Preference Learning in Automated Negotiation Using Gaussian Uncertainty Models

In this paper, we propose a general two-objective Markov Decision Process (MDP) modeling paradigm for automated negotiation with incomplete information, in which preference elicitation alternates with negotiation actions, with the objective to optimize negotiation outcomes. The key ingredient in our MDP framework is a stochastic utility model governed by a Gaussian law, formalizing the agent's belief (uncertainty) over the user's preferences. Our belief model is fairly general and can be updated in real time as new data becomes available, which makes it a fundamental modeling tool

Automated negotiation with Gaussian process-based utility models

Designing agents that can efficiently learn and integrate user's preferences into decision making processes is a key challenge in automated negotiation. While accurate knowledge of user preferences is highly desirable, eliciting the necessary information might be rather costly, since frequent user interactions may cause inconvenience. Therefore, efficient elicitation strategies (minimizing elicitation costs) for inferring relevant information are critical. We introduce a stochastic, inverse-ranking utility model compatible with the Gaussian Process preference learning framework and integrate it into a (belief) Markov Decision Process paradigm which formalizes automated negotiation processes with incomplete information. Our utility model, which naturally maps ordinal preferences (inferred from the user) into (random) utility values (with the randomness reflecting the underlying uncertainty), provides the basic quantitative modeling ingredient for automated (agent-based) negotiation

Unobtrusive Personalized Services in Ambient Media Environments

In the age of ambient media, people are surrounded by lots of physical objects (media objects) for rendering the digital world in the natural environment. These media objects should interact with users in a way that is not disturbing for them. To address this issue, this work presents a design strategy for augmenting the world around us with personalized services capable of adjusting its obtrusiveness level (i.e., the extent to which each service intrudes the user's mind) by using the appropriate media objects for each situation

Minimising intrusiveness in pervasive computing environments using multi-agent negotiation

This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multi-agent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario

Minimising Intrusiveness in Pervasive Computing Environments Using Multi-Agent Negotiation

This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multi-agent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario

Automating unobtrusive personalized services in ambient media environments

The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-013-1634-2In the age of ambient media, people are surrounded by lots of physical objects (media objects) for rendering the digital world in the natural environment. These media objects should interact with users in a way that is not disturbing for them. To address this issue, this work presents a design and automation strategy for augmenting the world around us with personalized ambient media services that behave in a considerate manner. That is, ambient services are capable of adjusting its obtrusiveness level (i.e., the extent to which each service intrudes the user¿s mind) by using the appropriate media objects for each user¿s situation.This work has been developed with the support of MICINN, under the project EVERYWARE TIN2010-18011, and the support of the Christian Doppler Forschungsgesellschaft and the BMWFJ, Austria.Serral Asensio, E.; Gil Pascual, M.; Valderas Aranda, PJ.; Pelechano Ferragud, V. (2014). Automating unobtrusive personalized services in ambient media environments. Multimedia Tools and Applications. 71(1):159-178. https://doi.org/10.1007/s11042-013-1634-2S159178711Bencomo N, Grace P, Flores-Cortés CA, Hughes D, Blair GS (2008) Genie: supporting the model driven development of reflective, component-based adaptive systems. In: ICSE, pp 811–814Blumendorf M, Lehmann G, Albayrak S (2010) Bridging models and systems at runtime to build adaptive user interfaces. In: Proc. of EICS 2010. ACM, pp 9–18Brown DM (2010) Communicating design: developing web site documentation for design and planning, 2nd edn. New Riders PressCalinescu R (2011) When the requirements for adaptation and high integrity meet. In: Proceedings of the 8th workshop on assurances for self-adaptive systems, ASAS ’11. ACM, New York, pp 1–4Filieri A, Ghezzi C, Tamburrelli G (2011) Run-time efficient probabilistic model checking. In: Proceedings of the 33rd International Conference on Software Engineering, ICSE ’11. ACM, New York, pp 341–350Gershenfeld N, Krikorian R, Cohen D (2004) The internet of things. Sci Am 291(4):46–51Gibbs WW (2005) Considerate computing. Sci Am 292(1):54–61Gulliksen J, Goransson B, Boivie I, Blomkvist S, Persson J, Cajander A (2003) Key principles for user-centred systems design. Behav Inform Technol 22:397–409Hinckley K, Horvitz E (2001) Toward more sensitive mobile phones. In: Proc. of the UIST ’01, pp 191–192Ho J, Intille SS (2005) Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. In: Proc. of CHI ’05. ACM, pp 909–918Horvitz E, Kadie C, Paek T, Hovel D (2003) Models of attention in computing and communication: from principles to applications. Commun ACM 46:52–59Ju W, Leifer L (2008) The design of implicit interactions: making interactive systems less obnoxious. Des Issues 24(3):72–84Kortuem G, Kawsar F, Fitton D, Sundramoorthy V (2010) Smart objects as building blocks for the internet of things. IEEE Internet Comput 14(1):44–51Lewis JR (1995) Ibm computer usability satisfaction questionnaires: psychometric evaluation and instructions for use. Int J Hum Comput Interact 7(1):57–78Lugmayr A, Risse T, Stockleben B, Laurila K, Kaario J (2009) Semantic ambient media—an introduction. Multimed Tools Appl 43(3):337–359Mattern F (2003) From smart devices to smart everyday objects. In: Proc. Smart Objects Conf. (SOC 03). Springer, pp 15–16Morin B, Barais O, Jezequel JM, Fleurey F, Solberg A (2009) Models run.time to support dynamic adaptation. Comput 42(10):44–51Nelson L, Churchill EF (2005) User experience of physical-digital object systems: implications for representation and infrastructure. Paper presented at smart object systems workshop, in cojunction with ubicomp 2005Paternò F (2002) Concurtasktrees: an engineered approach to model-based design of interactive systems. In: L.E. Associates (ed) The handbook of analysis for human-computer interaction, pp 483–500Paternò F (2003) From model-based to natural development. HCI International, pp 592–596Ramchurn SD, Deitch B, Thompson MK, Roure DCD, Jennings NR, Luck M (2004) Minimising intrusiveness in pervasive computing environments using multi-agent negotiation. MobiQuitous ’04, pp 364–372Runeson P, Höst M (2009) Guidelines for conducting and reporting case study research in software engineering. 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An Investigation into Trust & Reputation for Agent-Based Virtual Organisations

