A Modeler-Friendly API for ABM Partitioning

2009 ◽  
Author(s):  
La´szlo´ Gulya´s ◽  
Ga´bor Szemes ◽  
George Kampis ◽  
Walter de Back
Keyword(s):  
Agent Based Modeling ◽  
Emergent Behavior ◽  
System Level ◽  
Acceptable Solution ◽  
Agent Based ◽  
Java Language ◽  
Interacting Agents ◽  
Communication Topology ◽  
Performance Results ◽  
Domain Independent

Agent Based Modeling (ABM) is a popular technique for dealing with complex systems. An ABM usually consists of many autonomous, interacting agents, and modelers are interested in the system-level, emergent behavior of these agents. In developing an ABM, scalability is one of most critical factors for validation. Looking for an acceptable solution, parallelization often comes into play. However, writing a parallel version of an ABM simulation is at least as hard as developing the original model, and usually takes an expert of the area. This paper demonstrates our ongoing developments based on the idea that ABMs can be classified on the basis of their interior communication topology. We have developed six reusable parallel simulation schemas that can be instantiated with simulation-specific code using the Java language. Our aim was to give general, domain independent support for ABM modelers, where the parallel piece of code is completely transparent. The hope is that ABM modelers can treat their parallel system in almost the same way as they do the original. The paper details our approach as well as the implementation and, towards the end, shows performance results and how one of the templates works in a GRID system.

Agent-Based Modeling the Emergent Behavior of A System-of-Systems

2009 ◽  
Vol 19 (1) ◽  
pp. 1581-1590 ◽  
Author(s):  
John C. Hsu ◽  
John R. Clymer ◽  
Jose Garcia ◽  
Efrain Gonzalez
Keyword(s):  
System Of Systems ◽  
Agent Based Modeling ◽  
Emergent Behavior ◽  
Agent Based

scholarly journals Agent-based modeling and simulation of emergent behavior in air transportation

2013 ◽  
Vol 1 (1) ◽  
Author(s):  
Soufiane Bouarfa ◽  
Henk AP Blom ◽  
Richard Curran ◽  
Mariken HC Everdij
Keyword(s):  
Modeling And Simulation ◽  
Air Transportation ◽  
Agent Based Modeling ◽  
Emergent Behavior ◽  
Agent Based

scholarly journals UNDERSTANDING THE EFFECT OF CO-WORKER SUPPORT ON CONSTRUCTION SAFETY PERFORMANCE FROM THE PERSPECTIVE OF RISK THEORY: AN AGENT-BASED MODELING APPROACH

2019 ◽  
Vol 25 (2) ◽  
pp. 132-144 ◽  
Author(s):  
Tingting Ji ◽  
Hsi-Hsien Wei ◽  
Jiayu Chen
Keyword(s):  
Construction Safety ◽  
Agent Based Modeling ◽  
Safety Performance ◽  
Worker Safety ◽  
Risk Theory ◽  
System Level ◽  
Agent Based ◽  
Hazardous Area ◽  
Worker Support

Co-worker safety support has been given prominence in manufacturing and transportation field for its positive effect on individual workers’ safety; however, there is little evidence to show if such supporting role of co-workers is significant in improving project-level safety performance in construction workplace. This study adopts agent-based modeling (ABM) to understand the effectiveness of two distinct co-worker-safety-support actions on the safety performance of a construction project. Based on the risk theory, the ABM model simulates a construction site where worker agents reinforce steel bars with the likelihood of suffering crane-related incidents. The results indicate that both co-worker-support actions can significantly reduce the occurrence of nonfatal incidents but shows little influence in fatal incidents, and in reducing high-severity incidents, the action of warning peers to leave the hazardous area has the same effectiveness as reminding peers to wear Personal Protective Equipment. The present study provides a fresh insight into the safety-related role of co-workers: not only reveals how the local-level effects of co-workers’ safety assistance emerge the system-level consequences, but demonstrates the effectiveness of specific peer-support actions on three levels of construction safety performance, and thereby extends our existing body of knowledge on co-worker safety support in the construction field.

