Socionics: Sociological Concepts for Social Systems of Artificial (and Human) Agents

Socionics is an interdisciplinary approach with the objective to use sociological knowledge about the structures, mechanisms and processes of social interaction and social communication as a source of inspiration for the development of multi-agent systems, both for the purposes of engineering applications and of social theory construction and social simulation. The approach has been spelled out from 1998 on within the Socionics priority program funded by the German National research foundation. This special issue of the JASSS presents research results from five interdisciplinary projects of the Socionics program. The introduction gives an overview over the basic ideas of the Socionics approach and summarizes the work of these projects.Socionics, Sociology, Multi-Agent Systems, Artificial Social Systems, Hybrid Systems, Social Simulation

From Social Simulation to Integrative System Design

As the recent financial crisis showed, today there is a strong need to gain "ecological perspective" of all relevant interactions in socio-economic-techno-environmental systems. For this, we suggested to set-up a network of Centers for integrative systems design, which shall be able to run all potentially relevant scenarios, identify causality chains, explore feedback and cascading effects for a number of model variants, and determine the reliability of their implications (given the validity of the underlying models). They will be able to detect possible negative side effect of policy decisions, before they occur. The Centers belonging to this network of Integrative Systems Design Centers would be focused on a particular field, but they would be part of an attempt to eventually cover all relevant areas of society and economy and integrate them within a "Living Earth Simulator". The results of all research activities of such Centers would be turned into informative input for political Decision Arenas. For example, Crisis Observatories (for financial instabilities, shortages of resources, environmental change, conflict, spreading of diseases, etc.) would be connected with such Decision Arenas for the purpose of visualization, in order to make complex interdependencies understandable to scientists, decision-makers, and the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

Environmental analysis for application layer networks

Die zunehmende Vernetzung von Rechnern über das Internet lies die Vision von Application Layer Netzwerken aufkommen. Sie umfassen Overlay Netzwerke wie beispielsweise Peer-to-Peer Netzwerke und Grid Infrastrukturen unter Verwendung des TCP/IP Protokolls. Ihre gemeinsame Eigenschaft ist die redundante, verteilte Bereitstellung und der Zugang zu Daten-, Rechen- und Anwendungsdiensten, während sie die Heterogenität der Infrastruktur vor dem Nutzer verbergen. In dieser Arbeit werden die Anforderungen, die diese Netzwerke an ökonomische Allokationsmechanismen stellen, untersucht. Die Analyse erfolgt anhand eines Marktanalyseprozesses für einen zentralen Auktionsmechanismus und einen katallaktischen Markt. --Grid Computing

Smart Grid Technologies in Europe: An Overview

The old electricity network infrastructure has proven to be inadequate, with respect to modern challenges such as alternative energy sources, electricity demand and energy saving policies. Moreover, Information and Communication Technologies (ICT) seem to have reached an adequate level of reliability and flexibility in order to support a new concept of electricity network—the smart grid. In this work, we will analyse the state-of-the-art of smart grids, in their technical, management, security, and optimization aspects. We will also provide a brief overview of the regulatory aspects involved in the development of a smart grid, mainly from the viewpoint of the European Unio

The EnTrak system : supporting energy action planning via the Internet

Recent energy policy is designed to foster better energy efficiency and assist with the deployment of clean energy systems, especially those derived from renewable energy sources. To attain the envisaged targets will require action at all levels and effective collaboration between disparate groups (e.g. policy makers, developers, local authorities, energy managers, building designers, consumers etc) impacting on energy and environment. To support such actions and collaborations, an Internet-enabled energy information system called 'EnTrak' was developed. The aim was to provide decision-makers with information on energy demands, supplies and impacts by sector, time, fuel type and so on, in support of energy action plan formulation and enactment. This paper describes the system structure and capabilities of the EnTrak system

A theoretical and computational basis for CATNETS

The main content of this report is the identification and definition of market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. These build the theoretical foundation for the work within the following two years of the CATNETS project. --Grid Computing

Multi-agent systems for power engineering applications - part 1 : Concepts, approaches and technical challenges

This is the first part of a 2-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part 1 of the paper examines the potential value of MAS technology to the power industry. In terms of contribution, it describes fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications. As well as presenting a comprehensive review of the meaningful power engineering applications for which MAS are being investigated, it also defines the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part 2 of the paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented

