Charles Macal

community which builds immersive training simulators for expensive equipment such as jet fighters. Visualization technologies have progressively increased in performance and lessened in price and are now becoming available to the remainder of the simulation community. Advances in computer hardware and software capabilities are making what was impractical 18 months ago into a desktop reality in terms of technical feasibility and cost. Visualization of simulations can range from the very complex-immersive, virtual worlds in which an individual interacts with a simulation model, mediated by a highly complex visual interface-to the relatively simple-in which the ongoing status or final output of a simulated process is rendered in the form of graphics, meters, or other aggregations of numerical data that are easier to understand and interpret. On the development side, visual approaches offer the possibility of constructing simulation models with objects that are rendered visually-for example, drag-and-drop. SIMULATION is soliciting original papers that represent the state-of the-art in closely linking simulation and visualization technologies. Sample topics include: ~ Integrated simulation and visualization systems and models that demonstrate state-of-the-art technical

I'd like to welcome you to the Agent 2004 conference. As most of you are aware, this conference is the fifth in a series of meetings that began in 1999. A conference followed the next year in 2000. The 2001 conference was skipped because of some conflicts with other conferences, and the conferences have proceeded annually since then. We have the proceedings of the previous conferences available here on CDs. One CD has the proceedings from 1999, 2000, and 2002; the other contains last year's proceedings. The purpose of these conferences is to advance the state of the computational social sciences and to integrate the social sciences with the decision sciences and something that is traditionally known as the management sciences. Those of you in the operations/research area are familiar with the traditional school of modeling simulation that emerged from that scientific area. This conference will bring together a different group of people to talk about the topic of agent-based theories and simulations. This fifth agent conference is one of a group of conferences held annually around the country. Most of you are probably aware of the CASOS Conference held at Carnegie Mellon University, usually in July. UCLA holds themore » Arrowhead Conference, generally around May. The University of Michigan is now holding a conference as well. Of course everyone is aware of SwarmFest, which has been held annually for about a decade. The Swarm seems to 'swarm' in different locations each year. As you're well aware, this conference is organized into a three-day program. This is the first time we've used three days for the full conference setting. Last year, we held simultaneous sessions, and that didn't work well for most of those who attended. We had complaints from people who missed sessions and papers because of scheduling, so we decided to extend this year's conference by one day. As a result, we now have a program designed to present the papers in a serial sequence rather than in a parallel manner. Today, we'll focus on toolkits. Tomorrow we'll look at computational social theory, and Saturday is application day. We'll talk about how we're taking some of the theories and toolkits to look at real-world problems in order to understand how our very complex world works and maybe even to predict how it might work in the future. In addition to the content of the papers themselves, one of the more important things about this conference is the discussion that is inspired by these papers. I invite you to ask penetrating questions, offer insightful comments, share your experiences with toolkits or your ideas on theories, and help to create an atmosphere that will help this field move along and grow. It's a fairly new science--it is just emerging--but it seems to have been gaining momentum in the last couple of years. This is a conference to get your energy going and perhaps foster your creativity. With that, I welcome you to Agent 2004; have a great time at the conference.« less

Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. ABMS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use electronic laboratories to support their research. Some have gone so far as to contend that ABMS 'is a third way of doing science,' in

The methodology described here projects use of purchased boiler fuel from 1980 to 2030 for six industrial groups. Three types of information were required to generate these projections: a long-term forecast of total industrial fossil fuel use, forecasts of industrial activity, and relative growth rates of industrial energy intensity. The resulting projections were used as inputs to the Industrial Combustion Emissions (ICE) model, one of the sector models of the National Acid Precipitation Assessment Program. In our projections, we used long-term forecasts of fossil fuel use from the 1985 National Energy Policy Plan (NEPP) prepared by the US Department of Energy (DOE). The NEPP provides projections of total industrial energy use from 1980 to 2010 for several fuel types and three economic growth scenarios (base, low, and high). To extend these projections to 2030, total energy use, electricity use, and renewable energy use were extrapolated. We constructed relative rates of growth for energy intensity in each industry group from historical data. Combining the three elements - fossil fuel use, industrial activity, and relative growth rate of energy intensity - yields a disaggregation of total purchased fossil fuel for each industry consistent with the NEPP forecast. Total fossil fuel use is then converted to boiler fuel use by applying some conversion factors constructed from 1980 census data and 1980 ICE model data. The results indicate negligible growth in boiler fuel use for most of the six industries represented in detail in the ICE model. Only the chemical industry has any significant growth in boiler fuel use in the base and high cases. This finding reflects the low growth in fossil fuel use projected by the NEPP, optimistic projections for the chemical industry by DRI, and significant conservation rates in the other industries.

Social and behavioral simulation is an emerging field at the intersection of computational social science and simulation modeling and analysis. Modeling how individual and heterogeneous agents “behave” by converting sensory inputs to decisions, emotions, or actions, is the essence of behavioral simulation. The essence of social simulation, analogously, is modeling how these agents “interact” with each other, and behave collectively as a group, as a function of their behavioral imperatives. When techniques from these two fields are combined, social and behavioral simulation connects individual behaviors at the micro-level to system-level behaviors at the macro-level, allowing the study of dynamic social behavior. This kind of modeling can lead to new insights into the causal mechanisms that underlie social systems. Until now, social and behavioral simulation has consisted largely of innovative applications of simulation to illustrate social or group behavior. More recently, the ability of agent-based modeling, system dynamics, network analysis, and associated techniques to study these micro-macro interactions is unparalleled. The field is ripe for methodological and theoretical advancements. This chapter describes the history of social and behavioral simulation from the perspective of the Winter Simulation Conference community, provides a thematic overview of the questions being addressed, and discusses possible future directions.

