The Simulation Model Partitioning Problem: an Adaptive Solution Based on Self-Clustering (Extended Version)

This paper is about partitioning in parallel and distributed simulation. That means decomposing the simulation model into a numberof components and to properly allocate them on the execution units. An adaptive solution based on self-clustering, that considers both communication reduction and computational load-balancing, is proposed. The implementation of the proposed mechanism is tested using a simulation model that is challenging both in terms of structure and dynamicity. Various configurations of the simulation model and the execution environment have been considered. The obtained performance results are analyzed using a reference cost model. The results demonstrate that the proposed approach is promising and that it can reduce the simulation execution time in both parallel and distributed architectures

Programming agent-based demographic models with cross-state and message-exchange dependencies: A study with speculative PDES and automatic load-sharing

Agent-based modeling and simulation is a versatile and promising methodology to capture complex interactions among entities and their surrounding environment. A great advantage is its ability to model phenomena at a macro scale by exploiting simpler descriptions at a micro level. It has been proven effective in many fields, and it is rapidly becoming a de-facto standard in the study of population dynamics. In this article we study programmability and performance aspects of the last-generation ROOT-Sim speculative PDES environment for multi/many-core shared-memory architectures. ROOT-Sim transparently offers a programming model where interactions can be based on both explicit message passing and in-place state accesses. We introduce programming guidelines for systematic exploitation of these facilities in agent-based simulations, and we study the effects on performance of an innovative load-sharing policy targeting these types of dependencies. An experimental assessment with synthetic and real-world applications is provided, to assess the validity of our proposal

Agent-based Computing in Java

Agents are powerful, autonomous entities capable of performing simple, or vastly complex, operations individually or in groups of agent systems. Their capabilities extend significantly as mobile agents distributed across a network. Agent-based computing is a widely used technology with a broad range of applications, particularly in distributed computing and agent-based modeling. Many types of systems can be designed using the different architectures that define how they act, communicate, migrate, and more. This paper surveys agent-based computing, their architectures, and efforts at the standardization of certain aspects of the technology. It explores an existing framework called Jade through the lens of a demonstration based on the Sugarscape model, implemented using Jade’s library. Finally, it presents a new framework, called NOMAD, a simple barebones framework which comprises the most essential components needed for a mobile agent framework. With it, a user can quickly and more deeply understand the vital challenges agent systems must address, such as communication and code mobility, and the solutions needed to be implemented. They’ll be able to use the framework to extend its capabilities, create new components, and build powerful agent systems of their own

Big Data in MultiAgent Systems: Market Design Solutions

El objetivo principal de esta Tesis es presentar un conjunto de novedosos y diferentes métodos en los que los sistemas multiagente pueden jugar un papel clave en predicciones y modelos económicos en un amplio conjunto de contextos. La hipótesis principal es que los sistemas multiagente permiten la creación de modelos macroeconómicos con microfundamentos reales que son capaces de representar la economía en los diferentes niveles de acuerdo con diferentes propósitos y necesidades. La investigación se estructura en seis capítulos. El Capítulo 1 es una introducción teórica al resto de los capítulos que presentan aplicaciones empíricas. En él se compara los sistemas multiagente con dos alternativas: los modelos de equilibrio general computable y la econometría espacial. El resto de los capítulos son intencionadamente diferentes en sus objetivos y sus contenidos. Estas cinco aplicaciones incorporan diferentes tipos de agentes: incluyen individuos (2, 5, 6), familias (2, 5), empresas (3, 5, 6), establecimientos (5), instituciones financieras (6) y usuarios (4). En el ámbito espacial, la desagregación espacial es deliberadamente diferente en cada aplicación: El capítulo 4 no incluye el espacio, El capítulo 6 es una aplicación para la zona euro en su conjunto y en el capítulo 3 se toma España en su conjunto. Los capítulos 2 y 5 exploran las dos de las principales posibilidades para la incorporación del espacio en los sistemas multiagente: el capítulo 2 incluye las regiones NUTS 3 de la Unión Europea y en el capítulo 5 se geolocalizan los agentes. En el capítulo 2 se desarrolla un sistema multiagente que incluye a todos los individuos de la Unión Europea. Con este sistema podemos predecir la población a escala regional para toda la Unión Europea y cómo distintos niveles de crecimiento económico repercuten asimismo sobre el empleo. En el capítulo 3 se presenta un modelo de simulación con los principales puntos de vista de la teoría de negocios para estudiar el crecimiento empresarial y la demografía empresarial en un modelo evolutivo estocástico. El modelo que se presenta también muestra cómo las empresas se adaptan a los cambios en las características deseadas del producto y el efecto de la crisis sobre estas dinámicas. El capítulo 4 discute el papel clave de los incentivos en la seguridad de los sistemas de información. Trabajos anteriores realizan este estudio utilizando un enfoque de teoría de juegos, pero el capítulo muestra que un modelo basado en agentes es capaz de incluir la heterogeneidad y las interrelaciones entre los individuos, y no se centra en el equilibrio alcanzado sino en la dinámica antes de su aparición. El objetivo del capítulo 5 es el estudio de los efectos de la Ley para la Revitalización Comercial (Ley de Dinamización Comercial) que fue aprobada en la Comunidad de Madrid durante el año 2012. Por último, el objetivo del capítulo 6 es explicar los determinantes de la inflación y pronosticar la tasa de inflación en la zona euro en los próximos cinco años. Se predice una inflación para la zona euro creciente hasta 2018 con un límite cercano al 2,5% en tasa interanual siempre que no se produzcan perturbaciones externas relevantes

