Sven Tomforde, J. Hähner, S. Mammen, Christian Gruhl, B. Sick, K. Geihs
In many application domains, developers aim at building technical systems that can cope with the complexity of the world they are surrounded with, including other technical systems. Due to this complexity, system designers cannot explicitly foresee every possible situation "their" system will be confronted with at runtime. This resulted in solutions capable of self-adaptation at runtime. Future intelligent technical systems will have to go far beyond such a reactive solution - the general question is: How can systems themselves define new goals and new classes of goals in order to increase their own performance at runtime and without the need of human control or supervision? This paper introduces a definition of "computational self-reflection", proposes an architectural concept, and discusses the potential benefit by means of three exemplary application scenarios. Finally, building blocks to achieve self-reflection are discussed and a basic research agenda is drafted.
{"title":"\"Know Thyself\" - Computational Self-Reflection in Intelligent Technical Systems","authors":"Sven Tomforde, J. Hähner, S. Mammen, Christian Gruhl, B. Sick, K. Geihs","doi":"10.1109/SASOW.2014.25","DOIUrl":"https://doi.org/10.1109/SASOW.2014.25","url":null,"abstract":"In many application domains, developers aim at building technical systems that can cope with the complexity of the world they are surrounded with, including other technical systems. Due to this complexity, system designers cannot explicitly foresee every possible situation \"their\" system will be confronted with at runtime. This resulted in solutions capable of self-adaptation at runtime. Future intelligent technical systems will have to go far beyond such a reactive solution - the general question is: How can systems themselves define new goals and new classes of goals in order to increase their own performance at runtime and without the need of human control or supervision? This paper introduces a definition of \"computational self-reflection\", proposes an architectural concept, and discusses the potential benefit by means of three exemplary application scenarios. Finally, building blocks to achieve self-reflection are discussed and a basic research agenda is drafted.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"50 1","pages":"150-159"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83677336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The study of complex networks and collective dynamics occurring in biological, social and technical systems has experienced a massive surge of interest both from academia and industry. Many of the results on the mechanisms underlying the self-organized formation of complex dynamic networks in natural and man-made systems have been derived based on a statistical physics perspective. In this tutorial, we provide a basic introduction to this perspective which will help attendees to benefit from the vast literature on self-organization and self-adaptation phenomena available in the fields of network science and complex systems. We cover basic models and abstractions for the study of static complex networks as well as dynamical processes like, e.g., information diffusion, random walks, synchronization or the propagation of cascading failures. We further introduce recent advances in the study of dynamic (social) networks and demonstrate how the resulting methods can be practically applied in the engineering of self-organizing and self-adaptive distributed systems and protocols.
{"title":"Complex Structures and Collective Dynamics in Networked Systems: Foundations for Self-Adaptation and Self-Organization","authors":"Ingo Scholtes, M. Esch","doi":"10.1109/SASOW.2014.7","DOIUrl":"https://doi.org/10.1109/SASOW.2014.7","url":null,"abstract":"The study of complex networks and collective dynamics occurring in biological, social and technical systems has experienced a massive surge of interest both from academia and industry. Many of the results on the mechanisms underlying the self-organized formation of complex dynamic networks in natural and man-made systems have been derived based on a statistical physics perspective. In this tutorial, we provide a basic introduction to this perspective which will help attendees to benefit from the vast literature on self-organization and self-adaptation phenomena available in the fields of network science and complex systems. We cover basic models and abstractions for the study of static complex networks as well as dynamical processes like, e.g., information diffusion, random walks, synchronization or the propagation of cascading failures. We further introduce recent advances in the study of dynamic (social) networks and demonstrate how the resulting methods can be practically applied in the engineering of self-organizing and self-adaptive distributed systems and protocols.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"65 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85015234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The design and operation of computer systems has traditionally been driven by technical aspects and considerations. However, the usage characteristics of information and communication systems are both implicitly and explicitly determined by social interaction and the social graph of users. The SASOST workshop addresses all aspects of self-adaptive and self-organising mechanisms in socio-technical systems, covering different perspectives of this exciting research area ranging from normative and trust management systems to socio-inspired design strategies for distributed algorithms, collaboration platforms and communication protocols.
