CiteULike: sudhira's library [63 articles]

Ãber ein Paradoxon aus der Verkehrsplanung

D Braess — 2006-06-12T05:36:04-00:00

Mathematical Methods of Operations Research (ZOR), Vol. 12, No. 1. (December 1968), pp. 258-268.

Evaluating similarity measures: a large-scale study in the orkut social network

Ellen Spertus — 2006-06-02T12:13:37-00:00

(2005), pp. 678-684.

Geovisualization and GIScience

Menno-Jan Kraak — 2005-04-24T05:17:31-00:00

Cartography and Geographic Information Science, Vol. 32, No. 2. (April 2005), pp. 67-68.

Untitled

2006-06-01T05:12:14-00:00

Determining development density using the Urban Carrying Capacity Assessment System

Kyushik Oh — 2006-05-27T08:42:19-00:00

Landscape and Urban Planning, Vol. 73, No. 1. (15 August 2005), pp. 1-15.

As the urban population increases, so do diverse urban problems and concerns including issues of servicing large numbers of people within existing infrastructures, as a result of over-development and over-concentration. Environmental problems, particularly air and water pollution, have become more evident and are now considered central issues for urban planners and decision-makers. To address these environmental problems, practical approaches which incorporate the concept of carrying capacity into managing urban development are needed.This research aims at developing an integrated framework for assessing urban carrying capacity which can determine development density based on current infrastructures and land use. First, seven determining factors were identified for urban carrying capacity including energy, green areas, roads, subway systems, water supply, sewage treatment, and waste treatment, and the assessment framework was developed by integrating such factors. Secondly, the Urban Carrying Capacity Assessment System, a GIS-based carrying capacity assessment system, was developed based upon the framework. Finally, through a case study for determining the carrying capacity for an area in Seoul, South Korea, it was revealed that decision support with UCCAS demonstrated in this research can play a pivotal role in planning and managing urban development more effectively.

Causes of Sprawl: A Portrait from Space

Marcy Burchfield — 2006-05-13T05:18:45-00:00

Quarterly Journal of Economics, Vol. 121, No. 2., 587.

We study the extent to which U. S. urban development is sprawling and what determines differences in sprawl across space. Using remote-sensing data to track the evolution of land use on a grid of 8.7 billion 30 × 30 meter cells, we measure sprawl as the amount of undeveloped land surrounding an average urban dwelling. The extent of sprawl remained roughly unchanged between 1976 and 1992, although it varied dramatically across metropolitan areas. Ground water availability, temperate climate, rugged terrain, decentralized employment, early public transport infrastructure, uncertainty about metropolitan growth, and unincorporated land in the urban fringe all increase sprawl.

How migration restrictions limit agglomeration and productivity in China

Chun-Chung Au — 2006-04-21T12:39:48-00:00

Journal of Development Economics, Vol. In Press, Corrected Proof

China strongly restricts rural-urban migration, resulting in a well acknowledged surplus of labor in agriculture. But migration is also restricted within sectors. This paper argues that these intra-sector restrictions lead to insufficient agglomeration of economic activity in both the rural industrial and urban sectors, with resulting first order losses in GDP. For urban areas the paper estimates a city productivity relationship, based on city GDP numbers. The effects of access, educational attainment, FDI, and public infrastructure on productivity are estimated. Given these, worker productivity is shown to be an inverted U-shape function of city employment, with the peak point shifting out as industrial composition moves from manufacturing to services, as predicted by urban theory. As far as we know this is the first paper to actually estimate the relationship between output per worker and city scale for any country. The majority of Chinese cities are shown to be potentially undersized--below the lower bound on the 95% confidence interval about the size where their output per worker peaks. The paper calculates the large gains from increased agglomeration in both the rural industrial and urban sectors.

