A Dynamic and Adaptable Service Composition Architecture in the Cloud Based on Multi-Agent Systems

Nowadays, service composition is one of the major problems in the Cloud due to the exceptional growth in the number of services deployed by providers. Recently, atomic services have been found to be unable to deal with all client requirements. Traditional service composition gives the clients a composite service without non-functional parameters. To respond to both functional and non-functional parameters, we need a service composition. Since web services cannot communicate with each other or participate dynamically to handle changes service parameters in service composition, this issue has led us to use a dynamic entity represented by an agent based on dynamic architecture. This work proposes an agent-based architecture with a new cooperation protocol that can offer an automatic and adaptable service composition by providing a composite service with the maximum quality of service. The implementation of this model has been provided in order to evaluate the authors' system. The obtained results demonstrate the effectiveness of their proposed system

Assistant Agents to Advice Users in Hybrid Structured 3D Virtual Environments

Hybrid structured 3D Virtual Environments model serious activities in immersive 3D spaces, where participants are human and software agents, and their interactions are regulated by an Organization Centered Multi-Agent System (OCMAS). In this context, both OCMAS social model and the tasks that users need to accomplish can be rather complex, and thus, users may benefit from having an assistance service. Hence, we propose personal assistant agents (PA), which, based on knowledge about the OCMAS specification and current system state, provide the user with an advice (a plan) to achieve her or his goal. Additionally, we implement this service with plan-ea, an extension of the A¿*¿ algorithm that generates plans for a user whose actions may depend on other users¿ actions. Thus, PAs provide plans that do not only include assisted user actions but also other users¿ ones. We illustrate our approach by means of v-mWater¿an online water market¿and make a comparative analysis, with and without assistance, where efficiency¿in terms of number of user actions¿shows an improvement (7 vs 10.8), efficacy¿percentage of completed tasks¿also improves (93% vs 77%), and assistance's overall satisfaction is positive. Copyright © 2014 John Wiley & Sons, Ltd.Peer Reviewe

Assistive Awareness in Smart Grids

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Execution infrastructure for normative virtual environments

Virtual Institutions (VIs) have proven to be adequate to engineer applications where participants can be humans and software agents. VIs combine Electronic Institutions (EIs) and 3D Virtual Worlds (VWs). In this context, Electronic Institutions are used to establish the regulations that structure interactions and support software agent participation while Virtual Worlds facilitate human participation. In this paper we propose Virtual Institution eXEcution Environment (VIXEE) as an innovative communication infrastructure for VIs. Using VIXEE to connect Virtual Worlds and EI opens EI to humans, providing a fully operational and comprehensive environment. The main features of the infrastructure are (i) the causal connection between Virtual Worlds and Electronic Institutions, (ii) the automatic generation and update of the VIs' 3D visualization and (iii) the simultaneous participation of users from different virtual world platforms. We illustrate the execution of VIXEE system in a simple eAuction house example and use this example to evaluate the performance of our solution

Assistant Agents to Advice Users in Hybrid Structured 3D Virtual Environments

Hybrid structured 3D Virtual Environments model serious activities in immersive 3D spaces, where participants are human and SW agents, and their interactions are regulated by an OCMAS (Organization Centered Multi-Agent System). In this context, both OCMAS social model and the tasks that users need to accomplish can be rather complex, and thus, users may benefit from having an assistance service. Hence, we propose Personal Assistant agents (PA) which, based on knowledge about the OCMAS specification and current system state, provide the user with an advice (a plan) to achieve her goal. Additionally, we implement this service with PLAN-EA, an Extension of the $A^{\ast}$ algorithm that generates plans for a user whose actions may depend on other users' actions. Thus, PAs provide plans that do not only include assisted user actions but other users' ones. We illustrate our approach by means of v-mWater -an online water market- and make a comparative analysis, with and without assistance, where efficiency -in terms of number of user actions- shows an improvement (7 vs 10.8), efficacy -percentage of completed tasks- also improves (93% vs 77%), and assistance's overall satisfaction is positive

