Adaptive User Interfaces Based on Models and Software
Adaptive User Interfaces Based on Models and Software Agents Víctor M. López Jaquero Escuela Politécnica Superior de Albacete Departamento de Sistemas Informáticos Universidad de Castilla-La Mancha Campus Universitario, s/n. 02071 – Albacete (SPAIN) Email: victor@info-ab. uclm. es Supervisors: Dr. Pascual González López Dr. Antonio Fernández Caballero October, 2005 (Albacete) 1
CONTENTS 1. 2. 3. 4. 5. October, 2005 (Albacete) Introduction State of Art in Adaptive User Interfaces Design AB-UIDE: A Method for Adaptive UIs Design A MAS Architecture for UI Adaptation Final Remarks 2
CONTENTS 1. Introduction 1. Motivation 2. Objectives 2. 3. 4. 5. October, 2005 (Albacete) State of Art in Adaptive User Interfaces Design AB-UIDE: A Method for Adaptive UIs Design A MAS Architecture for UI Adaptation Final Remarks 3
MOTIVATION § Interaction is changing, and it will keep on changing. . . Different Platforms Macintosh Wintel October, 2005 (Albacete) Different Capabilities PDA PC Different Contexts Different Users In the streets Expert users At Home Rookie users 4
MOTIVATION § Interaction is changing, and it will keep on changing. . . Different Platforms Macintosh Wintel Different Capabilities PDA PC Different Contexts Different Users In the streets Expert users At Home Rookie users There are different platforms October, 2005 (Albacete) 5
MOTIVATION § Interaction is changing, and it will keep on changing. . . Different Platforms Macintosh Wintel Different Capabilities PDA PC Different Environments Different Users In the streets Expert users At Home Rookie users They have different capabilities October, 2005 (Albacete) 6
MOTIVATION § Interaction is changing, and it will keep on changing. . . Different Platforms Macintosh Wintel Different Capabilities PDA PC Different Enviroments Different Users In the streets Expert users At Home Rookie users They are used in different environments October, 2005 (Albacete) 7
MOTIVATION § Interaction is changing, and it will keep on changing. . . Different Platforms Macintosh Wintel Different Capabilities PDA PC Different Environments Different Users In the streets Expert users At Home Rookie users They are used by different users October, 2005 (Albacete) 8
MOTIVATION § Interaction is changing, and it will keep on changing. . . Different Platforms Macintosh Wintel Different Capabilities PDA PC Different Environments Different Users In the streets Expert users At Home Rookie users We need to face designing user interfaces able to work under these different situations (adaptive user interfaces) October, 2005 (Albacete) 9
MOTIVATION § Design for different situations – One interface per situation considered • High monetary cost • High maintenance cost • Impossible to consider all the possible situations! – A single user interface able to adapt to all (or at least many) situations • Easy to keep consistency between versions • Lower maintainace cost • Lower monetary cost October, 2005 (Albacete) 10
MOTIVATION § Design for different situations – One interface per situation considered • High monetary cost • High maintenance cost • Impossible to consider all the possible situations! – A single user interface able to adapt to all (or at least many) situations • Easy to keep consistency between versions • Lower maintainace cost • Lower monetary cost October, 2005 (Albacete) 11
MOTIVATION § Hardcoded adaptation vs. Engineered adaptation – Hardcoded adaptation rules • • Adaptation knowledge reusing is hard Difficult to modify adaptation rules Hard to apply methodological processes Multi-platform development is almost handmade – Engineered adaptation • • October, 2005 (Albacete) Adaptation knowledge can be reused A standard manner of editing adaptation rules Adaptation can be included within a methodological process Adaptation code can be automatically generated 12
