Showing papers by "Michael North published in 2010"

Tutorial on agent-based modelling and simulation

Abstract: Agent-based modelling and simulation (ABMS) is a relatively new approach to modelling systems composed of autonomous, interacting agents. Agent-based modelling is a way to model the dynamics of complex systems and complex adaptive systems. Such systems often self-organize themselves and create emergent order. Agent-based models also include models of behaviour (human or otherwise) and are used to observe the collective effects of agent behaviours and interactions. The development of agent modelling tools, the availability of micro-data, and advances in computation have made possible a growing number of agent-based applications across a variety of domains and disciplines. This article provides a brief introduction to ABMS, illustrates the main concepts and foundations, discusses some recent applications across a variety of disciplines, and identifies methods and toolkits for developing agent models.

Multiscale agent-based consumer market modeling

Abstract: Consumer markets have been studied in great depth, and many techniques have been used to represent them. These have included regression-based models, logit models, and theoretical market-level models, such as the NBD-Dirichlet approach. Although many important contributions and insights have resulted from studies that relied on these models, there is still a need for a model that could more holistically represent the interdependencies of the decisions made by consumers, retailers, and manufacturers. When the need is for a model that could be used repeatedly over time to support decisions in an industrial setting, it is particularly critical. Although some existing methods can, in principle, represent such complex interdependencies, their capabilities might be outstripped if they had to be used for industrial applications, because of the details this type of modeling requires. However, a complementary method—agent-based modeling—shows promise for addressing these issues. Agent-based models use business-driven rules for individuals (e.g., individual consumer rules for buying items, individual retailer rules for stocking items, or individual firm rules for advertizing items) to determine holistic, system-level outcomes (e.g., to determine if brand X's market share is increasing). We applied agent-based modeling to develop a multi-scale consumer market model. We then conducted calibration, verification, and validation tests of this model. The model was successfully applied by Procter & Gamble to several challenging business problems. In these situations, it directly influenced managerial decision making and produced substantial cost savings. © 2010 Wiley Periodicals, Inc. Complexity, 2010

Toward teaching agent-based simulation

Abstract: Agent-based simulation (ABS) is a relatively recent modeling technique that is being widely used to model complex adaptive systems by many disciplines. Few full length courses exist on agent-based modeling and a standard curriculum has not yet been established, but there is considerable demand to include ABS into simulation courses. Modelers often come to agent-based simulation by way of self-study or attendance at tutorials and short courses. Although there is substantial overlap, there are many aspects of ABS that differ from discrete-event simulation (DES) and System Dynamics (SD), including applicable problem domains, disciplines and backgrounds of students, and the underpinnings of its computational implementation. These factors make ABS difficult to include as an incremental add-on to existing simulation courses. This paper reports on some approaches to teaching the modeling of complex systems and agent-based simulation that the authors have used in a range of classes and workshops.

Agent-based Modeling of a Rental Market for Agricultural Land in the Argentine Pampas

Abstract: More than half of land in the Argentine Pampas is cropped by tenants. The importance of production on rented land motivated development of a LAnd Rental MArket (LARMA) model with endogenous formation of Land Rental Price (LRP). LARMA is a “hybrid” model that relies partly on easy-to-implement concepts from neoclassical economics, but addresses drawbacks of this approach by being integrated into an agentbased model that involves heterogeneous agents interacting in a dynamic environment. LRP formation assumes economic equilibrium: it is the price at which supply of rental land area equals land demand. LRP depends on (a) the “willing to accept” price (WTAP) of owners renting out land due to lack of capital or dissatisfaction with recent economic progress (a Minimum Progress Rate, MPR, is targeted), and (b) the “willing to pay” price (WTPP) and working capital (WC) of potential tenants. Land owners base WTAP on estimated profits they could achieve from operating their farms. Potential tenants base WTPP on their target gross margin for the upcoming cycle. Initial experiments with simplified economic contexts (input and output prices) did not show significant differences in regional land tenure from LARMA vs. use of an exogenous, fixed LRP. Nevertheless, simulated LRP trajectories reproduced observed dynamics: prices followed consistently the trajectories of conditions driving crop yields and profits. Consideration of MPR induced many land owners to rent out their farms, thus increasing the proportion of rented land. LARMA is a first attempt to translate equilibrium-based models into a model involving agent heterogeneity and social embeddedness. Many LARMA components will be used in a subsequent model with full bilateral transactions.

Transcending borders: the sea as realm of memory

Abstract: In this joint paper, ‘Transcending Borders: The Sea as Realm of Memory’, we shall discuss issues of regional integration by applying the concept of realm of memory to maritime border regions in the Baltic Sea and the South China Sea. Since the material or immaterial realms of memory constitute symbolic intersections between cultures, spaces and times, they simultaneously affect not only the neighbouring countries and the national cultures of memory, but also societies and ethnic or religious groups. The Sea and adjacent regions provide an excellent example and object of study for this category of shared realms of memory. In this paper we are studying two straits regions in comparison—the Danish Sound (Oresund) and the Strait of Malacca—and try to reconstruct their different, shifting roles across history. Since the collective memory shapes how we perceive things and spaces across time, it affects contemporary policy making and thus (regional) integration in maritime border regions.

Multigame dynamics: structures and strategies

Abstract: The dominant strategy among game theorists is to pose a problem narrowly, formalize that structure, and then pursue analytical solutions. This strategy has achieved a number of stylized insights, but has not produced nuanced game-theoretic solutions to larger and more complex issues such as extended international historical conflicts, or the detailed assessment of variegated policy alternatives. In order to model more complex historical and policy-oriented processes, it has been proposed that a broader computational approach to game theory that has the potential to capture richer forms of social dynamics be used, namely the 'multigame.' In the multigame approach there are multiple games each of which is open, prototypical, implicit, reciprocal, positional, variegated and historical. When later implemented, the multigame approach will offer the potential to rigorously model complex international historical conflicts and variegated policy alternatives that, heretofore, typically required qualitative analysis.

Modeling Endogenous Coordination Using a Dynamic Language

Abstract: Dynamic languages are computer languages that allow programs to substantially restructure themselves while they are running. Interest in these kinds of programming languages has dramatically increased in the last few years. This paper builds on previous work by exploring the use of a popular dynamic language, namely Groovy, within the Repast Simphony (Repast S) platform. This language is applied to modeling the endogenous emergence of coordination within a group of social agents. This paper introduces the Endogenous Emergence of Coordination (EndEC) model. It then highlights many of the features in Groovy that were found to be particularly helpful during model implementation. This demonstrates the powerful and flexible capabilities that a dynamic language can bring to the creation of agent-based models. What is particularly exciting is the potential for creating truly dynamic and evolving open-ended simulations, where the simulation ­fundamentally changes as it executes.

The Baltic Sea and South China Sea regions: incomparable models of regional integration?

Abstract: This introduction explains the key concepts of integration and exemplifies how they can be applied to processes of regional integration in the Baltic Sea and South China Sea regions.