A Multi-Agent System Simulation Model for Trusted Local Energy Markets

The energy market and electric grid play a major role in everyday life. Most areas in modern society, such as: communication, health, transportation, the financial system and many others; require electrical energy to operate properly. Traditionally energy grids operate in a centralized manner. Consumers are connected to centralized utilities in the grid and energy flows from producers to Consumers. However, the rising in popularity in Renewable Energy Sources (RES) such as photovoltaic panels installed in households, small commerce and small industry wide spread the use of distributed energy generation, which the main energy grid was not designed to support. One of the possible solutions for this problem is the creation of a Local Energy Market (LeM). A LeM is a market that operates in a small physical area such as a neighborhood. Traditional consumers can become active market participants under a LeM. That is possible because the LeM is structured in such a way as to enable small-scale negotiations and energy exchanges between participants, who traditionally would only be final consumers. The LeM is capable of dealing with distributed energy generation from RES because negotiations and distribution happen at a local level, thus reducing problems with the main grid. Furthermore, the participation in the local market can reduce energy costs or even create profits for consumers, while contributing to easy the management of the grid and associated technical losses. This work explores the concept of LeM and is focused on two main objectives: designing and developing a system that allows the simulation of LeM, and designing and developing a mechanism that allows trusted negotiations in this market. To accomplish these objectives a Multi-Agent System (MAS) architecture is proposed to model and allow the simulation of LeM. Furthermore to support the market it is also proposed a trust model used to evaluate the behavior of participants and detecting faulty or malicious activities. The developed MAS models a LeM based on a Smart Grid, that is an energy grid with a cyber-physical system with smart meters and communications mechanisms. The MAS was developed with agents to model sensors, market participants and a Market Interaction Manager (MIM) agent that is responsible for managing the negotiations and for applying trust mechanisms. The trust mechanism was designed to attribute a dynamic trust value to each participant, which is reviewed during the all negotiation period. This evaluation of the participant’s trust is based on the analysis of historical data, contextual data, such as weather conditions, and by using forecasting methods to predict the participant expected behavior, allowing to penalize the ones that are exhibiting a questionable behavior in the market. A case study simulation was made with the objective of understanding how the proposed trust mechanism performed, and how the use of different forecasting methods can interfere with it. The results obtained allowed us to conclude that the trust methodology is able to update the trust of each participant, during the negotiation period, and when paired with a well performing forecasting mechanism it is able to achieve a trusted evaluation of the participants behavior. Taking into consideration these results we believe that the proposed trust methodology is capable of providing a valuable trust assessment when used by the MIM agent. This Master Thesis is developed within the scope of a project called Secure interactions and trusted Participation in local Electricity Trading (SPET), a FCT-SAICT2017 funded Research & Development project. SPET project envisions the development of a MAS that is designed to model and simulate the operations of a LeM, taking a focus on security and market trust necessary in this negotiation environment.O mercado de energia e a rede elétrica desempenham um papel importante na vida quotidiana da população. Grande parte das áreas da sociedade moderna, como é o caso da comunicação, transportes, saúde, sistema financeiro, entre outras; requer energia elétrica para funcionar corretamente. Tradicionalmente, as redes de energia operam de forma centralizada. Os consumidores estão conectados a fornecedores centralizados na rede e a energia é transferida dos produtores para os consumidores. No entanto, o aumento da popularidade das Fontes de Energia Renováveis (FER), como painéis fotovoltaicos instalados nas residências, pequeno comércio e pequena indústria, difundiu o uso da geração distribuída de energia, que a rede principal de energia não foi projetada para suportar. Uma das possíveis soluções para esse problema é a criação de um Mercado Local de Energia (MLe). Um MLe é um mercado que opera numa pequena área física, como uma vizinhança. Num MLe, os consumidores tradicionais têm a possibilidade de ser participantes ativos no mercado. Isto é possível porque o MLe está estruturado de forma a permitir negociações em pequena escala e trocas de energia entre os participantes, que tradicionalmente seriam apenas consumidores finais. O MLe é capaz de lidar com a geração de energia distribuída proveniente das FER, porque as negociações e a distribuição ocorrem a um nível local, reduzindo assim os problemas com a rede principal. Para além disso, a participação no mercado local pode reduzir os custos de energia ou até gerar lucros para os consumidores, contribuindo ainda para facilitar a gestão da rede e reduzir as perdas técnicas a ela associadas. Este trabalho explora o conceito de MLe e está focado em dois objetivos principais: projetar e desenvolver um sistema que permita a simulação de MLe, bem como um mecanismo que permita negociações confiáveis neste mercado. Para atingir estes objetivos, é proposta uma arquitetura de Sistema Multi-Agente (SMA) para modelar e permitir a simulação do MLe. Para além disso, para apoiar o mercado, também é proposto um modelo de confiança utilizado para avaliar o comportamento dos participantes e detetar falhas ou atividades maliciosas. O SMA desenvolvido modela um MLe com base numa Smart Grid, que é uma rede de energia com um sistema ciber-físico, com sensores inteligentes e mecanismos de comunicação. O SMA foi desenvolvido com agentes para modelar sensores, participantes do mercado e um agente Market Interaction Manager (MIM), responsável pela gestão das negociações e pela aplicação de mecanismos de confiança. O mecanismo de confiança foi projetado para atribuir um valor de confiança dinâmico a cada participante, que é adaptado durante todo o período de negociação. Essa avaliação da confiança do participante é baseada na análise de dados históricos, contextuais, como condições climatéricas, e no uso de métodos de previsão para antever o comportamento esperado do participante, permitindo penalizar aqueles que exibem um comportamento questionável no mercado. Foi realizada uma simulação de caso de estudo, com o objetivo de avaliar o desempenho do mecanismo de confiança proposto e de que forma é que o uso de diferentes métodos de previsão interfere neste desempenho. Os resultados obtidos permitiram concluir que a metodologia de confiança é capaz de atualizar a confiança de cada participante, durante o período de negociação e, quando combinada com um mecanismo de previsão com bom desempenho, é capaz de obter uma avaliação confiável do comportamento dos participantes. Tendo em consideração estes resultados, acreditamos que a metodologia de confiança proposta é capaz de fornecer uma avaliação de confiança valiosa quando usada pelo agente MIM. Esta tese de mestrado é desenvolvida no âmbito de um projeto chamado Secure interactions and trusted Participation in local Electricity Trading (SPET), um projeto de Investigação e Desenvolvimento (I&D) financiado pela FCT-SAICT2017. O projeto SPET tem como objetivo o desenvolvimento de um MAS para a modelação e simulação de MLe, tendo como foco a segurança e confiança necessárias neste ambiente de negociação

