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. On the other hand, we make use of Feature Modeling techniques in order to define the obtrusiveness level adaptation in a declarative manner. An experiment was conducted in order to put in practice the proposal and evaluate the user acceptance for the personalization capabilities provided by our approach. © Springer-Verlag London Limited 2011.This work has been developed with the support of MICINN under the project EVERYWARE TIN2010-18011 and co-financed with ERDF, in the grants program FPU.Gil Pascual, M.; Giner Blasco, P.; Pelechano Ferragud, V. (2012). Personalization for unobtrusive service interaction. Personal and Ubiquitous Computing. 16(5):543-561. https://doi.org/10.1007/s00779-011-0414-0S543561165Abrams M, Phanouriou C, Batongbacal AL, Williams SM, Shuster JE (1999) Uiml: an appliance-independent xml user interface language. In: WWW ’99. Elsevier, North-Holland, pp 1695–1708Ballagas R, Borchers J, Rohs M, Sheridan JG (2006) The smart phone: a ubiquitous input device. IEEE Pervas Comput 5(1):70Balme L, Demeure A, Barralon N, Coutaz J, Calvary G (2004) Cameleon-rt: a software architecture reference model for distributed, migratable, and plastic user interfaces. In: EUSAI, pp 291–302Benavides D, Cortés RA, Trinidad P (2005) Automated reasoning on feature models. In: LNCS, advanced information systems engineering: 17th international conference, CAiSE 2005 3520, pp 491–503Blomquist A, Arvola M (2002) Personas in action: ethnography in an interaction design team. In: Proceedings of NordiCHI ’02. ACM, New York, NY, pp 197–200Bright A, Kay J, Ler D, Ngo K, Niu W, Nuguid A (2005) Adaptively recommending museum tours. In: Nick Ryan Tullio Salmon Cinotti GR (ed) Proceedings of workshop on smart environments and their applications to cultural heritage. Archaeolingua, pp 29–32Brown DM (2010) Communicating design: developing web site documentation for design and planning, 2nd edn. New Riders Press, USACalvary G, Coutaz J, Thevenin D, Limbourg Q, Bouillon L, Vanderdonckt J (2003) A unifying reference framework for multi-target user interfaces. Interact Comput 15(3):289–308Cetina C, Giner P, Fons J, Pelechano V (2009) Autonomic computing through reuse of variability models at runtime: the case of smart homes. Computer 42(10):37–43Chatfield C, Carmichael D, Hexel R, Kay J, Kummerfeld B (2005) Personalisation in intelligent environments: managing the information flow. In: OZCHI ’05. Computer-human interaction special interest group of Australia, pp 1–10Clerckx T, Winters F, Coninx K (2005) Tool support for designing context-sensitive user interfaces using a model-based approach. In: TAMODIA ’05: Proceedings of the 4th international workshop on Task models and diagrams. ACM Press, New York, pp 11–18Czarnecki K, Helsen S, Eisenecker U (2004) Staged configuration using feature models. In: Proceedings of SPLCDuarte C, Carriço L (2006) A conceptual framework for developing adaptive multimodal applications. In: Proceedings of IUI ’06. ACM, New York, pp 132–139Evans (2003) Domain-driven design: tacking complexity In the heart of software. Addison-Wesley Longman Publishing Co., Inc., BostonsFavre JM (2004) Foundations of model (Driven) (Reverse) engineering: models—Episode I: stories of the fidus papyrus and of the solarus. In: Bezivin J, Heckel R (eds) Language engineering for model-driven software development, no. 04101, Dagstuhl seminar proceedings. Dagstuhl, GermanyFischer G (2001) User modeling in human–computer interaction. User Model User-Adap Inter 11(1–2):65–86Gibbs WW (2005) Considerate computing. Scientific American 292(1):54–61Giner P, Cetina C, Fons J, Pelechano V (2010) Developing mobile workflow support in the internet of things. IEEE Pervas Comput 9(2):18–26Giner P, Cetina C, Fons J, Pelechano V (2011) Implicit interaction design for pervasive workflows. Pers Ubiquit Comput 1–10Gulliksen 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: Proceedings of the UIST ’01. ACM, New York, pp 191–192Ho J, Intille SS (2005) Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. In: Proceedings of CHI ’05. ACM, New York, 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(3):52–59Ju W, Leifer L (2008) The design of implicit interactions: making interactive systems less obnoxious. Des Issues 24(3):72–84Lewis JR (1995) Ibm computer usability satisfaction questionnaires: psychometric evaluation and instructions for use. Int J Hum-Comput Interact 7(1):57–78Limbourg Q, Vanderdonckt J, Michotte B, Bouillon L, López-Jaquero V (2004) Usixml: a language supporting multi-path development of user