{"title":"Second International Workshop on Self-Adaptive and Self-Organising Socio-technical Systems (SASOST 2014)","authors":"Gerrit Anders, J. Botev, M. Esch","doi":"10.1109/SASOW.2014.33","DOIUrl":"https://doi.org/10.1109/SASOW.2014.33","url":null,"abstract":"The design and operation of computer systems has traditionally been driven by technical aspects and considerations. However, the usage characteristics of information and communication systems are both implicitly and explicitly determined by social interaction and the social graph of users. The SASOST workshop addresses all aspects of self-adaptive and self-organising mechanisms in socio-technical systems, covering different perspectives of this exciting research area ranging from normative and trust management systems to socio-inspired design strategies for distributed algorithms, collaboration platforms and communication protocols.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"24 1","pages":"74-75"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91183547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Morphogenetic engineering represents an interesting field in which models, frameworks and algorithms can be tested in order to study how self-* properties and emergent behaviours can arise in potentially complex and distributed systems. In this field, the morphogenetic model we will refer to is swarm chemistry, since a well known challenge in this dynamical process concerns discovering mechanisms for providing evolution within coalescing systems of particles. These systems consist in sets of moving particles able to self-organise in order to create shapes or geometrical formations that provide robustness towards external perturbations. We present a novel mechanism for providing evolutionary features in swarm chemistry that takes inspiration from artificial immune system literature, more specifically regarding idiotypic networks. Starting from a restricted set of chemical recipes, we show that the system evolves to new states, using an autonomous method of detecting new shapes and behaviours free from any human interaction.
{"title":"Artificial Immune System Driven Evolution in Swarm Chemistry","authors":"Nicola Capodieci, E. Hart, Giacomo Cabri","doi":"10.1109/SASO.2014.16","DOIUrl":"https://doi.org/10.1109/SASO.2014.16","url":null,"abstract":"Morphogenetic engineering represents an interesting field in which models, frameworks and algorithms can be tested in order to study how self-* properties and emergent behaviours can arise in potentially complex and distributed systems. In this field, the morphogenetic model we will refer to is swarm chemistry, since a well known challenge in this dynamical process concerns discovering mechanisms for providing evolution within coalescing systems of particles. These systems consist in sets of moving particles able to self-organise in order to create shapes or geometrical formations that provide robustness towards external perturbations. We present a novel mechanism for providing evolutionary features in swarm chemistry that takes inspiration from artificial immune system literature, more specifically regarding idiotypic networks. Starting from a restricted set of chemical recipes, we show that the system evolves to new states, using an autonomous method of detecting new shapes and behaviours free from any human interaction.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"126 1","pages":"40-49"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73620611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this work, we present the implementation of a novel Agent-based Modelling and Simulation approach for the Schema Matching problem called "Schema Matching Agent-based Simulation" (SMAS). Our solution aims at generating high quality schema matchings with minimum uncertainty.
{"title":"Towards an Agent-Based Simulation Model for Schema Matching","authors":"Hicham Assoudi, H. Lounis","doi":"10.1109/SASO.2014.42","DOIUrl":"https://doi.org/10.1109/SASO.2014.42","url":null,"abstract":"In this work, we present the implementation of a novel Agent-based Modelling and Simulation approach for the Schema Matching problem called \"Schema Matching Agent-based Simulation\" (SMAS). Our solution aims at generating high quality schema matchings with minimum uncertainty.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"19 1","pages":"197-198"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73786736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Reinforcement learning is a widespread mechanism for adapting the individual behaviour of autonomous agents, while norms are a well-established means for organising the common conduct of these agents. Therefore, norm-governed reinforcement learning agents appear to be a powerful bio-inspired, as well as socio-inspired, paradigm for the construction of decentralised, self-adapting, self-organising systems. However, the convergence of learning and norms is not as straightforward as it appears: learning can 'misguide' the development of norms, while norms can 'stall' the learning of optimal behaviour. In this paper, we investigate the self-governance of learning agents, or more specifically the domain-independent (de)construction at run-time of prescriptive systems from scratch, for and by learning agents, without any agent having complete information of the system. Most importantly, because prescriptions may also misguide agents, we allow them to repeal any misguiding prescriptions that have previously been enacted. Simulations illustrate the approach with experimental insights regarding scalability and timeliness in the construction of prescriptive systems.
