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Pagina personale di NICOLA CAPODIECI

Dipartimento di Scienze Fisiche, Informatiche e Matematiche
Dipartimento di Scienze Fisiche, Informatiche e Matematiche sede ex-Matematica

Farahani, Ali; Nazemi, Eslam; Cabri, Giacomo; Capodieci, Nicola ( 2017 ) - Enabling Autonomic Computing Support for the JADE Agent Platform - SCALABLE COMPUTING. PRACTICE AND EXPERIENCE - n. volume 18 - pp. da 91 a 103 ISSN: 1895-1767 [Articolo in rivista (262) - Articolo su rivista]
Abstract

Engineering complex distributed system is a real challenge documented in recent literature. Novel paradigms such as Autonomic Computing (AC) approaches appear to be the fittest engineering model in order to face performance instabilities of systems inserted in open and non-deterministic environments. To this purpose, the availability of appropriate development environments will facilitate the design of such systems. Standard agent development platforms represent a good starting point, but they generally lack of rigorous ways to define central AC-related concepts such as the prominent role of feedback loops and knowledge integration in decision making processes: we therefore believe that Agent Oriented Software Engineering (AOSE) can be substantially enriched by taking into account such concepts. In this paper, a novel extension of the well-known JADE agent development environment is discussed. This extension enhances JADE in order to address the engineering process with Autonomic Computing support. It is called “Autonomic Computing Enabled JADE” or shortly ACE-JADE. The behavioral model of ACE-JADE will be thoroughly described in the context of a case study (NASA ANTS project).

Capodieci, Nicola; Pagani, Giuliano Andrea; Cabri, Giacomo; Aiello, Marco ( 2016 ) - An adaptive agent-based system for deregulated smart grids - SERVICE ORIENTED COMPUTING AND APPLICATIONS - n. volume 10 - pp. da 185 a 205 ISSN: 1863-2386 [Articolo in rivista (262) - Articolo su rivista]
Abstract

The power grid is undergoing a major change due mainly to the increased penetration of renewables and novel digital instruments in the hands of the end users that help to monitor and shift their loads. Such transformation is only possible with the coupling of an information and communication technology infrastructure to the existing power distribution grid. Given the scale and the interoperability requirements of such future system, service-oriented architectures (SOAs) are seen as one of the reference models and are considered already in many of the proposed standards for the smart grid (e.g., IEC-62325 and OASIS eMIX). Beyond the technical issues of what the service-oriented architectures of the smart grid will look like, there is a pressing question about what the added value for the end user could be. Clearly, the operators need to guarantee availability and security of supply, but why should the end users care? In this paper, we explore a scenario in which the end users can both consume and produce small quantities of energy and can trade these quantities in an open and deregulated market. For the trading, they delegate software agents that can fully interoperate and interact with one another thus taking advantage of the SOA. In particular, the agents have strategies, inspired from game theory, to take advantage of a service-oriented smart grid market and give profit to their delegators, while implicitly helping balancing the power grid. The proposal is implemented with simulated agents and interaction with existing Web services. To show the advantage of the agent with strategies, we compare our approach with the “base” agent one by means of simulations, highlighting the advantages of the proposal.

Capodieci, Nicola; Hart, Emma; Cabri, Giacomo ( 2016 ) - Artificial immunology for collective adaptive systems design and implementation - ACM TRANSACTIONS ON AUTONOMOUS AND ADAPTIVE SYSTEMS - n. volume 11 - pp. da 1 a 25 ISSN: 1556-4665 [Articolo in rivista (262) - Articolo su rivista]
Abstract

Distributed autonomous systems consisting of large numbers of components with no central control point need to be able to dynamically adapt their controlmechanisms to deal with an unpredictable and changing environment. Existing frameworks for engineering self-adaptive systems fail to account for the need to incorporate self-expression - that is, the capability of a system to dynamically adapt its coordination pattern during runtime. Although the benefits of incorporating self-expression are well known, currently there is no principled means of enabling this during system design.We propose a conceptual framework for principled design of systems that exhibit self-expression, based on inspiration from the natural immune system. The framework is described as a set of design principles and customizable algorithms and then is instantiated in three case studies, including two from robotics and one from artificial chemistry.We show that it enables self-expression in each case, resulting in systems that are able to adapt their choice of coordination pattern during runtime to optimize functional and nonfunctional goals, as well as to discover novel patterns and architectures.