MOTIVATION § Hardcoded adaptation vs. Engineered adaptation – Hardcoded adaptation rules • • Adaptation knowledge reusing is hard Difficult to modify adaptation rules Hard to apply methodological processes Multi-platform development is almost handmade – Engineered adaptation • • October, 2005 (Albacete) Adaptation knowledge can be reused A standard manner of editing adaptation rules Adaptation can be included within a methodological process Adaptation code can be automatically generated 13
OBJECTIVES § Design adaptive user interfaces able to adapt to: – – User’s skills, preferences or characteristics The platform where the application is running on The physical environment where the interaction takes place The adaptation process should preserve the usability § Include adaptation within a development process – Reuse adaptation knowledge – A standard manner of editing adaptation rules – Adaptation code can be automatically generated § An architecture for adaptive user interfaces execution – Execute designed adaptive user interfaces – At any time apply the best possible adaptation – Support multi-platform development October, 2005 (Albacete) 14
CONTENTS 1. Introduction 2. State of Art in Adaptive User Interfaces Design 1. 2. 3. 4. 5. User Interfaces Design Model-Based User Interfaces Design (MB-UID) Adaptation in MB-UID Adaptation process Software Agents in User Interfaces Design 3. AB-UIDE: A Method for Adaptive UIs Design 4. A MAS Architecture for UI Adaptation 5. Final Remarks October, 2005 (Albacete) 15
STATE OF ART § User interfaces design approaches Hard and tedious programming task. Very low level of abstraction. – Language based approaches: the user interfaces is built by programming it using a general purpose language (C/C++, Java, Pascal, etc). – User interfaces integrated development environments: they allow the design of the user interface interactively by means of graphical tools (Borland Delphi, Borland JBuilder, Microsoft Visual Basic, . . . ). – Model-based user interfaces development environments: they allow the specification of user interfaces out of a set of declarative models. October, 2005 (Albacete) 16
STATE OF ART § User interfaces design approaches Hard to apply a methodological approach. Low level of abstraction. – Language based approaches: the user interfaces is built by programming the user interface using a general purpose language (C/C++, Java, Pascal, etc). – User interfaces integrated development environments: they allow the design of the user interface interactively by means of graphical tools (Borland Delphi, Borland JBuilder, Microsoft Visual Basic, . . . ). – Model-based user interfaces development environments: they allow the specification of user interfaces out of a set of declarative models. October, 2005 (Albacete) 17
STATE OF ART § User interfaces design approaches – Language based approaches: the user interfaces is built by programming the user interface using a general purpose language (C/C++, Java, Pascal, etc). – User interfaces integrated development environments: they Higher level of abstraction. Easier to maintain. allow the design of the user interface interactively by means of Automatic code generation. graphical tools (Borland Delphi, Borland JBuilder, Microsoft Methodological approach. Visual Basic, . . . ). – Model-based user interfaces development environments: they allow the specification of user interfaces out of a set of declarative models. October, 2005 (Albacete) 18
STATE OF ART § Model-based user interfaces design – Based on a set of declarative models • Task model • Domain model • Context of use model – user, platform and environment • Abstract user interface model • Concrete user interface model • Final user interface model – The models are transformed into an executable/interpretable presentation automatically or semiautomatically. October, 2005 (Albacete) 19
STATE OF ART § Adaptation in model-based user interfaces design – Each approach allows the adaptation of some specific features: • • Context aware help systems Look & Feel Navigation Many of them support no adaptation. – Most of the adaptations are personalizations – No language to specify new adaptations – No intelligent adaptation process October, 2005 (Albacete) 20
