A Communication Choreography for Discrete Step MultiAgent Social Simulations

Considerable research has been done on agent communications, yet in discrete step social agent simulations there is no standardized work done to facilitate reactive agent-to-agent communication. We propose an agent-to-agent interaction framework that preserves the integrity of the communication process in an artificial society in a \u27time-stepped\u27 discrete event simulator. We introduce the modeling language called Agent Choreography Description Language (ACDL) in order to model the communication. It serves in describing the common and collaborative observable behaviour of multiple agents that need to interact in a peer to peer manner to achieve some goal. ACDL further adopts the parallel and interaction activities to model proper communication in an artificial society. The ACDL communication framework is implemented and tested in REPAST. It employs a communication manager to generate and execute ACDL specification according to agent\u27s communication needs

Simulation techniques in an artificial society model

Artificial society refers to a generic class of agent-based simulation models used to discover global social structures and collective behavior produced by simple local rules and interaction mechanisms. Artificial society models are applicable in a variety of disciplines, including the modeling of chemical and biological processes, natural phenomena, and complex adaptive systems. We focus on the underlying simulation techniques used in artificial society discrete-event simulation models, including model time evolution and computational performance.;Although for some applications synchronous time evolution is the correct modeling approach, many other applications are better represented using asynchronous time evolution. We claim that asynchronous time evolution can eliminate potential simulation artifacts produced using synchronous time evolution. Using an adaptation of a popular artificial society model, we show that very different output can result based solely on the choice of asynchronous or synchronous time evolution. Based on the event list implementation chosen, the use of discrete-event simulation to incorporate asynchronous time evolution can incur a substantial loss in computational performance. Accordingly, we evaluate select event list implementations within the artificial society simulation model and demonstrate that acceptable performance can be achieved.;In addition to the artificial society model, we show that transforming from a synchronous to an asynchronous system proves beneficial for scheduling resources in a parallel system. We focus on non-FCFS job scheduling policies that permit jobs to backfill, i.e., to move ahead in the queue, given that they do not delay certain previously submitted jobs. Instead of using a single queue of jobs, we propose a simple yet effective backfilling scheduling policy that effectively separates short from long jobs by incorporating multiple queues. By monitoring system performance, our policy adapts its configuration parameters in response to severe changes in the job arrival pattern and/or resource demands. Detailed performance comparisons via simulation using actual parallel workload traces indicate that our proposed policy consistently outperforms traditional backfilling in a variety of contexts

Conception et évaluation d'un prototype de simulation de la morphogenèse urbaine par agents vecteurs multi-échelles

The research work of this PhD thesis was carried out in the context of an interdisciplinary project related to the study of urban morphogenesis. A team composed of architects and engineers specialized in GIS technologies have worked together in this project during three years, sharing their knowledge in order to understand and simulate the evolution of the urban environment of cities. The fundamental hypothesis that conducted this research is that the city can be seen as a self-organizing system governed by a set of morphogenesis rules, which can for example, determine the location of new architectural programs and induce the city's organization, from local to global scales. Architectural programs themselves are supposed to determine city's development. In this PhD thesis a simulation prototype of the urban growth based on the use of multi-agents systems was carried out. This prototype is a computer tool that allows the analysis and representation of the growth of the built environment. Nowadays, the ability to understand and simulate urban evolution proves to be essential in order to control the evolution of a city in a sustainable development view. Furthermore, this tool should facilitate the understanding and decision-making of those concerned with problems related to urban development. The urban system has been modeled as a set of space objects, such as buildings and networks, which interact between themselves. These interactions are carried out at different levels, from local to global scales, being controlled by behavioral rules or laws of growth. The result of their interaction can be figures or emergent phenomena represented at several scales. The approach using multi-agents vector systems was chosen in order to model a geographical complex system like a city, which integrates a vectorial modeling of space. Hence, each spatial agent does not possess a limit of form and size. The interest of using multi-agents vector systems also lies in their ability to manage various models of individuals, from simple entities to more complex ones. Thus, various levels of representation, such as individuals and groups of individuals, can be managed, which is not easily feasible, for example, with cellular agents. The development platform used is GeOxygene (Java computer programming language), which is an open-source platform developed at IGN (Institut Géographique National, France), by COGIT laboratory. This platform provides several GIS functions, allowing the development and implementation of the prototype here presented. An interaction model between agents was defined and the type of scenarios of each of these interactions was detailed. A set of methods and associated classes was developed. Agent's architecture was conceived in order to allow manipulation (sending, receiving and treatment) of exchanged messages. In order to show the relevance of the multi-agent multi-scale methodology, examples of buildings creation in a case study zone were carried out. Using the multi-scale vector simulation prototype here presented, the development of cities can be computed in a very innovative way. However, the developed prototype still lacks some accuracy, mostly due to the fact that the specified laws adopted for simulation do not reflect the whole reality, which is obviously much more complex to traduce. We have not yet validated the model for other cities – nevertheless, the model could already be used as a decision support tool, particularly as a planning support instrument for architects and urban planners. With regards to future work this prototype shall be integrated in a global approach of urban simulation, allowing the analysis of environmental risks, demographic and economic growth and transports simulation at different scales of analysis and 2D/3D visualization output, such as district and city

Asynchronous Time Evolution in an Artificial Society Model

"Artificial society" refers to an agent-based simulation model used to discover global social structures and collective behavior produced by simple local rules and interaction mechanisms. In most artificial society discrete-event simulation models, synchronous time evolution is used to drive the actions and interactions of the landscape and agents. Although for some applications synchronous time evolution is the correct modeling approach, other applications are better suited for asynchronous time evolution. In this paper we demonstrate that very different behavior can be observed in a typical artificial society model if agent events occur asynchronously. Using an adaptation of the artificial society model defined by Epstein and Axtell, we describe the implementation of asynchronous time evolution in a discrete-event simulation model. With output from this model, we show that the use of asynchronous time evolution can eliminate potential simulation artifacts produced using synchronous time evolution. Since the use of discrete-event simulation can produce an associated loss in computational performance, we also discuss means of improving the performance of the artificial society simulation model. We provide results demonstrating that acceptable computational performance for asynchronous time evolution can be achieved using an appropriate event list implementation.Artificial Society, Discrete-Event Simulation, Synchronous Time Evolution, Simulation Artifacts, Asynchronous Time Evolution, Next-Event Simulation, Event List Processing