Galassi, Marco; Capodieci, Nicola; Cabri, Giacomo; Leonardi, Letizia ( 2016 ) - Evolutionary Strategies for Novelty-Based Online Neuroevolution in Swarm Robotics ( 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest; Hungary - 9 October 2016 through 12 October 2016) ( - Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics ) (IEEE USA ) - pp. da 2026 a 2032 ISBN: 9781509018970 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

Neuroevolution in robot controllers throughobjective-based genetic and evolutionary algorithms is a wellknownmethodology for studying the dynamics of evolution inswarms of simple robots. A robot within a swarm is able toevolve the simple neural network embedded as its controllerby also taking into account how other robots are performingthe task at hand. In online scenarios, this is obtained throughinter-robot communications of the best performing genomes (i.e.representation of the weights of their embedded neural network).While many experiments from previous work have shown thesoundness of this approach, we aim to extend this methodologyusing a novelty-based metric, so to be able to analyze differentgenome exchange strategies within a simulated swarm of robotsin deceptive tasks or scenarios in which it is difficult to modela proper objective function to drive evolution. In particular, wewant to study how different information sharing approachesaffect the evolution. To do so we developed and tested threedifferent ways to exchange genomes and information betweenrobots using novelty driven evolution and we compared themusing a recent variation of the mEDEA (minimal EnvironmentdrivenDistributed Evolutionary Algorithm) algorithm. As thedeceptiveness and the complexity of the task increases, ourproposed novelty-driven strategies display better performancein foraging scenarios.

Puviani, Mariachiara; Cabri, Giacomo; Capodieci, Nicola; Leonardi, Letizia ( 2015 ) - Building self-adaptive systems by adaptation patterns integrated into agent methodologies ( - 7th International Conference on Agents and Artificial Intelligence, ICAART 2015 ) (Springer Heidelberg DEU ) - n. volume 9494 - pp. da 58 a 75 ISBN: 9783319279466 ISSN: 0302-9743 [Contributo in volume (Capitolo o Saggio) (268) - Capitolo/Saggio]
Abstract

Adopting patterns, i.e. reusable solutions to generic problems, turns out to be useful to rely on tested solutions and to avoid reinventing the wheel. To this aim, we proposed to use adaptation patterns to build systems that exhibit self-adaptive features. However, these patterns would be more usable if integrated in a methodology exploited to develop a system. In this paper we show how our Catalogue of adaptation patterns can be integrated into methodologies for adaptive systems; more in detail, we consider methodologies which support the development of multi-agent systems that can be considered good examples of adaptive systems. The paper, in particular, shows the integration of our Catalogue of adaptive patterns into the PASSI methodology, together with the graphical tool that we developed to support it.

Capodieci, Nicola; Burgio, Paolo ( 2015 ) - Efficient Implementation of Genetic Algorithms on GP-GPU with Scheduled Persistent CUDA Threads ( Seventh International Symposium on Parallel Architectures, Algorithms and Programming (PAAP), 2015 - Nanjing (China) - 12-14 Dicembre 2015) ( - Seventh International Symposium on Parallel Architectures, Algorithmsand Programming, PAAP 2015, Nanjing, China, December 12-14, 2015 ) - pp. da 6 a 12 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

In this paper we present a heavily exploration oriented implementation of genetic algorithms to be executed on graphic processor units (GPUs) that is optimized with our novel mechanism for scheduling GPU-side synchronized jobs that takes inspiration from the concept of persistent threads. Persistent Threads allow an efficient distribution of work loads throughout the GPU so to fully exploit the CUDA (NVIDIA's proprietary Compute Unified Device Architecture) architecture. Our approach (named Scheduled Light Kernel, SLK) uses a specifically designed data structure for issuing sequences of commands from the CPU to the GPU able to minimize CPUGPU communications, exploit streams of concurrent execution of different device side functions within different Streaming Multiprocessors and minimize kernels launch overhead. Results obtained on two completely different experimental settings show that our approach is able to dramatically increase the performance of the tested genetic algorithms compared to the baseline implementation that (while still running on a GPU) does not exploit our proposed approach. Our proposed SLK approach does not require substantial code rewriting and is also compared to newly introduced features in the last CUDA development toolkit, such as nested kernel invocations for dynamic parallelism.

