Adaptive User Interfaces Based on Models and Software Agents

1
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_at_info-ab.uclm.es

Supervisors Dr. Pascual González López Dr.
Antonio Fernández Caballero
2
CONTENTS

• 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

3
CONTENTS

• Introduction
• Motivation
• Objectives
• State of Art in Adaptive User Interfaces Design
• AB-UIDE A Method for Adaptive UIs Design
• A MAS Architecture for UI Adaptation
• Final Remarks

4
MOTIVATION

• Interaction is changing, and it will keep on
  changing ...

5
MOTIVATION

• Interaction is changing, and it will keep on
  changing ...

Different Platforms
Different Capabilities
Different Contexts
Different Users
Macintosh
PDA
Expert users
In the streets
Wintel
PC
At Home
Rookie users
There are different platforms
6
MOTIVATION

• Interaction is changing, and it will keep on
  changing ...

Different Platforms
Different Capabilities
Different Environments
Different Users
Macintosh
PDA
Expert users
In the streets
Wintel
PC
At Home
Rookie users
They have different capabilities
7
MOTIVATION

• Interaction is changing, and it will keep on
  changing ...

Different Platforms
Different Capabilities
Different Enviroments
Different Users
Macintosh
PDA
Expert users
In the streets
Wintel
PC
At Home
Rookie users
They are used in different environments
8
MOTIVATION

• Interaction is changing, and it will keep on
  changing ...

Different Platforms
Different Capabilities
Different Environments
Different Users
Macintosh
PDA
Expert users
In the streets
Wintel
PC
At Home
Rookie users
They are used by different users
9
MOTIVATION

• Interaction is changing, and it will keep on
  changing ...

Different Platforms
Different Capabilities
Different Environments
Different Users
Macintosh
PDA
Expert users
In the streets
Wintel
PC
At Home
Rookie users
We need to face designing user interfaces able to
work under these different situations (adaptive
user interfaces)
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

11
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

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
• 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
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
• 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

14
OBJECTIVES

• Design adaptive user interfaces able to adapt to
• Users 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

15
CONTENTS

• Introduction
• State of Art in Adaptive User Interfaces Design
• User Interfaces Design
• Model-Based User Interfaces Design (MB-UID)
• Adaptation in MB-UID
• Adaptation process
• Software Agents in User Interfaces Design
• AB-UIDE A Method for Adaptive UIs Design
• A MAS Architecture for UI Adaptation
• Final Remarks

16
STATE OF ART

• User interfaces design approaches
• 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.

Hard and tedious programming task. Very low level
of abstraction.
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 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.

Hard to apply a methodological approach. Low
level of abstraction.
18
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 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.

Higher level of abstraction. Easier to maintain.
Automatic code generation. Methodological
approach.
19
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.

20
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

21
STATE OF ART
Adaptation process can be fired by either the
user (adaptability) or the system (adaptivity).

• Adaptation process

Initiative stage
Initiative stage
Detect Platform Changes
Detect Platform Changes
Detect Users Goals
User initiated adaptation
Detect Users Goals
User initiated adaptation
Detect Environment
Detect Environment
Detect User Changes
Detect User Changes
Detect Users Needs
Detect Users Needs
Changes
Changes
Proposal for
Proposal for
Proposal stage
Proposal stage
Adaptation
Adaptation
Decision stage
Decision stage
Select Adaptation
Select Adaptation
Execution stage
Execution stage
Execute Adaptation
Execute Adaptation
22
STATE OF ART
Adaptation process can be fired by either the
user (adaptability) or the system (adaptivity).

• Adaptation process

Initiative stage
Initiative stage
Detect Platform Changes
Detect Platform Changes
Detect Users Goals
User initiated adaptation
Detect Users Goals
User initiated adaptation
Detect Environment
Detect Environment
Detect User Changes
Detect User Changes
Detect Users Needs
Detect Users Needs
Changes
Changes
Proposal for
Proposal for
Proposal stage
Proposal stage
Adaptation
Adaptation
Decision stage
Decision stage
Select Adaptation
Select Adaptation
Execution stage
Execution stage
Execute Adaptation
Execute Adaptation
23
STATE OF ART

• Adaptation process

Propose feasible adaptations given the current
situation and state of interaction.
24
STATE OF ART

• Adaptation process

Select the best adaptations among the proposed
adaptations.
25
STATE OF ART

• Adaptation process

Execute the selected adaptations.
26
STATE OF ART
The process requires reasoning about which
adaptation to fire, choose the best adaptations,
....