Swarm Intelligence : From Natural to Artificial Systems (Santa Fe Institute Studies on the Sciences of Complexity)

Eric Bonabeau — 2006-03-14T12:59:22-00:00

(23 September 1999)

Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Composed of simple interacting agents, this intelligence lies in the networks of interactions among individuals and between individuals and the environment. A fascinating subject, social insects are also a powerful metaphor for artificial intelligence, and the problems they solve--finding food, dividing labor among nestmates, building nests, responding to external challenges--have important counterparts in engineering and computer science. This book provides a detailed look at models of social insect behavior and how to apply these models in the design of complex systems. The book shows how these models replace an emphasis on control, preprogramming, and centralization with designs featuring autonomy, emergence, and distributed functioning. These designs are proving immensely flexible and robust, able to adapt quickly to changing environments and to continue functioning even when individual elements fail. In particular, these designs are an exciting approach to the tremendous growth of complexity in software and information. Swarm Intelligence draws on up-to-date research from biology, neuroscience, artificial intelligence, robotics, operations research, and computer graphics, and each chapter is organized around a particular biological example, which is then used to develop an algorithm, a multiagent system, or a group of robots. The book will be an invaluable resource for a broad range of disciplines.

Avoiding the Braess Paradox in Non-Cooperative Networks

Yannis Korilis — 2006-02-26T07:08:48-00:00

Journal of Applied Probability, Vol. 36, No. 1. (1999), pp. 211-222.

The exponential growth of computer networking demands massive upgrades in the capacity of existing networks. Traditional capacity design methodologies, developed with the single-class networking paradigm in mind, overlook the non-cooperative structure of modern networks. Consequently, such design approaches entail the danger of degraded performance when resources are added to a network, a phenomenon known as the Braess paradox. The present paper proposes methods for adding resources efficiently to a non-cooperative network of general topology. It is shown that the paradox is avoided when resources are added across the network, rather than on a local scale, and when upgrades are focused on direct connections between the sources and destinations. The relevance of these results for modern networks is demonstrated.

A Paradox of Congestion in a Queuing Network

Joel Cohen — 2006-02-26T06:55:22-00:00

Journal of Applied Probability, Vol. 27, No. 3. (1990), pp. 730-734.

In an uncongested transportation network, adding routes and capacity to an existing network must decrease, or at worst not change, the average time individuals require to travel through the network from a source to a destination. Braess (1968) discovered that the same is not true in congested networks. Here we give an example of a queuing network in which added capacity leads to an increase in the mean transit time for everyone. Self-seeking individuals are unable to refrain from using the additional capacity, even though using it leads to deterioration in the mean transit time. This example appears to be the first queuing network to demonstrate the general principle that in non-co-operative games with smooth payoff functions, user-determined equilibria generically deviate from system-optimal equilibria.

Geosimulation: object-based modeling of urban phenomena

I Benenson — 2004-12-28T18:01:30-00:00

Computers, Environment and Urban Systems, Vol. 28, No. 1. (January 2004), pp. 1-8.

Plural dreams: India in the 21st century

Rakesh Kapoor — 2005-12-21T16:59:35-00:00

Futures, Vol. 36, No. 6-7. ( 2004), pp. 637-653.

COMPLEX SYSTEMS:Life After Chaos

Carl Zimmer — 2005-12-20T10:20:31-00:00

Science, Vol. 284, No. 5411. (1999), pp. 83-86.

Complexity in Chemistry

George Whitesides — 2005-12-20T10:20:31-00:00

Science, Vol. 284, No. 5411. (1999), pp. 89-92.

Complexity in Natural Landform Patterns

BT Werner — 2005-12-20T10:20:31-00:00

Science, Vol. 284, No. 5411. (1999), pp. 102-104.

Complexity in Biological Signaling Systems

Gezhi Weng — 2005-12-20T10:20:31-00:00

Science, Vol. 284, No. 5411. (1999), pp. 92-96.

Economic agents and markets as emergent phenomena

Leigh Tesfatsion — 2005-12-20T10:20:31-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7191-7192.

An overview of recent work in agent-based computational economics is provided, with a stress on the research areas highlighted in the National Academy of Sciences Sackler Colloquium session "Economic Agents and Markets as Emergent Phenomena" held in October 2001.

Behavioral models for complex decision analysis

Hiroyuki Tamura — 2005-12-20T10:20:31-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 655-665.

The focus of this paper is to propose some behavioral (or descriptive) models of individual decision making and group decision making under risk/uncertainty as follows: models to explain the violations of expected utility models for the individual decision making; and a model to describe the ethical consensus formation process among multi-agent conflicting decision makers. The former models extend Kahneman-Tversky model of prospect theory and resolve Allais and Ellsburg paradoxes. The later model extends additive/utility independence in consensus formation process to get more flexible preference structure among conflicting decision makers.