{"title":"Self-Governance by Transfiguration: From Learning to Prescription Changes","authors":"Régis Riveret, A. Artikis, J. Pitt, E. Nepomuceno","doi":"10.1109/SASO.2014.19","DOIUrl":"https://doi.org/10.1109/SASO.2014.19","url":null,"abstract":"Reinforcement learning is a widespread mechanism for adapting the individual behaviour of autonomous agents, while norms are a well-established means for organising the common conduct of these agents. Therefore, norm-governed reinforcement learning agents appear to be a powerful bio-inspired, as well as socio-inspired, paradigm for the construction of decentralised, self-adapting, self-organising systems. However, the convergence of learning and norms is not as straightforward as it appears: learning can 'misguide' the development of norms, while norms can 'stall' the learning of optimal behaviour. In this paper, we investigate the self-governance of learning agents, or more specifically the domain-independent (de)construction at run-time of prescriptive systems from scratch, for and by learning agents, without any agent having complete information of the system. Most importantly, because prescriptions may also misguide agents, we allow them to repeal any misguiding prescriptions that have previously been enacted. Simulations illustrate the approach with experimental insights regarding scalability and timeliness in the construction of prescriptive systems.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"15 1","pages":"70-79"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81604206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Autonomous and autonomic systems have proved highly effective for self-management of resource allocation in open, distributed computer systems and networks. The operation of such systems is, not unexpectedly, hidden from human users. The key question is how self-organising mechanisms for common-pool resource management be successfully transferred to resolve corresponding problems in socio-technical systems, i.e. computer-mediated systems with humans 'in the loop'. We investigate this problem in the context of smart grids for decentralised community energy systems (dCES). We present the design and implementation of a Serious Game, the Social Mpower game, in which players have to distribute energy resources in an economy of scarcity. A socio-technical system to achieve collective action should include collective awareness to enhance the sense of collective responsibility, social networking to promote self-organisation and visualisation of Ostrom's principles. We argue that the integration and encapsulation of all those requirements by Social Mpower will support successful collective action in a dCES.
{"title":"Collective Awareness for Collective Action in Socio-technical Systems","authors":"Aikaterini Bourazeri, J. Pitt","doi":"10.1109/SASOW.2014.37","DOIUrl":"https://doi.org/10.1109/SASOW.2014.37","url":null,"abstract":"Autonomous and autonomic systems have proved highly effective for self-management of resource allocation in open, distributed computer systems and networks. The operation of such systems is, not unexpectedly, hidden from human users. The key question is how self-organising mechanisms for common-pool resource management be successfully transferred to resolve corresponding problems in socio-technical systems, i.e. computer-mediated systems with humans 'in the loop'. We investigate this problem in the context of smart grids for decentralised community energy systems (dCES). We present the design and implementation of a Serious Game, the Social Mpower game, in which players have to distribute energy resources in an economy of scarcity. A socio-technical system to achieve collective action should include collective awareness to enhance the sense of collective responsibility, social networking to promote self-organisation and visualisation of Ostrom's principles. We argue that the integration and encapsulation of all those requirements by Social Mpower will support successful collective action in a dCES.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"43 1","pages":"90-95"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83694228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jan Kantert, Lukas Klejnowski, Sven Tomforde, J. Hähner, C. Müller-Schloer
Self-integration of system components is characterised by uncertain relations among these components. One approach to handle such uncertainties is to introduce technical trust. In previous work, we developed a concept to automatically build collections of components with stable trust relationships so-called Trusted Communities. In this paper, we discuss advanced attacks to the trusted communities and describe counter measures to deal with malicious elements. As application scenario, a Desktop Grid Computing system is used, since it mischaracterised by all those properties that become important when developing self-integrating systems: e.g. openness, heterogeneity and limited control over participating entities. The evaluation demonstrates that even advanced attacks can be recognised fast and successfully.
