Sistemas multiagente colaborativos

Este proyecto examina el área de los sistemas multiagente colaborativos -- El proyecto describe seis simulaciones de sistemas multiagente -- Cada simulación representa un tipo de esquema de colaboración y comunicación diferente -- Los resultados de las simulaciones son analizados y comparados -- El proyecto también describe la implementación en hardware de un prototipo de sistema multiagente correspondiente a una de las simulaciones utilizando la plataforma Lego MindStorm

Інтелектуальні системи в промисловості і освіті

До збірника увійшли тези доповідей Третьої міжнародної науково-практичної конференції «ІСПО-2011» (2-4 листопада 2011 р., м. Суми), які висвітлюють стан та перспективи розвитку інтелектуальних технологій у різних галузях соціально-економічної сфери суспільства. Тези доповідей будуть корисними для студентів, аспірантів, науковців і фахівців, які займаються розроб-ленням та впровадженням інтелектуальних технологій При цитуванні документа, використовуйте посилання http://essuir.sumdu.edu.ua/handle/123456789/2522

Інтелектуальні системи в промисловості і освіті

До збірника увійшли тези доповідей Третьої міжнародної науково-практичної конференції «ІСПО-2011» (2-4 листопада 2011 р., м. Суми), які висвітлюють стан та перспективи розвитку інтелектуальних технологій у різних галузях соціально-економічної сфери суспільства. Тези доповідей будуть корисними для студентів, аспірантів, науковців і фахівців, які займаються розроб-ленням та впровадженням інтелектуальних технологій При цитуванні документа, використовуйте посилання http://essuir.sumdu.edu.ua/handle/123456789/2522

An agent-based simulation of wheat based ethanol plant location decisions for Saskatchewan

First generation ethanol production has experienced rapid expansion but is now at a crossroads facing impending industry transformation. While Saskatchewan’s ethanol industry has benefited from demand and policy instruments that have guided substantial growth in recent years, changing policy and market dynamics present new challenges which are compelling the industry to adjust. This thesis examines three factors that are suspected to influence ethanol plant locational decisions. The development of an agent-based simulation model in this thesis will ascertain how transportation networks, market synergies, and subsidization influence location stability for an ethanol plant. The long term interaction of these factors is unknown, therefore do tradeoffs exist between these factors or is it conditional for all to be present? Modeling factors that affect location stability through an agent-based approach creates a dynamic framework to understand how location attributes impact an ethanol agent’s longevity. It was found that location stability is affected by an ethanol agent’s distance to both primary transportation networks as well as product markets. Surprisingly, distance to DDGS (dried distillers grain with solubles) markets, a low value by-product of ethanol production, has a profound effect on location stability. Policy instruments and industry subsidization are considered key ethanol development drivers and the surge in ethanol industry growth brought hopes of rural revitalization. In Saskatchewan, policy was developed to support small ethanol plants, those 25 Mmly (million litres per year) or smaller, aimed at increasing farmer investment and alternative markets for wheat. Measuring the effect of subsidization on location stability was fundamental to understanding how a post subsidized ethanol industry may look. The research found that subsidization of Saskatchewan’s ethanol industry dramatically affected economies of scale and location decisions, which left ethanol agents unable to compete in an increasingly competitive ethanol industry

Analysis of the current state of water-­resource management in the UK using Social Network Analysis and Agent-­Based Modelling: a case study in the Wear Catchment, County Durham

Since the introduction of the Water Framework Directive in 2000, there has been a drive towards managing water resources at the catchment-­scale in the UK. The rationale for this approach is driven by intentions of localising environmental improvement, involving a wide range of stakeholders working in collaboration to identify water issues and potential actions to address them. However, despite this recognition, and drive towards collaborative working, there has been little focus on how the stakeholders actually come together in water-­resource management, for example: the role stakeholders play; what skills, expertise, and resources they contribute; and, how decisions are made in the collaboration. More specifically, there is an opportunity to conduct analysis and build understanding of the rules of collaboration behaviour, attitudes, activities and evolution directions. The overall aim of this research was to analyse the current state of water-resource management in the UK, focusing on cross-­boundary interactions between governmental and non-­governmental actors, specifically in the Wear Catchment, County Durham. To achieve this aim, a multi-­method approach was utilised, including social network analysis and agent-­based modelling, exploring the position and role of individual actors in the network, and how changes made to the network structure of stakeholders, could affect inter‑ and intra-­group collaborations. Ultimately, by analysing the current state of collaboration in water‑resource management, this research contributes to the wider understanding of progress made in terms of the management of water resources in the UK, including the strengths and potential flaws of the approach

Multi-Agent Modelling of Industrial Cyber-Physical Systems for IEC 61499 Based Distributed Intelligent Automation

Traditional industrial automation systems developed under IEC 61131-3 in centralized architectures are statically programmed with determined procedures to perform predefined tasks in structured environments. Major challenges are that these systems designed under traditional engineering techniques and running on legacy automation platforms are unable to automatically discover alternative solutions, flexibly coordinate reconfigurable modules, and actively deploy corresponding functions, to quickly respond to frequent changes and intelligently adapt to evolving requirements in dynamic environments. The core objective of this research is to explore the design of multi-layer automation architectures to enable real-time adaptation at the device level and run-time intelligence throughout the whole system under a well-integrated modelling framework. Central to this goal is the research on the integration of multi-agent modelling and IEC 61499 function block modelling to form a new automation infrastructure for industrial cyber-physical systems. Multi-agent modelling uses autonomous and cooperative agents to achieve run-time intelligence in system design and module reconfiguration. IEC 61499 function block modelling applies object-oriented and event-driven function blocks to realize real-time adaption of automation logic and control algorithms. In this thesis, the design focuses on a two-layer self-manageable architecture modelling: a) the high-level cyber module designed as multi-agent computing model consisting of Monitoring Agent, Analysis Agent, Self-Learning Agent, Planning Agent, Execution Agent, and Knowledge Agent; and b) the low-level physical module designed as agent-embedded IEC 61499 function block model with Self-Manageable Service Execution Agent, Self-Configuration Agent, Self-Healing Agent, Self-Optimization Agent, and Self-Protection Agent. The design results in a new computing module for high-level multi-agent based automation architectures and a new design pattern for low-level function block modelled control solutions. The architecture modelling framework is demonstrated through various tests on the multi-agent simulation model developed in the agent modelling environment NetLogo and the experimental testbed designed on the Jetson Nano and Raspberry Pi platforms. The performance evaluation of regular execution time and adaptation time in two typical conditions for systems designed under three different architectures are also analyzed. The results demonstrate the ability of the proposed architecture to respond to major challenges in Industry 4.0