STATE OF ART § Adaptation process can be fired by either the user (adaptability) or the system (adaptivity). Initiative stage Detect Platform Changes Detect User’s Goals Detect User’s Needs Detect Environment Changes Proposal for Adaptation Proposal stage Select Adaptation Decision stage Execute Adaptation October, 2005 (Albacete) User initiated adaptation Execution stage 21
STATE OF ART § Adaptation process can be fired by either the user (adaptability) or the system (adaptivity). Initiative stage Detect Platform Changes Detect User’s Goals Detect User’s Needs Detect Environment Changes Proposal for Adaptation Proposal stage Select Adaptation Decision stage Execute Adaptation October, 2005 (Albacete) User initiated adaptation Execution stage 22
STATE OF ART § Adaptation process Propose feasible adaptations given the current situation and state of interaction. October, 2005 (Albacete) 23
STATE OF ART § Adaptation process Select the best adaptations among the proposed adaptations. October, 2005 (Albacete) 24
STATE OF ART § Adaptation process Execute the selected adaptations. October, 2005 (Albacete) 25
STATE OF ART The process requires reasoning about which adaptation to fire, choose the best adaptations, . . § Adaptation process October, 2005 (Albacete) Multi-agent systems 26
STATE OF ART § Software agents in user interfaces – Interface agents dwell in the user interface to improve user’s interaction experience. Our agents use BDI mental model. BDI model is a natural manner to deal with the required decision mechanism to execute adaptive UIs. October, 2005 (Albacete) 27
STATE OF ART § Software agents in user interfaces – The design of multi-agent systems require new methodological approches: We used Prometheus because: • Extensions of Object Oriented / Knowledge • It supports the whole software life cycle. Engineering methods and techniques • Widely used. – – – – – October, 2005 (Albacete) • It provides a visual design tool. Tropos • Code generation for JACK and JADE. Gaia AUML OASIS Prometheus Desire MAS-Common. KADS INGENIAS. . . 28
CONTENTS 1. Introduction 2. State of Art in Adaptive User Interfaces Design 3. AB-UIDE: A Method for Adaptive UIs Design 1. 2. 3. 4. 5. A Study Case: ATM UI Requirements Analysis stage Design stage Implementation stage 4. A MAS Architecture for UI Adaptation 5. Final Remarks October, 2005 (Albacete) 29
AB-UIDE: A Method for Adaptative UIs Design § AB-UIDE (Agent Based User Interface Development Environment) extends usual model-based user interface development methods to support the development of adaptive user interfaces in a seamless way. – User-centred approach – Iterative – Covers the whole development life cycle of the user interface – The adaptive user interfaces designed are executed on an agent-based adaptation engine. October, 2005 (Albacete) 30
AB-UIDE: A Method for Adaptative UIs Design § AB-UIDE stages: October, 2005 (Albacete) 31
AB-UIDE: A Method for Adaptative UIs Design § A study case: ATM UI – ATM UI is a user interface for an automatic teller machine, where the user can: • • • Withdraw money Make a deposit Transfer money Recharge a cell phone Get the account statement Change the preferences for the application – The user interface should be able to run on different platforms (bank platform and mobile platform). October, 2005 (Albacete) 32
AB-UIDE: A Method for Adaptative UIs Design § Requirements analysis stage – Use case model • Use case sequence diagram – “Static” context of use model • User • Platform • Environment October, 2005 (Albacete) 33
AB-UIDE: A Method for Adaptative UIs Design § Requirements analysis stage – Use case model October, 2005 (Albacete) 34
AB-UIDE: A Method for Adaptative UIs Design § Requirements analysis stage – Use case model • Use case sequence diagram October, 2005 (Albacete) 35