Alsina, Emanuel F.; Capodieci, Nicola; Cabri, Giacomo; Regattieri, Alberto; Gamberi, Mauro; Pilati, Francesco; Faccio, Maurizio ( 2015 ) - The influence of the picking times of the components in time and space assembly line balancing problems: An approach with evolutionary algorithms ( IEEE Symposium Series on Computational Intelligence, SSCI 2015 - Cape Town; South Africa - 2015) ( - Proceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015 ) (Institute of Electrical and Electronics Engineers Inc. Piscataway USA ) - pp. da 1021 a 1028 ISBN: 9781479975600; 9781479975600 | 9781479975600 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

The balancing of assembly lines is one of the most studied industrial problems, both in academic and practical fields. The workable application of the solutions passes through a reliable simplification of the real-world assembly line systems. Time and space assembly line balancing problems consider a realistic versions of the assembly lines, involving the optimization of the entire line cycle time, the number of stations to install, and the area of these stations. Components, necessary to complete the assembly tasks, have different picking times depending on the area where they are allocated. The implementation in the real world of a line balanced disregarding the distribution of the tasks which use unwieldy components can result unfeasible. The aim of this paper is to present a method which balances the line in terms of time and space, hence optimizes the allocation of the components using an evolutionary approach. In particular, a method which combines the bin packing problem with a genetic algorithm and a genetic programming is presented. The proposed method can be able to find different solutions to the line balancing problem and then evolve they in order to optimize the allocation of the components in certain areas in the workstation.

N. Capodieci; E. Hart; G. Cabri ( 2014 ) - Artificial Immune System driven evolution in Swarm Chemistry ( 2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems - London, UK - September 8-12) ( - Proceedings of the 2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems ) (IEEE Piscataway. NJ USA ) - pp. da 40 a 49 ISBN: 9781479953677 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
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.

Capodieci N.; Hart E.; Cabri G. ( 2014 ) - Artificial Immune System in the context of Autonomic Computing: integrating design paradigms ( the 2014 conference companion on Genetic and evolutionary computation companion - Vancouver, CA - July 12-16) ( - Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion ) (ACM New York USA ) - n. volume 1 - pp. da 21 a 22 ISBN: 9781450328814 [Abstract in Atti di convegno (274) - Abstract in Atti di Convegno]
Abstract

We describe a framework for developing autonomic computing systems, based on an analogy with the natural immune system. A detailed comparison between the autonomic computing literature and the field of cognitive immune networks is drawn, particularly with respect to ensembles of components (in automomic computing) and ensembles of cells (in immune systems). We show how current approaches to designing autonomic systems could be enriched by considering alternative design processes based on cognitive immune networks.

N. Capodieci; E. Hart; G. Cabri ( 2014 ) - Idiotypic networks for evolutionary controllers in virtual creatures ( 14th International Conference on the Synthesis and Simulation of Living Systems (ALIFE 2014) - New York, USA - 30/7 - 2/8/2014) ( - Artificial Life 14: Proceedings of the 14th International Conference on the Simulation and Synthesis of Living Systems (Alife 14) ) (MIT Press Cambridge USA ) - pp. da 192 a 199 ISBN: 9780262326216 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

We propose a novel method for evolving adaptive locomotive strategies for virtual limbless creatures that addresses both functional and non-functional requirements, respectively the ability to avoid obstacles and to minimise spent energy. We describe an approach inspired by artificial immune systems, based on a dual-layer idiotypic network that results in a completely decentralised controller. Results are compared to a set of five fixed locomotion strategies and show that adaptive control can evolve and simultaneously optimise energy requirements, starting from the same locomotion non-adaptive strategies.

N Capodieci; G Cabri; F Zambonelli ( 2014 ) - Modeling Self-Expression by Holons ( 2014 High Performance Computing & Simulation Conference (HPCS 2014) - Bologna, Italy - July 21-25) ( - Proceedings of the 2014 International Conference on High Performance Computing & Simulation (HPCS 2014) ) (IEEE Los Alamitos USA ) - pp. da 424 a 431 ISBN: 9781479953110 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

In the field of autonomic computing the current trend is to develop cooperating computational entities enabled with enhanced self-* properties. The term self-* indicates the possibility of an element inside a set (an ensemble) composed of many potentially heterogeneous components to self organize, heal (repair), optimize and configure without little or no human interaction. The goal is to increase the level of adaptivity for both the ensemble and the single element, especially in scenarios in which stopping a system for further tuning is unfeasible. In this paper, we propose an approach to model and enable the capability of adopting different collaboration patterns in ensembles of autonomic components inserted in open and nondeterministic environments. This model takes inspiration from the holonic organisation of multi agent systems and from a Self-* property, called Self-Expression, which is defined as the property of a distributed system to change its collaboration pattern at run time in order to better adapt its execution of tasks in unknown situations. Ensembles able to deploy Self-Expression, show a higher level of adaptation and the concept of Self-Expression can be easily exploited though a Self-Repeating structure like a hierarchy of holons.