Applying IRON to a Virtual Community Scenario

Normative systems (norms) have been widely proposed as a technique for coordinating multi-agent systems (MAS). The automated synthesis of norms is a complex problem that remains open. IRON (Intelligent Robust On-line Norm synthesis mechanism) is a novel mechanism for the on-line automated synthesis of norms for MASs. IRON produces conflict-free norms that characterise necessary conditions for coordination, without over-regulation. In the past, IRON successfully regulated a traffic scenario even in the presence of non-compliant agents. In this paper, we apply IRON to synthesise norms for a virtual community scenario, where agents are users that share contents within the community. As a result, IRON synthesises norms that prevent users from uploading undesirable contents (i.e., those that users complain about). © 2013 The authors and IOS Press. All rights reserved.This work was funded by AT (CONSOLIDER CSD2007-0022), EVE (TIN2009-14702-C02-01/02), COR (TIN2012-38876-C02-01/02), MECER (201250E053) and the Generalitat of Catalunya (2009-SGR-1434).Peer Reviewe

Including Conversational Agents into Structured Hybrid 3D Virtual Environments

Structured Hybrid 3D Virtual Environments are 3D virtual spaces where staff (organisational) software agents support human users in their task achievement. These systems are characterized by: i) being hybrid, so that humans and software agents can interact; and ii) being structured and task oriented, so that interactions are regulated by a subjacent Organisation Centered Multi Agent System (OCMAS)-an Electronic Institution (EI). The contribution of this paper is to include task-oriented conversational staff bots (i.e. the embodiment of staff agents in the 3D environment) that communicate with users by using natural language. With this aim, we extend the Artificial Intelligence Mark-up Language (AIML) with special tags to enable complex task-oriented conversations whose flow needs to consider both the states of the conversation and the ontology related to the task. We evaluate the usability of our conversational proposal and compare it to a previous command-based interaction system. Results show the conversational approach presents a higher user satisfaction than the command-based one. Moreover, in average, it also performs better in terms of efficiency, effectiveness and errors

Synthesising Liberal Normative Systems

Norms have been extensively studied to coordinate multi-agent systems, and the literature has investigated two general approaches to norm synthesis: off-line (synthesising norms at design-time) and on-line (run-time synthesis). On-line synthesis is generally recognised to be appropriate for open systems, where aspects of the system remain unknown at design-time. In this paper we present LION, an algorithm aimed at synthesising liberal normative systems. lion's normative systems respect the agents' autonomy to the greatest possible extent, constraining their behaviour when only necessary to avoid undesirable system states, lion's norm synthesis is also driven by the need to construct compact normative systems. The key to the success of lion in this multi-objective synthesis process is that it learns about and exploits norm synergies. More precisely, lion can learn when norms are either substitutable or complementary. We show empirically that LION significantly outperforms the state of the art by synthesising normative systems that are more liberal while maintaining representation compactness. Copyright © 2015, International Foundation for Autonomous Agents and Multiagent Systems.Work funded by projects AT (CSD2007-0022), COR (TIN2012-38876-C02-01, TIN2012-38876-C02-02), and 2009-SGR-1434. Mike Wooldridge was supported by the ERC under Advanced Grant 291528 (“RACE")Peer reviewe

Minimality and Simplicity in the On-line Automated Synthesis of Normative Systems

Much previous research has investigated explicit, machine-process-able norms as a means to facilitate coordination in open multi-agent systems. This research can typically be classified as considering either offline design (norms are synthesised at design time) or online design. Online synthesis techniques aim to construct norms for a system while that system is actually running. A promising recent approach to on-line norm synthesis has been proposed but it suffers from serious drawbacks: (i) it needs too much information; (ii) it ignores issues of compactness in terms of minimality (ensuring that norms are not superfluous) and simplicity (ensuring that agents can process norms with little computational effort). To overcome these drawbacks, we propose an optimistic approach which, even though it uses less information, is able to explore more norms and synthesises sets of norms which are more compact. We present experimental evidence of the quality of our approach. Copyright © 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.Peer Reviewe

Extending NormLab to Spur Research on Norm Synthesis

On-line norm synthesis is a widely used approach to facilitate coordination in MASs. In [2] we introduced NormLab, a computational framework to support research on on-line norm synthesis. That framework provides functionalities to model, simulate and analyse norm synthesis algorithms in an agent-based simulation environment. Here we present several extensions to that work, providing a benchmark for research on norm synthesis in MAS.Work funded by projects AT (CSD2007-0022), COR (TIN2012-38876-C02-01/02), and 2009-SGR-1434. Mike Wooldridge was supported by the ERC under Advanced Grant 291528 (“RACE").Peer reviewe