AB-UIDE: A Method for Adaptative UIs Design § Requirements analysis stage – “Static” context of use model • User • Platform • Environment October, 2005 (Albacete) 36
AB-UIDE: A Method for Adaptative UIs Design § Analysis stage – Domain model – Roles model – Usability trade-off October, 2005 (Albacete) 37
AB-UIDE: A Method for Adaptative UIs Design § Analysis stage – Domain model October, 2005 (Albacete) 38
AB-UIDE: A Method for Adaptative UIs Design § Analysis stage – Roles model October, 2005 (Albacete) 39
AB-UIDE: A Method for Adaptative UIs Design § Analysis stage – Usability trade-off Usability criteria to be preserved. BANK ATM October, 2005 (Albacete) PDA Weight of the criterium in the usability trade-off. 40
AB-UIDE: A Method for Adaptative UIs Design § Design stage – Adaptivity rules – Task model – Interaction objects specification AIO AIO – Abstract User Interface (AUI) – Concrete User Interface (CUI) CIO CIO Connector model October, 2005 (Albacete) 41
AB-UIDE: A Method for Adaptative UIs Design § Design stage Transitions are labelled to specify the dialog. – Task model October, 2005 (Albacete) 42
AB-UIDE: A Method for Adaptative UIs Design § Design stage Actions and tasks – temporal relationships are described by using LOTOS operators (as defined in CTT). Task model Tasks and actions are described specifying a set of properties to help on UI generation. October, 2005 (Albacete) 43
AB-UIDE: A Method for Adaptative UIs Design § Design stage – Interaction objects specification Login (1, 1) Pin Name Login Type String Initial value (1, 1) Name Type Pin String Initial value Password October, 2005 (Albacete) “” “” true 44
AB-UIDE: A Method for Adaptative UIs Design § Design stage – Abstract User Interface (AUI) AUI consists of AIOs: Inputters, Displayers, Editors, Action. Invokers and Selectors. The AIOs are grouped in containers, that help on deciding a good final layout for the UI elements. Login (1, 1) Pin (1, 1) Free. Container Login Pin OK October, 2005 (Albacete) 45
AB-UIDE: A Method for Adaptative UIs Design § Design stage – Concrete User Interface (CUI) Free. Container Login CUI consists of CIOs are derived from AIOs and Interaction Objects. Login Pin OK Window Login box Login text. Component Name=“login. Label” is. Editable=false default. Content=“Login” Events represent the behaviour of the system. October, 2005 (Albacete) Name=“pin. Label” is. Editable=false default. Content=“Pin” button Name=“OK” Name=“Login” is. Editable=true default. Content=“” Name=“Pin” is. Editable=true default. Content=“” Event postcondition Name = “event 010” Name=“postcondition 004” device=“mouse” event. Type=“On. Click” expression=“Customer. check. Login()” 46
AB-UIDE: A Method for Adaptative UIs Design § Design stage – Conectors model Graphical relationship. • Automatically generated Mapping between CUI and AUI. Mapping between AUI and Domain model. October, 2005 (Albacete) 47
AB-UIDE: A Method for Adaptative UIs Design § Design stage Sensors model the information captured from the context of use. – Adaptivity Rules October, 2005 (Albacete) 48
AB-UIDE: A Method for Adaptative UIs Design § Design stage Context events are produced by one or several sensors. They trigger adaptivity rules. – Adaptivity Rules October, 2005 (Albacete) 49
AB-UIDE: A Method for Adaptative UIs Design § Design stage – Adaptivity Rules October, 2005 (Albacete) Adaptivity rules will be available to be applied if the context precondition is met. The “real” adaptation is described by means of graph grammars transformations rules. 50
AB-UIDE: A Method for Adaptative UIs Design § Design stage – Adaptivity Rules SENSOR CONTEXT EVENT ADAPTIVITY RULE October, 2005 (Albacete) 51
AB-UIDE: A Method for Adaptative UIs Design § Implementation stage – User interface specification • User Interface e. Xtensible Mark-Up Language • Stores the whole user interface specification • The specification is rendered for the target platform – Adaption engine • Multi-agent system based architecture • Takes advantage of the user interface specification for the application of adaptations • The architecture applies the adaptation facilities defined in the design process October, 2005 (Albacete) 52