Giacomo Cabri; Nicola Capodieci; Luca Cesari; Rocco De Nicola; Rosario Pugliese; Francesco Tiezzi; Franco Zambonelli ( 2014 ) - Self-Expression and Dynamic Attribute-based Ensembles in SCEL ( 6th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2014 - Imperial, Corfu, Greece - 08-11 October 2014) ( - Proceedings of 6th International Symposium on Leveraging Applications (ISoLA 2014) ) - LECTURE NOTES IN COMPUTER SCIENCE - n. volume 8802 - pp. da 147 a 163 ISSN: 0302-9743 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

In the field of distributed autonomous computing the current trend is to develop cooperating computational entities enabled with enhanced self-* properties. The expression self-* indicates the possibility of an element inside an ensemble, i.e. a set of collaborative autonomic components, to self organize, heal (repair), optimize and configure with little or no human interaction. We focus on a self-* property called Self-Expression, defined as the ability to deploy run-time changes of the coordination pattern of the observed ensemble; the goal of the ensemble is to achieve adaptivity by meeting functional and non-functional requirements when specific tasks have to be completed. The purpose of this paper is to rigorously present the mechanisms involved whenever a change in the coordination pattern is needed, and the interactions that take place. To this aim, we use SCEL (Software Component Ensemble Language), a formal language for describing autonomic components and their interactions, featuring an highly dynamic and flexible way to form ensembles based on components' attributes.

Capodieci, Nicola; Hart, Emma; Cabri, Giacomo ( 2013 ) - An immune network approach for self-adaptive ensembles of autonomic components: a case study in swarm robotics ( Twelfth European Conference on the Synthesis and Simulation of Living Systems - Tormina, Italy - September 2-6 2013) ( - Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems ) (MIT Press Cambridge, MA USA ) - pp. da 864 a 871 ISBN: 9780262317092; 9780262317092 | 9780262317092 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

We describe an immune inspired approach to achieve self-expression within an ensemble, i.e. enabling an ensemble of autonomic components to dynamically change their coordination pattern during the runtime execution of a given task. Building on previous work using idiotypic networks, we consider robotic swarms in which each robot has a lymph node containing a set of antibodies describing conditions under which different coordination patterns can be applied. Antibodies are shared between robots that come into communication range facilitating collaboration. Tests in simulation in robotic arenas of varying complexity show that the swarm is able to learn suitable patterns and effectively achieve a foraging task, particularly in arenas of high complexity.

Giacomo Cabri; Nicola Capodieci ( 2013 ) - Applying Multi-armed Bandit Strategies to Change of Collaboration Patterns at Runtime ( 1st International Conference on Artificial Intelligence, Modelling and Simulation, AIMS 2013 - Kota Kinabalu, Sabah, Malaysia - 3-5 December) ( - Proceedings of the First International Conference on Artificial Intelligence, Modelling and Simulation ) (IEEE Computer Society, Conference Publishing Service Los Alamitos, California USA USA ) - pp. da 151 a 156 ISBN: 978-147993251-1 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

Autonomic systems have some interesting properties that enable them to self-manage at runtime. Traditionally, they are Self-configuration, Self-healing, Self-optimization, and Self-protection. Another interesting property is Self-expression, i.e. the capability of reconfiguring the collaboration pattern of a system at runtime and in an autonomous way. This re-factoring of behaviours, roles and interactions takes place whenever the environment in which the set of components is inserted experiences some changes, so that in order to adapt to the ever variable external conditions, the system is still able to maximize its utilities. In the past we have motivated the need for such a pattern change, and have proposed some approaches to enact it in situations in which we can associate to each external condition the fittest coordination pattern. In this paper we propose a strategy to decide the change and to choose the next collaboration pattern in situations in which the system components do not have sufficient knowledge and cognition to reason about the varying external conditions. Our approach is based on the algorithms proposed to solve the multi-armed bandit problem, in which a player must choose which slot machine to pull, given a number of them, in order to maximize the reward.