COMPLEX SYSTEMS:Exploring the Systems of Life

Robert Service — 2005-12-20T10:20:31-00:00

Science, Vol. 284, No. 5411. (1999), pp. 80a-83.

An intelligent agent model

Ralf Schleiffer — 2005-12-20T10:20:31-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 666-693.

This paper discusses fundamental issues of intelligent agents. Based on a portrayal of agent characteristics a general agent architecture linking aspects of perception, interpretation of natural language, learning and decision-making is provided. Agents built upon this architecture are equipped to handle unknown, open and distributed environments. The paper concludes with a discussion whether or not agents designed in accordance with this architecture exhibit some sort of intelligence.

Agent-based approach to complex systems modeling

Mina Ryoke — 2005-12-20T10:20:31-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 717-725.

In this paper, we propose a method for detection of local system structures in a complex database. The complex database is viewed as consisting of mixed numeric and nominal attributes, and the local system structure as expressed by "if-then" rules. The detection of local system structures is an important task, and is concerned with inter-dependent issues. The issues involved in the detection of "if-then" rules include finding the objects that share common interests and then finding if-then rules that characterize those objects. To deal with these issues, an agent-based approach is proposed. Each agent has the role of collecting data points (objects) based on their similarity, for mixed data and detecting a rule. The similarity is introduced so that the agent can handle a mixed database. Each agent will occupy a part of the database as its territory according to the predefined algorithm with which agents try to expand or reduce their territories.

Complexity and Climate

D Rind — 2005-12-20T10:20:31-00:00

Science, Vol. 284, No. 5411. (1999), pp. 105-107.

A multitrajectory, competition model of emergent complexity in human social organization

Dwight Read — 2005-12-20T10:20:31-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7251-7256.

The repeated pattern of emergent human organization at a societal level going from small-scale, egalitarian decentralized societies to complex, stratified, and centralized societies is well-documented in the archaeological record of past societies. In this paper, I outline a multitrajectory model that relates to the broad features of this sequence of societal change. Competition is shown to play a critical role in the way interaction--among decision making, demographic parameters, and social units that organize resource ownership and procurement--either promotes or inhibits change in social organization. Multiagent simulation is discussed as a way to link culturally embedded decision making to emergent properties in the multitrajectory model.

COMPLEX SYSTEMS:Unraveling Bacteria's Dependable Homing System

Elizabeth Pennisi — 2005-12-20T10:20:31-00:00

Science, Vol. 284, No. 5411. (1999)

Some remarks on conflict analysis

Zdzislaw Pawlak — 2005-12-20T10:20:31-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 649-654.

Study of conflicts is of greatest importance both practically and theoretically. Conflict analysis and resolution play an important role in business, governmental, political and lawsuits disputes, labor-management negotiations, military operations and others. Many formal models of conflict situations have been proposed and studied. In this paper we outline a new approach to conflict analysis, which will be illustrated by a simple tutorial example of voting analysis in conflict situations.

Complexity, Pattern, and Evolutionary Trade-Offs in Animal Aggregation

Julia Parrish — 2005-12-20T10:20:31-00:00

Science, Vol. 284, No. 5411. (1999), pp. 99-101.

COMPLEX SYSTEMS:Building Working Cells 'in Silico'

Dennis Normile — 2005-12-20T10:20:31-00:00

Science, Vol. 284, No. 5411. (1999), pp. 80b-81.

MOP/GP models for machine learning

Hirotaka Nakayama — 2005-12-20T10:20:30-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 756-768.

Techniques for machine learning have been extensively studied in recent years as effective tools in data mining. Although there have been several approaches to machine learning, we focus on the mathematical programming (in particular, multi-objective and goal programming; MOP/GP) approaches in this paper. Among them, Support Vector Machine (SVM) is gaining much popularity recently. In pattern classification problems with two class sets, its idea is to find a maximal margin separating hyperplane which gives the greatest separation between the classes in a high dimensional feature space. This task is performed by solving a quadratic programming problem in a traditional formulation, and can be reduced to solving a linear programming in another formulation. However, the idea of maximal margin separation is not quite new: in the 1960s the multi-surface method (MSM) was suggested by Mangasarian. In the 1980s, linear classifiers using goal programming were developed extensively.This paper presents an overview on how effectively MOP/GP techniques can be applied to machine learning such as SVM, and discusses their problems.

