proactive role of consumers, power systems and their operation are drifting away from a conventional top-down hierarchical structure. Electricity market structures, however, have not yet embraced that evolution. Respecting the high-dimensional, distributed and dynamic nature of modern power systems would translate to designing peer-to-peer markets or, at least, to using such an underlying decentralized structure to enable a bottom-up approach to future electricity markets. A peer-to-peer market structure based on a Multi-Bilateral Economic Dispatch (MBED) formulation is introduced, allowing for multi-bilateral trading with product differentiation, for instance based on consumer preferences. A Relaxed Consensus+Innovation (RCI) approach is described to solve the MBED in fully decentralized manner. A set of realistic case studies and their analysis allow us showing that such peer-to-peer market structures can effectively yield market outcomes that are different from centralized market structures and optimal in terms of respecting consumers preferences while maximizing social welfare. Additionally, the RCI solving approach allows for a fully decentralized market clearing which converges with a negligible optimality gap, with a limited amount of information being shared.Comment: Accepted for publication in IEEE Transactions on Power System

Optimal dynamic profit taxation: The derivation of feedback Stackelberg equilibria

Game Theory;Corporate Tax;operations research