N. Capodieci; G. Cabri ( 2013 ) - Collaboration in Swarm Robotics: a Visual Communication Approach ( The 2013 International Conference on Collaboration Technologies and Systems (CTS) - San Diego, California, USA - May 20-24) ( - Proceedings of the 2013 International Conference on Collaboration Technologies and Systems (CTS) ) (IEEE Computer Society, Conference Publishing Service Los Alamitos, California USA ) - pp. da 195 a 202 ISBN: 9781467364034 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

Swarm robotics involves a number of simple robots that have a common task and carry it out in a collective way. In this context the collaboration among the different components is a crucial aspect, but not always it can be enacted in a direct way, i.e., by means of direct communication between components. This is because of the simplicity of the robots, but this turns out to increase robustness and flexibility of the swarm systems. In this paper we present a case study in which some robots are in charge of sweeping the perimeter of an area, and propose a distributed algorithm for the task division. We have tested the proposed algorithm in different situations; we report the results and we also compare them to the ones achieved with no collaboration.

Capodieci, Nicola; Alsina, Emanuel Federico; Cabri, Giacomo ( 2013 ) - Context-awareness in the deregulated electric energy market: an agent-based approach - CONCURRENCY AND COMPUTATION - n. volume 27 - pp. da 1513 a 1524 ISSN: 1532-0626 [Articolo in rivista (262) - Articolo su rivista]
Abstract

Multiagent systems are commonly used for simulation of new paradigms of energy distribution. Especially when considering Smart Grids, the autonomicity deployed by goal-driven agents implies the need for being aware of multiple aspects connected to the energy distribution context. With ‘context’, we refer to the outside world variables such as weather, stock market trends, location of the users, government actions, and so on; therefore, an architecture highly context-aware is needed. We propose a model in which every important factor concerning the electric energy distribution is presented by modeling context-aware agents able to identify the impact of these factors. Moreover, some tests have been performed regarding the web service integration in which agents contracting energy will automatically retrieve data to be used in adaptive and collaborative aspects; an explicative example is represented by the retrieval of weather forecasting that provides input on ongoing demand and data for the predicted availability (in case of photovoltaic or wind powered environments).

N. Capodieci; E. Hart; G. Cabri ( 2013 ) - Designing Self-Aware Adaptive Systems: from Autonomic Computing to Cognitive Immune Networks ( 7th IEEE International Conference on Self-Adaptation and Self-Organizing Systems Workshops, SASOW 2013 - Philadelphia, USA - September, 13, 2013) ( - Proceedings of the 7th IEEE International Conference on Self-Adaptation and Self-Organizing Systems Workshops, SASOW 2013 ) (IEEE Computer Society, Conference Publishing Service Los Alamitos, California USA USA ) - pp. da 59 a 64 ISBN: 9781479950867 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

An autonomic system is composed of ensembles of heterogeneous autonomic components in which large sets of components are dynamically added and removed. Nodes within such an ensemble should cooperate to achieve system or human goals, and systems are expected to self-adapt with little or no human-interaction. Designing such systems poses significant challenges. In this paper we propose that the system engineer might gain significant inspiration by looking to the biological immune system, particularly by adopting a perspective on the immune system proposed by Cohen known as the Cognitive Immune Network. The goal of this paper is to show how the current literature in autonomic computing could be positively enriched by considering alternative design processes based on cognitive immune networks. After sketching out the mapping in commonalities between the Cognitive Immune Network and the autonomic computing reference model, we demonstrate how these considerations regarding the design process can be exploited with an engineered autonomic system by describing experiments with a simple robotic swarm scenario.

N. Capodieci; G. Cabri ( 2013 ) - Managing Deregulated Energy Markets: an Adaptive and Autonomous Multi-Agent System Application ( 2013 IEEE International Conference on Systems, Man, and Cybernetics - Manchester, UK - October, 2013) ( - Proceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics ) (IEEE Computer Societyy, Conference Publishing Service Los Alamitos, California USA USA ) - pp. da 758 a 763 ISBN: 9780769551548 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

Given the complexity of modelling actors and interactions of the deregulated electric energy market, the Multi-Agent System approach turns out to be suitable for both simulation and application of critical aspects in the Smart Grid. In particular, for balancing demand and offer and for handling negotiation among peers: now, even a domestic environment that features photovoltaic and/or wind turbines modules can decide to enter the deregulated market as a small-scale seller, thus making the requirement of having such an architecture to be autonomous by deploying Self-* properties such as Self-Organization, Self- Repairing, Self-Adaptation. To be more specific about the presented case study, we propose a model in which small-scale seller agents dynamically and autonomously decide either to address the market as lone operators or by aggregating into Virtual Power Plants, from time to time in order to adapt to different situations. This iterated decisional process depends on highly variable market related factors, thus our goal is to design a net of agents able to autonomously react to this dynamic environment.