Emergent Behavior in a Population of Thermostatically Controlled Loads With Peer-to-Peer Communication

2019 ◽  
Author(s):  
Ryan Schwartz ◽  
John F. Gardner
Keyword(s):  
Demand Response ◽  
Air Conditioning ◽  
Large Scale ◽  
Large Population ◽  
Agent Based Modeling ◽  
Emergent Behavior ◽  
Peer Communication ◽  
Agent Based ◽  
Thermostatically Controlled Loads ◽  
Residential Air Conditioning

Abstract Thermostatically controlled loads (TCLs) are often considered as a possible resource for demand response (DR) events. However, it is well understood that coordinated control of a large population of previously un-coordinated TCLs may result in load synchronization that results in higher peaks and large uncontrolled swings in aggregate load. In this paper we use agent based modeling to simulate a number of residential air conditioning loads and allow each to communicate a limited amount of information with their nearest neighbors. As a result, we document emergent behavior of this large scale, distributed and nonlinear system. Using the techniques described here, the population of TCLs experienced up to a 30% reduction in peak demand following the DR event. This behavior is shown to be beneficial to the goals of balancing the grid and integrating increasing penetration of variable generators.

Spatial Units as Agents: Making the Landscape an Equal Player in Agent-Based Simulations

2002 ◽  
Author(s):  
Paul Box
Keyword(s):  
Cell Structure ◽  
Natural Extension ◽  
Data Gathering ◽  
Agent Based Modeling ◽  
Emergent Behavior ◽  
Modeling Tools ◽  
Bottom Up ◽  
Agent Based ◽  
Landscape Processes ◽  
Dynamic Landscape

Agent-based modeling has generated considerable interest in recent years as a tool for exploring many of the processes that can be modeled as bottom up processes. This has accelerated with the availability of software packages, such as Swarm and StarLogo, that allow for relatively complex simulations to be constructed by researchers with limited computer-programming backgrounds. A typical use of agent-based models is to simulate scenarios where large numbers of individuals are inhabiting a landscape, interacting with their landscape and each other by relatively simple rules, and observing the emergent behavior of the system (population) over time. It has been a natural extension in this sort of a study to create a landscape from a “real world” example, typically imported through a geographic information system (GIS). In most cases, the landscape is represented either as a static object, or a “stage” upon which the agents act (see Briggs et al. , Girnblett et al., and Remm). In some cases, an approximation of a dynamic landscape has been added to the simulation in a way that is completely exogenous to the population being simulated; the dynamic conditions are read from historical records, in effect “playing a tape” of conditions, to which the population reacts through time (such as Dean et al. and Kohler et al. ). There has also been many simulations where dynamic landscape processes have been modeled through “bottom up” processes, where localized processes in landscapes are simulated, and the global emergent processes are observed. Topmodel is a Fortran-based implementation of this concept for hydrologic processes; and PCRaster has used similar software constructs to simulate a variety of landscape processes, with sophisticated visualization and data-gathering tools. In both of these examples, the landscape is represented as a regular lattice or cell structure. There are also many examples of “home grown” tools (simulations created for a specific project), applying cellular automata (CA) rules to landscapes to simulate urban growth, wildfire , lava flows, and groundwater flow. There are also examples of how agent-based modeling tools were employed to model dynamic landscape processes such as forest dynamics, i.e., Arborgames. In these models the landscape was the object of the simulation, and free-roaming agents were not considered as part of the model.

Book Reviews

2017 ◽  
Vol 55 (2) ◽  
pp. 644-647
Keyword(s):  
Agent Based Modeling ◽  
Agent Based Models ◽  
Agent Based ◽  
Practical Guide ◽  
Interacting Agents ◽  
Hamilton College ◽  
Heterogeneous Interacting Agents

Christophre Georges of the Department of Economics, Hamilton College reviews “Economics with Heterogeneous Interacting Agents: A Practical Guide to Agent-Based Modeling,” edited by Alessandro Caiani, Alberto Russo, Antonio Palestrini, and Mauro Gallegati. The Econlit abstract for this book begins: “Text for graduate and PhD students, as well as undergraduates with some knowledge of computers and economics comprises four papers emerging from a workshop on agent-based modeling held by the Dipartimento di Scienze Economiche e Sociali at the Università Politecnica delle Marche. Presents a guide to agent-based models (ABM) and the technicalities that need to be solved in order to evaluate the effect of different rules and their switching.”