Policy analysis from first principles

Scott Moss — 2005-12-20T10:20:30-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7267-7274.

The argument of this paper is predicated on the view that social science should start with observation and the specification of a problem to be solved. On that basis, the appropriate properties and conditions of application of relevant tools of analysis should be defined. Evidence is adduced from data for sales volumes and values of a disparate range of goods to show that frequency distributions are commonly fat-tailed. This result implies that any stable population distribution will generally have infinite variance and perhaps undefined mean. Models with agents that reason about their behavior and are influenced by, but do not imitate, other agents known to them will typically generate fat-tailed time series data. A simulation model of intermediated exchange is reported that is populated by such agents and yields the same type of fat-tailed time series and cross-sectional data that is found in data for fast moving consumer goods and for retail outlets. This result supports the proposition that adaptive agent models of markets with agents that reason and are socially embedded have the same statistical signatures as real markets. Whereas this statistical signature precludes any conventional hypothesis testing or forecasting, these models do offer unique opportunities for validation on the basis of domain expertise and qualitative data. Perhaps the most striking conclusion is that neither current social theory nor any similar construct will ever support an effective policy analysis. However, adaptive agent modeling is an effective substitute when embedded in a wider policy analysis procedure.

Policy evaluations under environmental constraints using a computable general equilibrium model

Toshihiko Masui — 2005-12-20T10:20:30-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 843-855.

In this paper, the AIM/Material model, a country-based computable general equilibrium model with recursive dynamics, is applied to Japan and simulations are carried out on various policies for the concurrent solution of CO2 reduction and solid waste management. To ensure the consistency of waste flows, the material balance is maintained in the model in addition to the monetary balance. Using this model, the GDP loss derived from the environmental constraints on CO2 reduction under the Kyoto Protocol and reduction of final disposal of solid wastes according to the target of the Japanese government is estimated to be 0.2% in 2010 compared to the business-as-usual case. On the other hand, the GDP loss in 2010 will be mitigated by 55% by introducing the following environmental policies: Enhancement of environmental investment, improvement of waste management technology, taxation reform for the introduction of waste power generation, and changes in consumption patterns.

On a bi-dimensional dynamic alternative routing method

Lucia Martins — 2005-12-20T10:20:30-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 828-842.

The analysis of a bi-dimensional dynamic routing model for alternative routing telecommunication networks led to the identification of an instability problem in the synchronous path selection associated with the complex interdependencies among the coefficients of the objective functions and the computed paths for every node pair. In this paper an analytical model enabling to make explicit this problem and evaluate its effects in terms of two global network criteria, is presented. Also a heuristic procedure dedicated to overcome this instability problem and select "good" compromise solutions in terms of network performance is developed. Finally the performance of the proposed routing method using the heuristic is compared by recurring to discrete-event simulation with a reference dynamic routing method (Real Time Network Routing) for some test networks.

Advances in complex systems modeling

Marek Makowski — 2005-12-20T10:20:30-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 593-596.

A structured modeling technology

Marek Makowski — 2005-12-20T10:20:30-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 615-648.

This paper presents the methodological background and implementation of a structured modeling environment developed to meet the requirements of modeling activities undertaken to support intergovernmental negotiations aimed at improving European air quality. Although the motivation for the reported work came from the actual complex application presented in the paper, the actual scope of the paper covers a wide range of issues related to model-based decision-making support. The paper starts with a summary of the context of modeling composed of: the role of models in decision-making support; modeling paradigms; and state-of-the-art aspects of modeling complex problems. The modeling process is then characterized, and the requirement analysis for implementation of structured modeling is specified. The main part of the paper presents the structured modeling technology which was developed to support the implementation of the structured modeling principles for modeling complex problems.

Learning dynamics in social dilemmas

Michael Macy — 2005-12-20T10:20:30-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7229-7236.