G. Cabri; N. Capodieci ( 2013 ) - Runtime Change of Collaboration Patterns in Autonomic Systems: Motivations and Perspectives ( 2013 IEEE 27th International Conference on Advanced Information Networking and Applications Workshops - Barcelona, Spain - March 25-28) ( - Proceedings of the 2013 IEEE 27th International Conference on Advanced Information Networking and Applications Workshops ) (IEEE Conference Publishing Services, IEEE Computer Society Los Alamitos USA ) - pp. da 1038 a 1043 ISBN: 9780769549521; 9781467362399 | 9781467362399 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

Today’s distributed systems are more and more complex, so they are required to be autonomic, i.e., to exhibit some self-* properties in order to manage themselves. Autonomic systems are usually composed of different components, which collaborate to achieve a global goal or to provide a high-level service. The collaboration pattern is usually defined statically, but the aim of this paper is to show that there are motivations to enable composed systems to change their collaboration pattern at runtime in an autonomous way, starting from some case studies. This capability of autonomic systems is called self-expression, meaning that a system can express itself despite unexpected situations. Moreover, we propose three perspective solutions that aim at enabling the change at runtime: role-based, descriptionbased, and Artificial Immune Systems (AIS)-inspired.

N. Capodieci; E. Alsina; G. Cabri ( 2012 ) - A Context-aware Agent-based Approach for Deregulated Energy Market ( 21st IEEE International WETICE conference - Toulouse, France - June 25-27) ( - Proceedings of the 21st IEEE International WETICE conference ) (IEEE Computer Society, Conference Publishing Service Los Alamitos, CA USA ) - pp. da 16 a 21 ISBN: 9781467318884 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

A deregulated energy market is a typical scenario in which software agents are used for simulation and/or application purposes. Agents act on behalf of end users, thus implying the necessity of being aware of multiple aspects connected to the distribution of electricity. These aspects refer to outside world variables like weather, stock market trends, location of the users etc. therefore an architecture highly context aware is needed. We propose a web service integration in which agents contracting energy will automatically retrieve data to be used in adaptive and collaborative aspects, an explicative example, misrepresented by the retrieval of weather forecasting, that provides input on ongoing demand and data for the predicted availability(in case of photovoltaic or wind powered environments). The challenge lies in how to correctly use data coming from different sources, since these information are crucial for user profiling and balancing in the short-term contracts in the Smart Grid.

N. Capodieci; G. Cabri; G. A. Pagani; M. Aiello ( 2012 ) - Adaptive Game-based Agent Negotiation in Deregulated Energy Markets ( the 2012 International Conference on Collaboration Technologies and Systems - Denver, Colorado, USA - May 21-25) ( - Proceedings of the 2012 International Conference on Collaboration Technologies and Systems ) (IEEE Computer Society Press Piscataway, NJ USA ) - pp. da 300 a 307 ISBN: 9781467313810 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

In the emerging deregulated energy paradigm enabled by the Smart Grid, energy provisioning will change drastically. Energy contracts will be negotiated between a potential multitude of parties at high frequency (e.g., several times per day) based on local needs and micro-generation production facilities. In this context, this paper presents an agent-based approach to manage negotiation among the different parties.The goal of the presented work is to propose adaptive negotiation strategies for trading energy in a deregulated market. In particular, we provide strategies derived from game theory, in order to optimize energy production and supply costs by means of negotiation and adaptation. The novelty lies in the adaptation of the class of minority and stochastic games to the energy trading problem in order to model the strategy of the various parties involved. The paper presents also simulation results of a scenario with a large number of energy buyers, a small set of prosumers (energy consumers and producers using renewable micro-generation facilities) and a few large-scale traditional electricity suppliers.