CONTENTS 1. 2. 3. 4. Introduction State of Art in Adaptive User Interfaces Design AB-UIDE: A Method for Adaptive UIs Design A MAS Architecture for UI Adaptation 1. 2. 3. 4. 5. Initiative stage Proposal stage Decision stage Execution stage Implementing the MAS architecture 5. Final Remarks October, 2005 (Albacete) 53
A MAS ARCHITECTURE FOR UI ADAPTATION Context : : = Adaptivity rules Usability trade-off Platform Environment Current UI Multi-Agent System User Task October, 2005 (Albacete) Adapted UI 54
A MAS ARCHITECTURE FOR UI ADAPTATION § Multi-agent system goals Adaptation process stages have been refined to design the goals for the multi-agent system. October, 2005 (Albacete) 55
A MAS ARCHITECTURE Dispatcher. Agent and Agent. Context. Of. Use sense the context of use by means of the designed sensors. FOR UI ADAPTATION § Multi-agent system overview October, 2005 (Albacete) 56
A MAS ARCHITECTURE FOR UI ADAPTATION § Multi-agent system overview Agent. Context. Platform, Agent. Contex. User and Agent. Context. Environment process the incoming data and produce the context events. October, 2005 (Albacete) 57
A MAS ARCHITECTURE FOR UI ADAPTATION The MAS uses all the§ Multi-agent system overview knowledge about the UI collected at design time. Agent. Adaptation. Process proposes the plausible adaptations, selects the best ones and executes them. October, 2005 (Albacete) 58
A MAS ARCHITECTURE FOR UI ADAPTATION § Initiative stage – Adaptation can be initiated by: • The user (adaptability) • The system (adaptivity) – System initiated adaptation • Sensing the context of use – Sensors detect the events produced in the context » Software sensors » Hardware sensors • Detecting the user’s current goal – What is the task the user is carrying out at a moment? – Recurrent task sequences – Heuristics based on the interaction data collected October, 2005 (Albacete) 59
A MAS ARCHITECTURE FOR UI ADAPTATION § Proposal stage – A set of plausible adaptations for the current situation is proposed. – The possible adaptations to be applied are those adaptivity rules specified at design time. Adaptivity rules – The adaptation applicable given a context of use change are those that: • Are fired by the context events produced by the changes in the incoming sensors data. • The context precondition is met. October, 2005 (Albacete) 60
A MAS ARCHITECTURE FOR UI ADAPTATION § Decision stage – How to choose the best adaptation (plan) among the proposed ones • Compute how good or bad an adaptation (plan) is for the user: – Migration cost: represents the physical, cognitive and conative effort the user needs to apply in order to migrate from one context to another. – Adaptation benefit: represents how good an adaptation will be for the user in the new context. • Choose the one that maximizes: Adaptation benefit – Migration cost October, 2005 (Albacete) 61
A MAS ARCHITECTURE FOR UI ADAPTATION § Decision stage – Migration cost: represents the physical, cognitive and conative effort the user needs to apply in order to migrate from one context to another. User’s mental effort required to resume the task that was carrying out before adaptation took place. October, 2005 (Albacete) 62
A MAS ARCHITECTURE FOR UI ADAPTATION § Decision stage – Migration cost: represents the physical, cognitive and conative effort the user needs to apply in order Amount of information the user to migrate from one context to another. needs to understand to perform the tasks using the adapted user interface. October, 2005 (Albacete) 63
A MAS ARCHITECTURE FOR UI ADAPTATION § Decision stage – October, 2005 (Albacete) They are assessed by means of metrics based on the empirical Migration cost: represents the physical, cognitive results from GOMS-based and conative effort the user needs to apply in order (Goals, Operators, Methods, Selection rules) evaluations. to migrate from one context to another. 64