The Nash equilibrium, the main solution concept in analytical game theory, cannot make precise predictions about the outcome of repeated mixed-motive games. Nor can it tell us much about the dynamics by which a population of players moves from one equilibrium to another. These limitations, along with concerns about the cognitive demands of forward-looking rationality, have motivated efforts to explore backward-looking alternatives to analytical game theory. Most of the effort has been invested in evolutionary models of population dynamics. We shift attention to a learning-theoretic alternative. Computational experiments with adaptive agents identify a fundamental solution concept for social dilemmas--stochastic collusion--based on a random walk from a self-limiting noncooperative equilibrium into a self-reinforcing cooperative equilibrium. However, we show that this solution is viable only within a narrow range of aspiration levels. Below the lower threshold, agents are pulled into a deficient equilibrium that is a stronger attractor than mutual cooperation. Above the upper threshold, agents are dissatisfied with mutual cooperation. Aspirations that adapt with experience (producing habituation to stimuli) do not gravitate into the window of viability; rather, they are the worst of both worlds. Habituation destabilizes cooperation and stabilizes defection. Results from the two-person problem suggest that applications to multiplex and embedded relationships will yield unexpected insights into the global dynamics of cooperation in social dilemmas.

Agent-based modeling on technological innovation as an evolutionary process

Tieju Ma — 2005-12-20T10:20:30-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 741-755.

This paper describes a multi-agent model built to simulate the process of technological innovation, based on the widely accepted theory that technological innovation can be seen as an evolutionary process. The actors in the simulation include producers and a large number of consumers. Every producer will produce several types of products at each step. Each product is composed of several design parameters and several performance parameters (fitness components). Kauffman's famous NK model is used to deal with the mapping from a design parameter space (DPS) to a performance parameter space (PPS). In addition to the constructional selection, which can be illustrated by the NK model, we added environmental selection into the simulation and explored technological innovation as the result of the interaction between these two kinds of selection.

Agent-based modeling as organizational and public policy simulators

Robert Lempert — 2005-12-20T10:20:30-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7195-7196.

Agent-based models are an increasingly powerful tool for simulating social systems because they can represent important phenomenon difficult to capture in other mathematical formalisms. But, agent-based models have provided only limited support for policy-making because their distinctive abilities are often most useful in situations where the future is unpredictable. In such situations, the traditional analytic methods for applying simulation models to support decision-making are least effective. Fortunately, new analytic approaches for decision-making under conditions of deep uncertainty--emphasizing large ensembles of model-created scenarios and adaptive policies evaluated with the criteria of robustness, rather than with optimality or efficiency--can unleash the full potential of agent-based policy simulators.

Short-memory traders and their impact on group learning in financial markets

Blake Lebaron — 2005-12-20T10:20:30-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7201-7206.

This article highlights several issues from simulating agent-based financial markets. These all center around the issue of learning in a multiagent setting, and specifically the question of whether the trading behavior of short-memory agents could interfere with the learning process of the market as whole. It is shown in a simple example that short-memory traders persist in generating excess volatility and other features common to actual markets. Problems related to short-memory trader behavior can be eliminated by using several different methods. These are discussed along with their relevance to agent-based models in general.

Complexity and the Nervous System

Christof Koch — 2005-12-20T10:20:30-00:00

Science, Vol. 284, No. 5411. (1999), pp. 96-98.

Software agents and the route to the information economy

Jeffrey Kephart — 2005-12-20T10:20:30-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7207-7213.

Humans are on the verge of losing their status as the sole economic species on the planet. In private laboratories and in the Internet laboratory, researchers and developers are creating a variety of autonomous economically motivated software agents endowed with algorithms for maximizing profit or utility. Many economic software agents will function as miniature businesses, purchasing information inputs from other agents, combining and refining them into information goods and services, and selling them to humans or other agents. Their mutual interactions will form the information economy: a complex economic web of information goods and services that will adapt to the ever-changing needs of people and agents. The information economy will be the largest multiagent system ever conceived and an integral part of the world's economy. I discuss a possible route toward this vision, beginning with present-day Internet trends suggesting that agents will charge one another for information goods and services. Then, to establish that agents can be competent price setters, I describe some laboratory experiments pitting software bidding agents against human bidders. The agents' superior performance suggests they will be used on a broad scale, which in turn suggests that interactions among agents will become frequent and significant. How will this affect macroscopic economic behavior? I describe some interesting phenomena that my colleagues and I have observed in simulations of large populations of automated buyers and sellers, such as price war cycles. I conclude by discussing fundamental scientific challenges that remain to be addressed as we journey toward the information economy.