N. Capodieci; G. Cabri; G. A. Pagani; M. Aiello ( 2012 ) - An Agent-based Application to Enable Deregulated Energy Markets ( 36th Annual IEEE Computer Software and Applications Conference (COMPSAC 2012) - Izmir, Turkey - July 16-20) ( - Proceedings of the 36th Annual IEEE Computer Software and Applications Conference (COMPSAC 2012) ) (IEEE Computer Society, Conference Publishing Service Los Alamitos, California USA ) - pp. da 638 a 647 ISBN: 9780769547367; 9781467319904 | 9781467319904 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

Private houses are more and more enabled with devices that can produce renewable energy, and the not so remote chance of selling the surplus energy makes them new players in the energy market.This market is likely to become deregulated since each energy home-producer can negotiate the energy price with consumers, typically by means of an auction; on the other hand, consumers can always rely on energy companies, even if their energy is more expensive.This scenario could lead to advantages for users, but it is certainly complex and dynamic, and needs an appropriate management.To this purpose, in this paper we propose an agent-based application to deal with the negotiation among different parties producing and consuming energy.Software agents, thanks to their autonomy in taking decisions, well suit the requirements of the proposed scenario.For our application, we adopt a strategy derived from game theory, in order to optimize energy production and supply costs by means of negotiation and learning.The effectiveness of our approach is proved by simulation results of a situation involving energy buyers, energy producers using renewable micro-generation facilities and large-scale traditional electricity companies.

Nicola Capodieci; Giacomo Cabri ( 2012 ) - Conceptual Map and Classification in Ensembles of Autonomic Components: from Awareness to Organization ( The 2nd AWARE workshop on Challenges for Achieving Self-Awareness in Autonomic Systems - Lyon, France - September 10) ( - Proceedings of the 2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems Workshops (SASOW) ) (IEEE Computer Society, Conference Publishing Service Los Alamitos, CA USA ) - pp. da 127 a 132 ISBN: 9781467351539 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

Designing cooperative autonomic components andstudying their possible interactions when operating in ensemblein open and non-deterministic environments, poses severalchallenges for the developer. While older studies focus on theseveral possibilities for optimized collaboration protocols andcommunication possibilities in distributed architectures, themost recent trend is more focussing on the self-expression andself-organizing features that aware components may deployduring run-time, thus exploring new frontiers in designingadaptive collaboration patterns. In this paper we propose aconceptual map for autonomic components (taking into accountthe distributed robotics scenario) able to classify old andnew approaches in collaboration, highlighting similarities andcommonalities between patterns and by focussing on the laststudies about awareness of autonomous components. Being apreliminary study, the further goal is represented by findinga design approach for dynamically changing collaborationpatterns during a run-time execution of tasks.

N. Capodieci; G. Cabri ( 2012 ) - Coordination And Task Division In Robot Ensembles: Perimeter Sweep Case Study ( 21st IEEE International WETICE conference - Toulouse, France - June 25-27) ( - Proceedings of the 21st IEEE International WETICE conference ) (IEEE Computer Society, Conference Publishing Service Los Alamitos, CA USA ) - pp. da 101 a 103 ISBN: 9781467318884 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

Coordination and communication in scenarios where a multitude of robots are presents represent very critical aspects when designing robot ensembles. This paper will show how is it possible to coordinate and sub-divide tasks in a homogeneous ensemble of robots, exploiting a wall-following case study in which every bot has to be aware of the presence of other peers, by adapting its choices accordingly and cooperate to improve the overall performances. The global task has to be accomplished with extremely limited communication capabilities and by distributed coordination. Software simulations that model existing robots were performed for helping us to show the efficiency of the proposed approach.

N. Capodieci; G. A. Pagani; G. Cabri; M. Aiello ( 2011 ) - Smart Meter aware Domestic Energy Trading Agents ( First International E-Energy Market Challenge (IEEMC 2011) at the 8th International Conference on Autonomic Computing - Karlsruhe, Germany - June 2011) ( - Proceedings of 8th International Conference on Autonomic Computing ) (ACM New York USA ) - pp. da 1 a 10 ISBN: 9781450306072 [Contributo in Atti di convegno (273) - Relazione in Atti di Convegno]
Abstract

The domestic energy market is changing with the increasing availability of energy micro-generating facilities. On thelong run, households will have the possibility to trade energyfor purchase and sale from a number of different actors. Wemodel such a futuristic scenario using software agents. Weillustrate an implementation including the interfacing with aphysical Smart Meter and provide initial simulation results.Given the high autonomy of the actors in the domestic market and the complex set of behaviors, the agent approachproves to be effective for both modeling and simulating purposes.