Organization of Multi-Agent Systems: An Overview

In complex, open, and heterogeneous environments, agents must be able to reorganize towards the most appropriate organizations to adapt unpredictable environment changes within Multi-Agent Systems (MAS). Types of reorganization can be seen from two different levels. The individual agents level (micro-level) in which an agent changes its behaviors and interactions with other agents to adapt its local environment. And the organizational level (macro-level) in which the whole system changes it structure by adding or removing agents. This chapter is dedicated to overview different aspects of what is called MAS Organization including its motivations, paradigms, models, and techniques adopted for statically or dynamically organizing agents in MAS.Comment: 12 page

A framework for proving the self-organization of dynamic systems

This paper aims at providing a rigorous definition of self- organization, one of the most desired properties for dynamic systems (e.g., peer-to-peer systems, sensor networks, cooperative robotics, or ad-hoc networks). We characterize different classes of self-organization through liveness and safety properties that both capture information re- garding the system entropy. We illustrate these classes through study cases. The first ones are two representative P2P overlays (CAN and Pas- try) and the others are specific implementations of \Omega (the leader oracle) and one-shot query abstractions for dynamic settings. Our study aims at understanding the limits and respective power of existing self-organized protocols and lays the basis of designing robust algorithm for dynamic systems

Resilient Bioinspired Algorithms: A Computer System Design Perspective

This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution is published in Cotta, C., Olague, G. (2022). Resilient Bioinspired Algorithms: A Computer System Design Perspective. In: Jiménez Laredo, J.L., Hidalgo, J.I., Babaagba, K.O. (eds) Applications of Evolutionary Computation. EvoApplications 2022. Lecture Notes in Computer Science, vol 13224. Springer, Cham. https://doi.org/10.1007/978-3-031-02462-7_39Resilience can be defined as a system's capability for returning to normal operation after having suffered a disruption. This notion is of the foremost interest in many areas, in particular engineering. We argue in this position paper that is is a crucial property for bioinspired optimization algorithms as well. Following a computer system perspective, we correlate some of the defining requirements for attaining resilient systems to issues, features, and mechanisms of these techniques. It is shown that bioinspired algorithms do not only exhibit a notorious built-in resilience, but that their plasticity also allows accommodating components that may boost it in different ways. We also provide some relevant research directions in this area.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Methodological Guidelines for Engineering Self-organization and Emergence

The ASCENS project deals with the design and development of complex self-adaptive systems, where self-organization is one of the possible means by which to achieve self-adaptation. However, to support the development of self-organising systems, one has to extensively re-situate their engineering from a software architectures and requirements point of view. In particular, in this chapter, we highlight the importance of the decomposition in components to go from the problem to the engineered solution. This leads us to explain and rationalise the following architectural strategy: designing by following the problem organisation. We discuss architectural advantages for development and documentation, and its coherence with existing methodological approaches to self-organisation, and we illustrate the approach with an example on the area of swarm robotics

Comparison of approaches for developing self-adaptive systems

The engineering of software systems enables developers to create very powerful, complex and highly customized software systems by utilizing newest technical capabilities. However, these systems often are error-prone, inflexible, non-reusable and expensive to maintain. Self-adaptation attends to these challenges, offering new ways to automate the adjustment of a system's structure and state. For that reason, many software development approaches specifically consider self-adaptability, leading to a high diversity of methodologies with different characteristics and areas of application. This work addresses this issue by presenting a taxonomy for the analysis and comparison of different approaches for developing self-adaptive systems. In addition, different sample approaches are presented, demonstrating how these dimensions can be applied to compare and classify related work

Increasing the Resilience of Cyber Physical Systems in Smart Grid Environments using Dynamic Cells

Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown

LA COMPUTACIÓN COGNOSCITIVA – EL MUNDO DE LA CONCIENCIA

Cognitive computer science has been presented as a transdisciplinary investigation of cognitive and information science that investigates the processing and internal information mechanism along with brain processes and natural intelligence and its engineering applications. In this work we attempt to provide an enlightening perspective on the past, present and future of cognitive computing, analysing the development of computer science from the classical information theory, contemporary computing, and cognitive computing which is a deep interdisciplinary research that addresses the problems from modern common root computing, computing, software engineering, such as the future generation computer architecture known as cognitive computers of human memory. The goal of autonomous computing is to create computing systems capable of managing to a much greater extent than the current one. This paper presents Unity, a decentralized architecture for autonomous computing based on multiple interacting agents called autonomous elements. We illustrate how the unit architecture performs various desired behaviours of the autonomous system, including goal-oriented self-healing, self-healing, and real-time self-optimization. These elements are important for your comprehension and treatment in the process of computer engineer in, as well as in the area of Electronics and Telecommunications.  La informática cognitiva se ha presentado como una investigación transdisciplinaria de la ciencia cognitiva y de la información que investiga el mecanismo de procesamiento e información interna junto con los procesos cerebrales y la inteligencia natural y sus aplicaciones de ingeniería. En este trabajo intentamos proporcionar una perspectiva esclarecedora sobre el pasado, el presente y el futuro de la informática cognitiva, analizando el desarrollo de la informática a partir de la teoría de la información clásica, la informática contemporánea y la informática cognitiva, que es una investigación interdisciplinaria profunda que aborda los problemas desde informática raíz común moderna, informática, ingeniería de software, como la arquitectura informática de la generación futura conocida como computadoras cognitivas de la memoria humana. El objetivo de la informática autónoma es crear sistemas informáticos capaces de gestionar en mayor medida que el actual. Este artículo presenta Unity, una arquitectura descentralizada para computación autónoma basada en múltiples agentes interactivos llamados elementos autónomos. Ilustramos cómo la arquitectura de la unidad realiza varios comportamientos deseados del sistema autónomo, incluida la autocuración orientada a objetivos, la autocuración y la autooptimización en tiempo real. Estos elementos son importantes para su comprensión y tratamiento en el proceso de ingeniería informática, así como en el área de Electrónica y Telecomunicaciones

Algorithms for self-healing networks

Many modern networks are reconfigurable, in the sense that the topology of the network can be changed by the nodes in the network. For example, peer-to-peer, wireless and ad-hoc networks are reconfigurable. More generally, many social networks, such as a company\u27s organizational chart; infrastructure networks, such as an airline\u27s transportation network; and biological networks, such as the human brain, are also reconfigurable. Modern reconfigurable networks have a complexity unprecedented in the history of engineering, resembling more a dynamic and evolving living animal rather than a structure of steel designed from a blueprint. Unfortunately, our mathematical and algorithmic tools have not yet developed enough to handle this complexity and fully exploit the flexibility of these networks. We believe that it is no longer possible to build networks that are scalable and never have node failures. Instead, these networks should be able to admit small, and, maybe, periodic failures and still recover like skin heals from a cut. This process, where the network can recover itself by maintaining key invariants in response to attack by a powerful adversary is what we call self-healing. Here, we present several fast and provably good distributed algorithms for self-healing in reconfigurable dynamic networks. Each of these algorithms have different properties, a different set of gaurantees and limitations. We also discuss future directions and theoretical questions we would like to answer