Overcoming design and development challenges in agent-based modeling using ASCAPE

Mario Inchiosa — 2005-12-20T10:20:30-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7304-7308.

The ASCAPE agent-based modeling environment greatly eases the task of designing and investigating agent-based models. However, effective design can still require a relatively deep knowledge of programming and agent-based modeling. This issue has almost certainly slowed the adoption of agent-based modeling approaches to social science problems. We will discuss how the ASCAPE software technology can mitigate this requirement and significantly benefit modelers regardless of programming ability.

Foundations of "new" social science: Institutional legitimacy from philosophy, complexity science, postmodernism, and agent-based modeling

Leslie Henrickson — 2005-12-20T10:20:30-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7288-7295.

Since the death of positivism in the 1970s, philosophers have turned their attention to scientific realism, evolutionary epistemology, and the Semantic Conception of Theories. Building on these trends, Campbellian Realism allows social scientists to accept real-world phenomena as criterion variables against which theories may be tested without denying the reality of individual interpretation and social construction. The Semantic Conception reduces the importance of axioms, but reaffirms the role of models and experiments. Philosophers now see models as "autonomous agents" that exert independent influence on the development of a science, in addition to theory and data. The inappropriate molding effects of math models on social behavior modeling are noted. Complexity science offers a "new" normal science epistemology focusing on order creation by self-organizing heterogeneous agents and agent-based models. The more responsible core of postmodernism builds on the idea that agents operate in a constantly changing web of interconnections among other agents. The connectionist agent-based models of complexity science draw on the same conception of social ontology as do postmodernists. These recent developments combine to provide foundations for a "new" social science centered on formal modeling not requiring the mathematical assumptions of agent homogeneity and equilibrium conditions. They give this "new" social science legitimacy in scientific circles that current social science approaches lack.

Meta-synthesis approach to complex system modeling

Jifa Gu — 2005-12-20T10:20:30-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 597-614.

Meta-synthesis method is proposed to tackle with open complex giant system problems which cannot be effectively solved by traditional reductionism methods by a Chinese system scientist Qian, Xuesen (Tsien HsueShen) around the early 1990s. The method emphasizes the synthesis of collected information and knowledge of various kinds of experts, and combining quantitative methods with qualitative knowledge. Since then, continuous endeavors have been taken to put those ideas into practice. In this paper, firstly we review meta-synthesis approach and other research relevant to complex system modeling briefly. Then we discuss two main issues, model integration and opinion synthesis, which are often confronted when applying meta-synthesis approach, together with an exhibit of the development of an embryonic meta-synthetic support prototype. Such a demonstration shows how to model complex problems, such as macro-economic problems in Hall for Workshop on Meta-Synthetic Engineering with versatile resources in information collection, model integration and opinion synthesis. Finally, some future work is indicated.

Simple Lessons from Complexity

Nigel Goldenfeld — 2005-12-20T10:20:30-00:00

Science, Vol. 284, No. 5411. (1999), pp. 87-89.

Platforms and methods for agent-based modeling

Nigel Gilbert — 2005-12-20T10:20:30-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7197-7198.

The range of tools designed to help build agent-based models is briefly reviewed. It is suggested that although progress has been made, there is much further design and development work to be done. Modelers have an important part to play, because the creation of tools and models using those tools proceed in a dialectical relationship.

Beyond Reductionism

Richard Gallagher — 2005-12-20T10:20:30-00:00

Science, Vol. 284, No. 5411. (1999)

Planning vehicle transhipment in a seaport automobile terminal using a multi-agent system

T Fischer — 2005-12-20T10:20:30-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 726-740.

A multi-agent system (MAS) for supporting the planning of transhipments of imported finished vehicles via a seaport is presented. The focus is on storage allocation, i.e. the allocation of parking areas for the temporary storage of vehicles, and on deployment scheduling, i.e. the allocation of drivers to the vehicles that have to be moved in the terminal area. These planning tasks, which in practice are usually carried out by different operators, are assigned to two different agent types. A further agent, the coordinator agent, is responsible for combining the local sub-plans into an overall plan in such a way that the demand for drivers in the planning period is minimised and balanced. The MAS is tested using randomly generated problem instances with different distributions of the manufacturer shares in the vehicle streams. The tests verify a certain robustness of the MAS with regard to changes in the problem data, in particular to the number of permanently employed drivers and the cost surcharge for hired drivers. In addition, the results highlight that the minimum overall (relative) costs of the drivers depends on the number of permanently employed drivers and on the level of the cost surcharge for hired drivers.