• Adaptation process

27
STATE OF ART

• Software agents in user interfaces
• Interface agents dwell in the user interface to
  improve users 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.
28
STATE OF ART

• Software agents in user interfaces
• The design of multi-agent systems require new
  methodological approches
• Extensions of Object Oriented / Knowledge
  Engineering methods and techniques
• Tropos
• Gaia
• AUML
• OASIS
• Prometheus
• Desire
• MAS-CommonKADS
• INGENIAS
• ...

• We used Prometheus because
• It supports the whole software life cycle.
• Widely used.
• It provides a visual design tool.
• Code generation for JACK and JADE.

29
CONTENTS

• Introduction
• State of Art in Adaptive User Interfaces Design
• AB-UIDE A Method for Adaptive UIs Design
• A Study Case ATM UI
• Requirements Analysis stage
• Analysis stage
• Design stage
• Implementation stage
• A MAS Architecture for UI Adaptation
• Final Remarks

30
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.

31
AB-UIDE A Method for Adaptative UIs Design

• AB-UIDE stages

32
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).

33
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

34
AB-UIDE A Method for Adaptative UIs Design

• Requirements analysis stage
• Use case model

35
AB-UIDE A Method for Adaptative UIs Design

• Requirements analysis stage
• Use case model
• Use case sequence diagram

36
AB-UIDE A Method for Adaptative UIs Design

• Requirements analysis stage
• Static context of use model
• User
• Platform
• Environment

37
AB-UIDE A Method for Adaptative UIs Design

• Analysis stage
• Domain model
• Roles model
• Usability trade-off

38
AB-UIDE A Method for Adaptative UIs Design

• Analysis stage
• Domain model

39
AB-UIDE A Method for Adaptative UIs Design

• Analysis stage
• Roles model

40
AB-UIDE A Method for Adaptative UIs Design

• Analysis stage
• Usability trade-off

PDA
BANK ATM
41
AB-UIDE A Method for Adaptative UIs Design

• Design stage
• Adaptivity rules
• Task model
• Interaction objects specification
• Abstract User Interface (AUI)
• Concrete User Interface (CUI)

42
AB-UIDE A Method for Adaptative UIs Design
Transitions are labelled to specify the dialog.

• Design stage
• Task model

43
AB-UIDE A Method for Adaptative UIs Design

• Design stage
• Task model

Actions and tasks temporal relationships are
described by using LOTOS operators (as defined in
CTT).
44
AB-UIDE A Method for Adaptative UIs Design

• Design stage
• Interaction objects specification

45
AB-UIDE A Method for Adaptative UIs Design
The AIOs are grouped in containers, that help on
deciding a good final layout for the UI elements.

• Design stage
• Abstract User Interface (AUI)

AUI consists of AIOs Inputters, Displayers,
Editors, ActionInvokers and Selectors.
Login
(1,1)
Pin
FreeContainer Login
(1,1)
Login
Pin
OK
46
AB-UIDE A Method for Adaptative UIs Design

• Design stage
• Concrete User Interface (CUI)

FreeContainer Login
Login
Window Login
box Login
textComponent NameloginLabel isEditablefalse d
efaultContentLogin
textComponent NameLogin isEditabletrue default
Content
textComponent NamepinLabel isEditablefalse def
aultContentPin
textComponent NamePin isEditabletrue defaultCo
ntent
Events represent the behaviour of the system.
button NameOK
Event Name event010 devicemouse eventType
OnClick
postcondition Namepostcondition004 expression
Customer.checkLogin()
47
AB-UIDE A Method for Adaptative UIs Design

• Design stage
• Conectors model
• Automatically generated

48
AB-UIDE A Method for Adaptative UIs Design
Sensors model the information captured from the
context of use.

• Design stage
• Adaptivity Rules

49
AB-UIDE A Method for Adaptative UIs Design
Context events are produced by one or several
sensors. They trigger adaptivity rules.