interfaces. In: EHCI/DS-VIS, pp 200–220Mao JY, Vredenburg K, Smith PW, Carey T (2001) User-centered design methods in practice: a survey of the state of the art. In: CASCON ’01. IBM Press, New York, p 12McCrickard DS, Chewar CM (2003) Attuning notification design to user goals and attention costs. Commun ACM 46:67–72Mori G, Paternò F, Santoro C (2002) Ctte: support for developing and analyzing task models for interactive system design. IEEE Trans Softw Eng 28(8):797–813Mori G, Paternò F, Santoro C (2004) Design and development of multidevice user interfaces through multiple logical descriptions. IEEE Trans Softw Eng 30(8):507–520Myers B, Hudson SE, Pausch R (2000) Past, present, and future of user interface software tools. ACM Trans Comput-Hum Interact 7(1):3–28OMG (2006) Business process modeling notation (BPMN) specification. OMG Final Adopted SpecificationPaternò F, Santoro C (2003) A unified method for designing interactive systems adaptable to mobile and stationary platforms. Interact Comput 15(3):349–366Puerta A, Eisenstein J (2002) Ximl: a common representation for interaction data. In: Proceedings of IUI ’02. ACM, New York, pp 214–215Ramchurn SD, Deitch B, Thompson MK, Roure DCD, Jennings NR, Luck M (2004) Minimising intrusiveness in pervasive computing environments using multi-agent negotiation. In: First international conference on mobile and ubiquitous systems, pp 364–372Rumbaugh J, Jacobson I, Booch G (1998) The unified modeling language reference manual. Addison-Wesley, LondonSchobbens PY, Heymans P, Trigaux JC, Bontemps Y (2007) Generic semantics of feature diagrams. Comput Networks 51(2):456–479Serral E, Pérez F, Valderas P, Pelechano V (2010) An end-user tool for adapting smart environment automation to user behaviour at runtime. In: Proceedings of UCAmI ’10Streefkerk JW, van Esch-Bussemakers MP, Neerincx MA (2006) Designing personal attentive user interfaces in the mobile public safety domain. Comput Hum Behav 22:749–770Tedre M (2008) What should be automated? Interactions 15(5):47–49Unger R, Chandler C (2009) A project guide to UX design: for user experience designers in the field or in the making. New Riders Publishing, Thousand OaksVan den Bergh J, Coninx K. Using uml 2.0 and profiles for modelling context-sensitive user interfaces. In: Proceedings of the MDDAUI2005 CEUR workshopVastenburg MH, Keyson DV, de Ridder H (2008) Considerate home notification systems: a field study of acceptability of notifications in the home. Pers Ubiquit Comput 12(8):555–566Vertegaal R (2003) Attentive user interfaces. Commun ACM 46(3):30–33Weiser M, Brown JS (1997) The coming age of calm technology, pp 75–85Weld DS, Anderson C, Domingos P, Etzioni O, Gajos K, Lau T, Wolf S (2003) Automatically personalizing user interfaces. In: IJCAI ’03, pp 1613–161

Logics of knowledge and action: critical analysis and challenges

International audienceWe overview the most prominent logics of knowledge and action that were proposed and studied in the multiagent systems literature. We classify them according to these two dimensions, knowledge and action, and moreover introduce a distinction between individual knowledge and group knowledge, and between a nonstrategic an a strategic interpretation of action operators. For each of the logics in our classification we highlight problematic properties. They indicate weaknesses in the design of these logics and call into question their suitability to represent knowledge and reason about it. This leads to a list of research challenges

Module checking for uncertain agents

Module checking is a decision problem proposed in late 1990s to formalize verification of open systems, i.e., systems thatmust adapt their behavior to the input they receive from the environment. It was recently shown that module checking offers a distinctly different perspective from the better-known problem of model checking. Module checking has been studied in several variants. Syntactically, specifications in temporal logic CTL and strategic logic ATL have been used. Semantically, the environment was assumed to have either perfect or imperfect information about the global state of the interaction. In this work, we rectify our approach to imperfect information module checking from the previous paper. Moreover, we study the variant of module checking where also the system acts under uncertainty. More precisely, we assume that the system consists of one or more agents whose decision making is constrained by their observational capabilities. We propose an automata-based verification procedure for the new problem, and establish its computational complexit