Simulation-based optimization of social security systems under uncertainty

Tatiana Ermolieva — 2005-12-20T10:20:30-00:00

European Journal of Operational Research, Vol. 166, No. 3. (2005), pp. 782-793.

This paper analyzes optimization-based approaches for a social security simulation model under demographic and economic uncertainties. The model is a compromise between a purely actuarial model and an overlapping generations general equilibrium model. It deals with production and consumption processes coevolving with "birth-and-death" processes of involved agents, e.g., region-specific households subdivided into single-year age groups, firms, governments, financial intermediaries, including pension systems and insurance. The production function of the model allows to track incomes expenditures, savings and dissavings of agents, as well as intergenerational and interregional transfers of wealth. The proposed approach combines the actuarial and the economic growth simulation models in a single stochastic optimization model which explicitly and realistically treats the underlying uncertainties with the goal to satisfy reasonable and secure consumption of agents. The design of optimal robust strategies is achieved by an adaptive simulation-based optimization procedure defined by non-smooth risk functions. Numerical solution is discussed.

Modeling civil violence: An agent-based computational approach

Joshua Epstein — 2005-12-20T10:20:30-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7243-7250.

This article presents an agent-based computational model of civil violence. Two variants of the civil violence model are presented. In the first a central authority seeks to suppress decentralized rebellion. In the second a central authority seeks to suppress communal violence between two warring ethnic groups. F2"> WIDTH=178 HEIGHT=200 SRC="/small/pq0920801002.gif" ALT=" "> View larger version (135K): F2">[in this window] F2" onClick="startTarget('F2', 542, 640); this.href='F2'" onMouseOver="window.status='View figure in a separate window'; return true" TARGET="F2">[in a new window] Fig. 2. Local outbursts. F13"> WIDTH=77 HEIGHT=200 SRC="/small/pq0920801013.gif" ALT=" "> View larger version (76K): F13">[in this window] F13" onClick="startTarget('F13', 319, 640); this.href='F13'" onMouseOver="window.status='View figure in a separate window'; return true" TARGET="F13">[in a new window] Fig. 13. Local ethnic cleansing to genocide.

Exploring cooperation and competition using agent-based modeling

Euel Elliott — 2005-12-20T10:20:30-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7193-7194.

Agent-based modeling enhances our capacity to model competitive and cooperative behaviors at both the individual and group levels of analysis. Models presented in these proceedings produce consistent results regarding the relative fragility of cooperative regimes among agents operating under diverse rules. These studies also show how competition and cooperation may generate change at both the group and societal level. Agent-based simulation of competitive and cooperative behaviors may reveal the greatest payoff to social science research of all agent-based modeling efforts because of the need to better understand the dynamics of these behaviors in an increasingly interconnected world.

Competition among cooperators: Altruism and reciprocity

Peter Danielson — 2005-12-20T10:20:30-00:00

PNAS, Vol. 99, No. 90003. (2002), pp. 7237-7242.

Levine argues that neither self-interest nor altruism explains experimental results in bargaining and public goods games. Subjects' preferences appear also to be sensitive to their opponents' perceived altruism. Sethi and Somanathan provide a general account of reciprocal preferences that survive under evolutionary pressure. Although a wide variety of reciprocal strategies pass this evolutionary test, Sethi and Somanthan conjecture that fewer are likely to survive when reciprocal strategies compete with each other. This paper develops evolutionary agent-based models to test their conjecture in cases where reciprocal preferences can differ in a variety of games. We confirm that reciprocity is necessary but not sufficient for optimal cooperation. We explore the theme of competition among reciprocal cooperators and display three interesting emergent organizations: racing to the "moral high ground," unstable cycles of preference change, and, when we implement reciprocal mechanisms, hierarchies resulting from exploiting fellow cooperators. If reciprocity is a basic mechanism facilitating cooperation, we can expect interaction that evolves around it to be complex, non-optimal, and resistant to change.