We describe an agent-based conceptual model of a Blockchain system. Blockchain technology enables distributed, encrypted and secure logging of digital transactions in an add-only ledger record. We model and simulate an expanding Blockchain network, describing the participating agents, the transactions, and the verified add-only public ledger record achieving decentralized consensus. All of the essential details of the functioning of the Blockchain including the behaviors and decisions made by agents deciding to join as well as participate in the market are detailed in the prototype model. The aim of this paper is to illustrate the essential elements and functioning of a Blockchain system, implement a generalized simulation and a measure of Blockchain efficiency from an agent choice and energy cost perspective. Our preliminary results indicate that mining choice (transaction block to verify) coupled with proof of work incentives are critical for energy efficiency.

Developed for use by Department of Defense deployment analysts to perform detailed Reception, Staging, Onward movement and Integration (RSO&I) analyses. ELIST requires: o Vehicle characteristics for ships, planes, trucks, railcars, buses, and helicopters. o Network (physical) characteristics defining the airport, seaport, road, rail, waterway and pipeline infrastructure available in a theater of operations. o Assets available for moving the personnel, equipment and supplies over the infrastructure network. o Movement requirements plan defining the deployment requirements of a military force. This includes defining each unit, its cargo (at various levels of resolution) , where it must move from and to, what modes it is required to travel by, and when it must be delivered through each phase of deployment.

Fifty-six summary sheets on energy-conserving industrial technologies were prepared. These summaries describe Office of Industrial Programs (OIP) energy-conservation and waste-recovery projects that have progressed to the point of potential industrial application. Possibilities for cross-industry applications are pointed out in many of the summary sheets. Each summary includes the following types of information: industrial application, process energy savings, conventional situation, new

PurposeThis paper is to describe development of the features and functions of Repast Simphony, the widely used, free, and open source agent-based modeling environment that builds on the Repast 3 library. Repast Simphony was designed from the ground up with a focus on well-factored abstractions. The resulting code has a modular architecture that allows individual components such as networks, logging, and time scheduling to be replaced as needed. The Repast family of agent-based modeling software has collectively been under continuous development for more than 10 years.MethodIncludes reviewing other free and open-source modeling libraries and environments as well as describing the architecture of Repast Simphony. The architectural description includes a discussion of the Simphony application framework, the core module, ReLogo, data collection, the geographical information system, visualization, freeze drying, and third party application integration.ResultsInclude a review of several R...

348 December 5-7, 1977 Charles Standrldge Purdue University Charles Macal Argonne Laboratory A. Alan B. Pritsker Purdue University & Prftsker & Associates Harry Delcher Emory College of Medicine Raymond Murray Michigan State University School of Medicine Page 2. ...

CHAPTER 17 MODEL VERIFICATION AND VALIDATION Dirk Brade and Axel Lehmann ABSTRACT With respect to the permanent increasing importance and complexity of modeling and simulation applied for the analysis, synthesis and for training of (technical) systems, model ...

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The Argentine Pampas, one of the main agricultural areas in the world, recently has undergone significant changes in land use and tenure and structural characteristics of agricultural production systems. Concerns about the environmental and societal impacts of the changes motivated development of an agent-based model (ABM) to explore recently observed patterns and plausible future evolution. The PM includes three main types of entities: the environment, the farm and the farmer. The model environment represents the northern part of Buenos Aires Province − the most productive sub-region of the Pampas that encompasses about 1,000,000 ha and has a long agricultural history. The environment contains farms of variable size defined during initialization. All farms are assumed to have the same soil and experience the same climate (represented by weather records from Pergamino, a location in the center of the region). The model involves one main type of agent: farmers who grow soybean, maize...

We present our development of load balancing algorithms to efficiently distribute and parallelize the running of large-scale complex agent-based modeling (ABM) simulators on High-Performance Computing (HPC) resources. Our algorithm is based on partitioning the co-location network that emerges from an ABM’s underlying synthetic population. Variations of this algorithm are experimentally applied to investigate algorithmic choices on two factors that affect run-time performance. We report these experiments’ results on the CityCOVID ABM, built to model the spread of COVID-19 in the Chicago metropolitan region.

Grand challenges are significant themes that can bring together researchers to bring significant change to a field. In 2012 a new initiative to restart the debate on major grand challenges for modeling and simula-tion (M&S) began. Leading researchers have presented M&S Grand Challenges in areas such as ubiqui-tous simulation, high performance computing, spatial simulation, big simulation, human behaviour, multi-domain design, systems engineering, cyber systems, network simulation and education. To contribute further to this initiative, this paper presents M&S Grand Challenges from an Operational Re-search/Management Science (OR/MS) perspective and discusses themes including simulation in healthcare, value of information, data modeling, stochastic modeling and optimization, agent-based simu-lation and simulation analytics. 1

Agent-based models (ABMs) integrate multiple scales of behavior and data to produce higher-order dynamic phenomena and are increasingly used in the study of cancer. However, the complexity of ABMs provides numerous challenges to their effective use, mostly related to the relatively high computational cost in carrying out the simulation experiments by which ABMs are developed, calibrated and used. Highperformance computing (HPC) platforms can address some of these computational constraints. We have developed a framework, called Extreme-scale Model Exploration with Swift/T (EMEWS), that can leverage the computing capabilities of HPC parallel architectures by integrating model exploration (ME) modules such as machine learning and evolutionary computing methods to augment the performance of large-scale simulation experiments. EMEWS can be used to aid in the calibration, parameter estimation and model exploration of any simulation-model. Herein we provide a use case examining the factors...

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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-toimplement concepts from neoclassical economics, but addresses drawbacks of this approach by being integrated into an agent-based 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, 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. Simulated LRP trajectories reproduced observed...