A MAS ARCHITECTURE FOR UI ADAPTATION § Decision stage – Migration cost: represents the physical, cognitive and conative effort the user needs to apply in order to migrate from one context to another. Preferences modify the other two parameters evaluation. October, 2005 (Albacete) 65
A MAS ARCHITECTURE FOR UI ADAPTATION § Decision stage – Adaptation benefit: represents how good an adaptation will be for the user in the new context. When a context of use situation is often found, the cost should be reduced since it will allow dealing with common situations. The adaptations can be rejected by the user. The more times the user rejects an adaptation the less likely that adaptation will be. October, 2005 (Albacete) 66
A MAS ARCHITECTURE FOR UI ADAPTATION § Proposal stage – Because of the limitations of the model the system needs to evolve at run time to improve adaptation process. This evolution has been included as Bayesian learning (as in antispam filters, for instance). – The formula below will be applied for each selectable adaptation (producing a ranking of rules). P(R|S) quantifies the compatibility between the hypothesis (the adaptation selection) and the contents of the adaptation (the adaptation itself). P(S|R) represents the probability that when R is applicable, R is choosed. October, 2005 (Albacete) P(S) represents the a priori probability that R is selected to be applied. P(R) represents the probability of R. 67
A MAS ARCHITECTURE FOR UI ADAPTATION § Execution stage – The system executes the first adaptation in the ranking by means of the transformation engine. – The system checks that the application of the adaptation doesn’t violate the usability trade-off for the current platform profile created at design-time. – If the adaptation violates the usability trade-off • Undo last adaptation • Repeat the execution and usability trade-off checking processes for the next adaptation in the ranking until: – One adaptation meets usability trade-off – Adaptation ranking list is empty (no adaptation could be applied) – An adaptation is found where ranking value is too low October, 2005 (Albacete) 68
A MAS ARCHITECTURE FOR UI ADAPTATION § Execution stage Translate the UI graph representation into usi. XML syntax. Translate the XML specification into a graph representation. Apply the graph grammar transformations on the UI graph representation. October, 2005 (Albacete) Render the usi. XML specification for the target platform. 69
CONTENTS 1. 2. 3. 4. 5. Introduction State of Art in Adaptive User Interfaces Design AB-UIDE: A Method for Adaptive UIs Design A MAS Architecture for UI Adaptation Final Remarks 1. Conclusions 2. Contributions 3. Future work October, 2005 (Albacete) 70
FINAL REMARKS § Conclusions & Outcomes – An adaptive UI design method (AB-UIDE) – Adaptive user interfaces execution October, 2005 (Albacete) 71
FINAL REMARKS § Conclusions & Outcomes – An adaptive UI design method (AB-UIDE) • A specification to capture context data through sensors modelling. • A metamodel for adaptivity rules to provide a common syntax for adaptations specification. • A runtime quality model (usability trade-off) to preserve usability while adapting the user interface. • A task model enriched with dialog specification. • An abstract user interface (AUI) model and a set of heuristics to transform the domain and task/dialog model into the AUI and the CUI. • A graphical syntax for model-to-model mapping that allows preserving traceability in the development process. – Adaptive user interfaces execution October, 2005 (Albacete) 72
FINAL REMARKS § Conclusions & Outcomes – An adaptive UI design method (AB-UIDE) – Adaptive user interfaces execution • An architecture based on multi-agent system for adaptive user interfaces execution. • The integration of the adaptation facilities designed following AB-UIDE within the architecture in a seamless way. • A model to assess how good or bad an adaptation is given a context of use state. • The implementation of the MAS architecture proposed. • The implementation of a tool for the transformation of user interfaces specifications by means of graph grammars transformations rules. October, 2005 (Albacete) 73