The securities custody industry

Custody is, in essence, a service consisting in holding (and normally administering) securities on behalf of third parties. In step with the growth of sophisticated financial markets, custody has evolved into a complex industry no longer characterised by physical safekeeping but by a range of information and banking services. Given the multi-tier structure of the industry, custody services are provided by a variety of intermediaries. This paper describes the development of the custody industry and the structure of the custody services market. It also discusses the risks involved in custody and the challenges the industry is facing, particularly in the European context. JEL Classification: G15, G21, L22.Custody industry, securities settlement, systemic risk, custodian banks, global custodians.

A cell outage management framework for dense heterogeneous networks

In this paper, we present a novel cell outage management (COM) framework for heterogeneous networks with split control and data planes-a candidate architecture for meeting future capacity, quality-of-service, and energy efficiency demands. In such an architecture, the control and data functionalities are not necessarily handled by the same node. The control base stations (BSs) manage the transmission of control information and user equipment (UE) mobility, whereas the data BSs handle UE data. An implication of this split architecture is that an outage to a BS in one plane has to be compensated by other BSs in the same plane. Our COM framework addresses this challenge by incorporating two distinct cell outage detection (COD) algorithms to cope with the idiosyncrasies of both data and control planes. The COD algorithm for control cells leverages the relatively larger number of UEs in the control cell to gather large-scale minimization-of-drive-test report data and detects an outage by applying machine learning and anomaly detection techniques. To improve outage detection accuracy, we also investigate and compare the performance of two anomaly-detecting algorithms, i.e., k-nearest-neighbor- and local-outlier-factor-based anomaly detectors, within the control COD. On the other hand, for data cell COD, we propose a heuristic Grey-prediction-based approach, which can work with the small number of UE in the data cell, by exploiting the fact that the control BS manages UE-data BS connectivity and by receiving a periodic update of the received signal reference power statistic between the UEs and data BSs in its coverage. The detection accuracy of the heuristic data COD algorithm is further improved by exploiting the Fourier series of the residual error that is inherent to a Grey prediction model. Our COM framework integrates these two COD algorithms with a cell outage compensation (COC) algorithm that can be applied to both planes. Our COC solution utilizes an actor-critic-based reinforcement learning algorithm, which optimizes the capacity and coverage of the identified outage zone in a plane, by adjusting the antenna gain and transmission power of the surrounding BSs in that plane. The simulation results show that the proposed framework can detect both data and control cell outage and compensate for the detected outage in a reliable manner