Trust is a prevalent concept in human society. In essence, it concerns our reliance on the actions of our peers, and the actions of other entities within our environment. For example, we may rely on our car starting in the morning to get to work on time, and on the actions of our fellow drivers, so that we may get there safely. For similar reasons, trust is becoming increasingly important in computing, as systems, such as the Grid, require computing resources to work together seamlessly, across organisational and geographical boundaries (Foster et al., 2001). In this context, the reliability of resources in one organisation cannot be assumed from the point of view of another. Moreover, certain resources may fail more often than others, and for this reason, we argue that software systems must be able to assess the reliability of different resources, so that they may choose which resources to rely upon. With this in mind, our goal here is to develop a mechanism by which software entities can automatically assess the trustworthiness of a given entity (the trustee). In achieving this goal, we have developed a probabilistic framework for assessing trust based on observations of a trustee's past behaviour. Such observations may be accounted for either when they are made directly by the assessing party (the truster), or by a third party (reputation source). In the latter case, our mechanism can cope with the possibility that third party information is unreliable, either because the sender is lying, or because it has a different world view. In this document, we present our framework, and show how it can be applied to cases in which a trustee's actions are represented as binary events; for example, a trustee may cooperate with the truster, or it may defect. We place our work in context, by showing how it constitutes part of a system for managing coalitions of agents, operating in a grid computing environment. We then give an empirical evaluation of our method, which shows that it outperforms the most similar system in the literature, in many important scenarios

Developing Unobtrusive Mobile Interactions: a Model Driven Engineering approach

In Ubiquitous computing environments, people are surrounded by a lot of embedded services. With the inclusion of pervasive technologies such as sensors or GPS receivers, mobile devices turn into an effective communication tool between users and the services embedded in their environment. All these services compete for the attentional resources of the user. Thus, it is essential to consider the degree in which each service intrudes the user mind when services are designed. In order to prevent service behavior from becoming overwhelming, this work, based on Model Driven Engineering foundations, is devoted to develop services according to user needs. In this thesis, we provide a systematic method for the development of mobile services that can be adapted in terms of obtrusiveness. That is, services can be developed to provide their functionality at different obtrusiveness levels by minimizing the duplication of efforts. For the system specification, a modeling language is defined to cope with the particular requirements of the context-aware user interface domain. From this specification, following a sequence of well-defined steps, a software solution is obtained.Gil Pascual, M. (2010). Developing Unobtrusive Mobile Interactions: a Model Driven Engineering approach. http://hdl.handle.net/10251/12745Archivo delegad

Personalization for unobtrusive service interaction

Increasingly, mobile devices play a key role in the communication between users and the services embedded in their environment. With ever greater number of services added to our surroundings, there is a need to personalize services according to the user needs and environmental context avoiding service behavior from becoming overwhelming. In order to prevent this information overload, we present a method for the development of mobile services that can be personalized in terms of obtrusiveness (the degree in which each service intrudes the user's mind) according to the user needs and preferences. That is, services can be developed to provide their functionality at different obtrusiveness levels depending on the user by minimizing the duplication of efforts. On the one hand, we provide mechanisms for describing the obtrusiveness degree required for a service. 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