FINAL REMARKS § Acknowledgements – This work has been supported by • The spanish grants: – CYCIT TIN 2004 -08000 -C 03 -01 project – JCCM PBC-03 -003 project • European networks – SIMILAR Network of Excellence – Seven month stay at BCHI (Belgian laboratory of Computer Human Interaction). October, 2005 (Albacete) 74
FINAL REMARKS § Contributions – Topics • Adaptive user interfaces development related papers • Multi-agent systems related papers • Study cases related papers October, 2005 (Albacete) 75
FINAL REMARKS § Contributions – Adaptive user interfaces development related papers (i) • López-Jaquero, V. , Montero, F. , Molina, J. P. , González, P. , Fernández-Caballero, A. A Seamless Development Process of Adaptive User Interfaces Explicitly Based on Usability Properties. Proc. of 9 th IFIP Working Conference on Engineering for Human-Computer Interaction jointly with 11 th Int. Workshop on Design, Specification, and Verification of Interactive Systems EHCI-DSVIS’ 2004 (Hamburg, July 11 -13, 2004). Lecture Notes in Computer Science, Vol. 3425, Springer-Verlag, Berlin, 2005. • López Jaquero, V. , Montero, F. , Fernández Caballero, A. , Lozano, M. D. Towards Adaptive User Interfaces Generation: One Step Closer to People. In Enterprise Information Systems V. Kluwert Academia Publishers, Dordrecht, Holanda, 2004. pp. 226 -232. ISBN: 1 -4020 -1726 -X. • López Jaquero, V. , Montero, F. , Molina, J. P. , Fernández-Caballero, A. , González, P. Model-Based Design of Adaptive User Interfaces through Connectors. Design, Specification and Verification of Interactive Systems 2003, DSV-IS 2003. In DSV-IS 2003 : Issues in Designing New-generation Interactive Systems Proceedings of the Tenth Workshop on the Design, Specification and Verification of Interactive Systems. J. A. Jorge, N. J. Nunes, J. F. Cunha (Eds). Springer Verlag, LNCS 2844, 2003. Madeira, Portugal June 4 -6, 2003. • López Jaquero, V. , Montero, F. , Fernández, A. , Lozano, M. Towards Adaptive User Interface Generation: One Step Closer To People. 5 th International Conference on Enterprise Information Systems, ICEIS 2003. Proccedings of 5 th International Conference on Enterprise Information Systems, ICEIS 2003, vol. 3, pp. 97103. Angers, France, April 23 -26, 2003. • Montero, F. , López Jaquero, V. , Molina, J. P. , González, P. An approach to develop User Interfaces with plasticity. Design, Specification and Verification of Interactive Systems 2003, DSV-IS 2003. In DSV-IS 2003 : Issues in Designing New-generation Interactive Systems Proceedings of the Tenth Workshop on the Design, Specification and Verification of Interactive Systems. J. A. Jorge, N. J. Nunes, J. F. Cunha (Eds). Springer Verlag, LNCS 2844, 2003. Madeira, Portugal June 4 -6, 2003. October, 2005 (Albacete) 76
FINAL REMARKS § Contributions – Adaptive user interfaces development related papers (ii) • Limbourg, Q. , Vanderdonckt, J. , Michotte, B. , Bouillon, L. , López-Jaquero, V. , Usi. XML: a Language Supporting Multi-Path Development of User Interfaces, Proc. of 9 th IFIP Working Conference on Engineering for Human-Computer Interaction jointly with 11 th Int. Workshop on Design, Specification, and Verification of Interactive Systems EHCI-DSVIS’ 2004 (Hamburg, July 11 -13, 2004). Lecture Notes in Computer Science, Vol. 3425, Springer-Verlag, Berlin, 2005, pp. 207 -228. • Montero, F. , López-Jaquero, V. , Vanderdonckt, J. , González, P. , Lozano, M. D. , Solving the Mapping Problem in User Interface Design by Seamless Integration in Ideal. XML. 12 th International Workshop on Design, Specification and Verification of Interactive Systems (DSV-IS’ 2005), Newcastle upon Tyne, England, July 13 -15, 2005. Springer-Verlag, Berlin, 2005 (in print). • Montero, F. , López-Jaquero, V. , Lozano, M. , González, P. A User Interfaces Development and Abstraction Mechanism. Artículo seleccionado en el V Congreso Interacción Persona Ordenador para su publicación en Springer-Verlag, Berlin, 2005 (in print). October, 2005 (Albacete) 77