Multi-Agent Based Modeling Simulation about VANET

2013 ◽  
Vol 760-762 ◽  
pp. 680-684
Author(s):  
Shan Shan Wan ◽  
Dong Liang Wang ◽  
Qing Cao
Keyword(s):  
Ad Hoc Network ◽  
Ad Hoc ◽  
Agent Based Modeling ◽  
Emergent Behavior ◽  
Self Organization ◽  
Working Mechanism ◽  
Agent Based ◽  
Modeling Simulation ◽  
Large Numbers ◽  
Multi Agent

The self-organization characteristics and the interaction between a large numbers of self-organizing vehicles are complexity, to obtain a more accurate model of vehicular Ad-hoc network (VANET) and obtain a more profound comprehension of the complex behavior working mechanism of the vehicle in the VANET environment multi-agent based and bottom-up modeling approach is proposed here. It aims to describe the dynamics of VANET caused by the different behaviors of vehicular. The simulation tool for vehicular misbehaviors is developed with multi-agent. It aims to and be able to effectively reproduce the real VANET scene. Though the multi-agent based modeling the emergent behavior and sudden existing behaviors of VANET entities are well reflected.

scholarly journals Enabling the Analysis of Emergent Behavior in Future Electrical Distribution Systems Using Agent-Based Modeling and Simulation

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Sonja Kolen ◽  
Stefan Dähling ◽  
Timo Isermann ◽  
Antonello Monti
Keyword(s):  
Modeling And Simulation ◽  
Distribution Systems ◽  
Large Scale ◽  
Agent Based Modeling ◽  
Emergent Behavior ◽  
System Control ◽  
Distribution Grid ◽  
Agent Based ◽  
Electrical Distribution Systems ◽  
Electrical Distribution

In future electrical distribution systems, component heterogeneity and their cyber-physical interactions through electrical lines and communication lead to emergent system behavior. As the distribution systems represent the largest part of an energy system with respect to the number of nodes and components, large-scale studies of their emergent behavior are vital for the development of decentralized control strategies. This paper presents and evaluates DistAIX, a novel agent-based modeling and simulation tool to conduct such studies. The major novelty is a parallelization of the entire model—including the power system, communication system, control, and all interactions—using processes instead of threads. Thereby, a distribution of the simulation to multiple computing nodes with a distributed memory architecture becomes possible. This makes DistAIX scalable and allows the inclusion of as many processing units in the simulation as desired. The scalability of DistAIX is demonstrated by simulations of large-scale scenarios. Additionally, the capability of observing emergent behavior is demonstrated for an exemplary distribution grid with a large number of interacting components.

Agent-Based Modeling of Automobile Producer and Consumer Behavior to Support Design for Market Systems Analysis

2017 ◽  
Author(s):  
Amineh Zadbood ◽  
Steven Hoffenson
Keyword(s):  
Systems Analysis ◽  
Agent Based Modeling ◽  
Emergent Behavior ◽  
Purchasing Decisions ◽  
Support Design ◽  
Agent Based ◽  
Regulatory Strategies ◽  
Design Attributes ◽  
Design For Market Systems ◽  
Future Work

Improving design for market systems analysis relies on understanding the motivations and interactions among producers and consumers. Producers should theoretically develop their strategies for designing new products based on consumer demand and the expected profits from their sales. In this study, an agent-based modeling approach is proposed to simulate consumer and producer behavior for use in market systems analysis, and it is demonstrated through a simplified automobile market. In the model, consumers make heterogeneous purchasing decisions based on product attributes, which provides the producers with insights into their preferences and how to improve upon these design attributes over time. Emergent behavior of the model shows that analyzing the behavior of consumers provides the opportunity for producers to compete which one another with different strategies to improve their designs by investing in technology improvements. This lays the foundation for future work that can model how different business and regulatory strategies, social structures, and policies influence consumer and producer behavior, which in turn influences economic, environmental, and social impacts.

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