• Design stage
• Adaptivity Rules

50
AB-UIDE A Method for Adaptative UIs Design

• Design stage
• Adaptivity Rules

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.
51
AB-UIDE A Method for Adaptative UIs Design

• Design stage
• Adaptivity Rules

SENSOR
CONTEXT EVENT
52
AB-UIDE A Method for Adaptative UIs Design

• Implementation stage
• User interface specification
• User Interface eXtensible 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

53
CONTENTS

• Introduction
• State of Art in Adaptive User Interfaces Design
• AB-UIDE A Method for Adaptive UIs Design
• A MAS Architecture for UI Adaptation
• Initiative stage
• Proposal stage
• Decision stage
• Execution stage
• Implementing the MAS architecture
• Final Remarks

54
A MAS ARCHITECTURE FOR UI ADAPTATION
Platform
Environment
Current UI
Multi-Agent System
User
Task
Adapted UI
55
A MAS ARCHITECTURE FOR UI ADAPTATION

• Multi-agent system goals

56
A MAS ARCHITECTURE FOR UI ADAPTATION

• Multi-agent system overview

57
A MAS ARCHITECTURE FOR UI ADAPTATION

• Multi-agent system overview

58
A MAS ARCHITECTURE FOR UI ADAPTATION

• Multi-agent system overview

The MAS uses all the knowledge about the UI
collected at design time.
AgentAdaptationProcess proposes the plausible
adaptations, selects the best ones and executes
them.
59
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 users current goal
• What is the task the user is carrying out at a
  moment?
• Recurrent task sequences
• Heuristics based on the interaction data collected

60
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.
• 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.

Adaptivity rules
61
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

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 to migrate from one context to
  another.

Users mental effort required to resume the task
that was carrying out before adaptation took
place.
63
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.

Amount of information the user needs to
understand to perform the tasks using the adapted
user interface.
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.

65
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.
66
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.
67
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(RS) quantifies the compatibility between the
hypothesis (the adaptation selection) and the
contents of the adaptation (the adaptation
itself).
P(S) represents the a priori probability that R
is selected to be applied.
P(SR) represents the probability that when R is
applicable, R is choosed.
P(R) represents the probability of R.
68
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 doesnt 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

69
A MAS ARCHITECTURE FOR UI ADAPTATION
Translate the UI graph representation into usiXML
syntax.

• Execution stage

Translate the XML specification into a graph
representation.
Apply the graph grammar transformations on the UI
graph representation.
Render the usiXML specification for the target
platform.
70
CONTENTS

• 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
• Conclusions
• Contributions
• Future work

71
FINAL REMARKS

• Conclusions Outcomes
• An adaptive UI design method (AB-UIDE)
• Adaptive user interfaces execution

72
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

73
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.

74
FINAL REMARKS

• Acknowledgements
• This work has been supported by
• The spanish grants
• CYCIT TIN2004-08000-C03-01 project
• JCCM PBC-03-003 project
• European networks
• SIMILAR Network of Excellence
• Seven month stay at BCHI (Belgian laboratory of
  Computer Human Interaction).

75
FINAL REMARKS

• Contributions
• Topics
• Adaptive user interfaces development related
  papers
• Multi-agent systems related papers
• Study cases related papers

76
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  9th IFIP Working Conference on Engineering
  for Human-Computer Interaction jointly with 11th
  Int. Workshop on Design, Specification, and
  Verification of Interactive Systems
  EHCI-DSVIS2004 (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. 5th
  International Conference on Enterprise
  Information Systems, ICEIS 2003. Proccedings of
  5th International Conference on Enterprise
  Information Systems, ICEIS 2003, vol. 3, pp.
  97-103. 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.

77
FINAL REMARKS

• Contributions
• Adaptive user interfaces development related
  papers (ii)
• Limbourg, Q., Vanderdonckt, J., Michotte, B.,
  Bouillon, L., López-Jaquero, V., UsiXML a
  Language Supporting Multi-Path Development of
  User Interfaces, Proc. of  9th IFIP Working
  Conference on Engineering for Human-Computer
  Interaction jointly with 11th Int. Workshop on
  Design, Specification, and Verification of
  Interactive Systems EHCI-DSVIS2004 (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 IdealXML. 12th International
  Workshop on Design, Specification and
  Verification of Interactive Systems
  (DSV-IS2005), 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).

78
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. 4th 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. ISSN0302-9743. 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.

79
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 E-learning / 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. ISBN0-7695-1013-2.
  Madison, USA, August 6-8, 2001.

80
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.

81
Adaptive User Interfaces Based on Models and
Software Agents
QUESTIONS ANSWERS

• 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_at_info-ab.uclm.es

Thanks for your attention