FINAL REMARKS § Contributions – Multi-agent systems related papers • López-Jaquero, V, Montero, F. , Molina, J. P. , González, P. , Fernández-Caballero, A. A Multi-Agent System Architecture for the Adaptation of User Interfaces. 4 th International Central and Eastern European Conference on Multi-Agent Systems (CEEMAS 2005). 15 -17 September 2005, Budapest, Hungary. In Multi -Agents Systems and Applications IV. M. Pechoucek, P. Petta, L. Zsolt Varga (Eds. ) LNAI 3690, Springer. Verlag, Berlin. • López-Jaquero, V. , Fernández-Caballero, A. Métricas de Usabilidad y Sistemas Multiagente en Hipermedia Adaptativa. XIII Escuela de Verano de Informática. Tendencias Actuales en la Interacción Persona. Ordenador: Accesibilidad, Adaptabilidad y Nuevos Paradigmas. ISBN: 84 -921873, pp. 21 -34, Albacete, España, 2003. • Fernández-Caballero, A. , López Jaquero, V. , Montero, F. , González, P. Adaptive Interaction Multi-agent Systems in E-learning/E-teaching on the Web. International Conference on Web Engineering, ICWE 2003. In Web Engineering: International Conference, ICWE 2003, Oviedo, Spain, July 14 -18, 2003. Proceedings. J. M. Cueva Lovelle, B. M. González Rodríguez, L. Joyanes Aguilar, J. E. Labra Gayo, M. del Puerto Paule Ruiz (Eds. ). Springer Verlag, LNCS 2722, pp. 144 -154. ISSN: 0302 -9743. Oviedo, Spain, June, 2003. • López Jaquero, V. , Montero, F. , Fernández, A. , Lozano, M. Usability Metrics in Agent-Based Intelligent Tutoring Systems. Human-Computer Interaction: Theory and Practice (part 1). J. Jacko, C. Stephanidis (Eds. ). Lawrence Erlbaum Associates. Londrés, Reino Unido, 2003. ISBN: 0 -8058 -4931 -9. pp. 539 -543. October, 2005 (Albacete) 78
FINAL REMARKS § Contributions – Study cases related papers • Robles, A. , Molina, J. P. , López-Jaquero, V. , García, A. S. Even Better Than Reality: The Development of a 3 -D Online Store that Adapts to Every User and Every Platform. HCI International 2005, Las Vegas, Nevada, USA, July, 2005. Volume 7 - Universal Access in HCI: Exploring New Interaction Environments. • López-Jaquero, V. , Fernández-Caballero, A. , Montero, F. , Molina, J. P. , González, P. Towards Adaptive Elearning / E-teaching on the Web. International Conference on Technology-Enhanced Learning (TEL 2003). Procedings of International Conference on Technology-Enhanced Learning (TEL 2003). Milán, Italia, noviembre, 2003. • González, P. , Montero, F. , López Jaquero, V. , Fernández, A. , Montañés, J. , Sánchez, T. A Virtual Learning Environment for Short Age Children. IEEE International Conference on “Advanced Learning Technologies”, ICALT 2001. Proccedings of the IEEE International Conference on Advanced Learning Technologies, ICALT 2001, Okamoto, T. , Hartley, R. , Kinshuk, Klus, J. (eds. ). IEEE Computer Society, Los Alamitos, CA. , Agosto 2001, pp. 283 -285. ISBN: 0 -7695 -1013 -2. Madison, USA, August 6 -8, 2001. October, 2005 (Albacete) 79
FINAL REMARKS § Future work – Collaborative adaptive user interfaces – Adaptation in virtual environments – Visual and intuitive graphical tools for adaptivity rules design – Creating a corpus of adaptiviy rules big enough – Porting the multi-agent system to a open source agent language like JADE. – Adding user modelling techniques to make user model evolve automatically by inference. – Make some more usability tests for adaptive user interfaces designed and executed by using our approach. October, 2005 (Albacete) 80
QUESTIONS & ANSWERS Adaptive User Interfaces Based on Models and Software Agents Víctor M. López Jaquero Escuela Politécnica Superior de Albacete Departamento de Sistemas Informáticos Universidad de Castilla-La Mancha Campus Universitario, s/n. 02071 – Albacete (SPAIN) Email: victor@info-ab. uclm. es Thanks for your attention October, 2005 (Albacete) 81
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