MAGDA: A Mobile Agent based Grid Architecture

Mobile agents mean both a technology and a programming paradigm. They allow for a flexible approach which can alleviate a number of issues present in distributed and Grid-based systems, by means of features such as migration, cloning, messaging and other provided mechanisms. In this paper we describe an architecture (MAGDA – Mobile Agent based Grid Architecture) we have designed and we are currently developing to support programming and execution of mobile agent based application upon Grid systems

Efficient Communication and Coordination for Large-Scale Multi-Agent Systems

The growth of the computational power of computers and the speed of networks has made large-scale multi-agent systems a promising technology. As the number of agents in a single application approaches thousands or millions, distributed computing has become a general paradigm in large-scale multi-agent systems to take the benefits of parallel computing. However, since these numerous agents are located on distributed computers and interact intensively with each other to achieve common goals, the agent communication cost significantly affects the performance of applications. Therefore, optimizing the agent communication cost on distributed systems could considerably reduce the runtime of multi-agent applications. Furthermore, because static multi-agent frameworks may not be suitable for all kinds of applications, and the communication patterns of agents may change during execution, multi-agent frameworks should adapt their services to support applications differently according to their dynamic characteristics. This thesis proposes three adaptive services at the agent framework level to reduce the agent communication and coordination cost of large-scale multi-agent applications. First, communication locality-aware agent distribution aims at minimizing inter-node communication by collocating heavily communicating agents on the same platform and maintaining agent group-based load sharing. Second, application agent-oriented middle agent services attempt to optimize agent interaction through middle agents by executing application agent-supported search algorithms on the middle agent address space. Third, message passing for mobile agents aims at reducing the time of message delivery to mobile agents using location caches or by extending the agent address scheme with location information. With these services, we have achieved very impressive experimental results in large- scale UAV simulations including up to 10,000 agents. Also, we have provided a formal definition of our framework and services with operational semantics

Dedale : Un environnement dédié aux problèmes multi-agents

We present Dedale, an environment for studying multi-agents coordination, learning and decision-making problems under realistic hypotheses. Dedale avoids the 8 fallacies of MAS in which all previous testbed fall and offers open, dynamic, asynchronous and partially observable environments. Highly parametrizable, Dedale allows to tackle either cooperative or competitive exploration, patrolling, pickup and delivery, trea-sure(s) or agent(s) hunt problems with teams from one to dozens of heterogeneous agents in discrete or continuous environments. The variety of modelable multi-agents problems associated with the possibility to create a peer-to-peer network of Dedale's environments makes us believe Dedale beeing able to become a unifying environment for both MAS research and teaching communities in their goal to work and evaluate their proposals under real-life hypotheses. Feedback from more than 150 early-users comfort us in this perspective

Load-Sharing Policies in Parallel Simulation of Agent-Based Demographic Models

Execution parallelism in agent-Based Simulation (ABS) allows to deal with complex/large-scale models. This raises the need for runtime environments able to fully exploit hardware parallelism, while jointly offering ABS-suited programming abstractions. In this paper, we target last-generation Parallel Discrete Event Simulation (PDES) platforms for multicore systems. We discuss a programming model to support both implicit (in-place access) and explicit (message passing) interactions across concurrent Logical Processes (LPs). We discuss different load-sharing policies combining event rate and implicit/explicit LPs’ interactions. We present a performance study conducted on a synthetic test case, representative of a class of agent-based models