{"title":"Advanced Attacks to Trusted Communities in Multi-agent Systems","authors":"Jan Kantert, Lukas Klejnowski, Sven Tomforde, J. Hähner, C. Müller-Schloer","doi":"10.1109/SASOW.2014.29","DOIUrl":"https://doi.org/10.1109/SASOW.2014.29","url":null,"abstract":"Self-integration of system components is characterised by uncertain relations among these components. One approach to handle such uncertainties is to introduce technical trust. In previous work, we developed a concept to automatically build collections of components with stable trust relationships so-called Trusted Communities. In this paper, we discuss advanced attacks to the trusted communities and describe counter measures to deal with malicious elements. As application scenario, a Desktop Grid Computing system is used, since it mischaracterised by all those properties that become important when developing self-integrating systems: e.g. openness, heterogeneity and limited control over participating entities. The evaluation demonstrates that even advanced attacks can be recognised fast and successfully.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"21 1","pages":"186-191"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87617178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Activity Recognition (AR) Systems more and more find their way into our daily lives, from monitoring daily activities to support in medical care. However, such systems tend to be used with narrowly defined specifications, demanding for application-dependent setup and configuration by their users. A long term goal are autonomous systems, being able to work with no (or minimal) user interaction. Closely related to that vision is the ability of autonomously adding further input sources (e.g., sensors) at run-time, leading to an increased dimensionality of the input-space. Our approach aims at systematically investigating methods necessary for the creation of self-adapting classification systems. This includes an architecture, based on Organic Computing (OC) principles, as well as the development of measures for comparing probabilistic models and procedures for evaluating classifiers of different dimensionality. With such evaluation techniques, systems should be able to adapt their system model at run-time in a self-organized manner. Besides self-improvement (adding a new sensor) we also address the problem of self-healing (replacing a sensor that dropped out).
{"title":"Self-Adapting Multi-sensor Systems: A Concept for Self-Improvement and Self-Healing Techniques","authors":"Martin Jänicke, B. Sick, P. Lukowicz, D. Bannach","doi":"10.1109/SASOW.2014.22","DOIUrl":"https://doi.org/10.1109/SASOW.2014.22","url":null,"abstract":"Activity Recognition (AR) Systems more and more find their way into our daily lives, from monitoring daily activities to support in medical care. However, such systems tend to be used with narrowly defined specifications, demanding for application-dependent setup and configuration by their users. A long term goal are autonomous systems, being able to work with no (or minimal) user interaction. Closely related to that vision is the ability of autonomously adding further input sources (e.g., sensors) at run-time, leading to an increased dimensionality of the input-space. Our approach aims at systematically investigating methods necessary for the creation of self-adapting classification systems. This includes an architecture, based on Organic Computing (OC) principles, as well as the development of measures for comparing probabilistic models and procedures for evaluating classifiers of different dimensionality. With such evaluation techniques, systems should be able to adapt their system model at run-time in a self-organized manner. Besides self-improvement (adding a new sensor) we also address the problem of self-healing (replacing a sensor that dropped out).","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"1 1","pages":"128-136"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91091120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jan-Philipp Steghöfer, Gerrit Anders, Jan Kantert, C. Müller-Schloer, W. Reif
We discuss the implementation of a normative system in an open self-organising system, including an OCL-based format for norms we settled on, the design of the feedback loops for their observation and adaptation, as well as a corresponding software architecture. These elements allow designers to quickly integrate a normative sub-system in a MAS and to define norms based on existing design concepts.
{"title":"An Effective Implementation of Norms in Trust-Aware Open Self-Organising Systems","authors":"Jan-Philipp Steghöfer, Gerrit Anders, Jan Kantert, C. Müller-Schloer, W. Reif","doi":"10.1109/SASOW.2014.34","DOIUrl":"https://doi.org/10.1109/SASOW.2014.34","url":null,"abstract":"We discuss the implementation of a normative system in an open self-organising system, including an OCL-based format for norms we settled on, the design of the feedback loops for their observation and adaptation, as well as a corresponding software architecture. These elements allow designers to quickly integrate a normative sub-system in a MAS and to define norms based on existing design concepts.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":"48 1","pages":"76-77"},"PeriodicalIF":0.0,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84867324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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