| An Architecture for More Realistic Conversational Systems | | BIBAK | PDF | 1-8 | |
| James Allen; George Ferguson; Amanda Stent | |||
| In this paper, we describe an architecture for conversational systems that
enables human-like performance along several important dimensions. First,
interpretation is incremental, multi-level, and involves both general and task-
and domain-specific knowledge. Second, generation is also incremental, proceeds
in parallel with interpretation, and accounts for phenomena such as
turn-taking, grounding and interruptions. Finally, the overall behavior of the
system in the task at hand is determined by the (incremental) results of
interpretation, the persistent goals and obligations of the system, and
exogenous events of which it becomes aware. As a practical matter, the
architecture supports a separation of responsibilities that enhances
portability to new tasks and domains. Keywords: Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2): Natural language; Computing Methodologies -Artificial
Intelligence - Applications and Expert Systems (I.2.1): Natural language
interfaces; Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2): Voice I/O; Computing Methodologies -Artificial Intelligence
- Natural Language Processing (I.2.7): Discourse; Design, Human Factors,
Languages, Management, Performance, Theory; architectures for intelligent,
conversational systems, cooperative, distributed, multimodal interfaces | |||
| Generating Virtual Camera Compositions | | BIBAK | PDF | 9-12 | |
| William Bares; Byungwoo Kim | |||
| This paper describes work in progress to automatically generate camera shots
featuring the composition techniques of expert photographers. This effort
builds upon an automated camera planner that computes a shot satisfying a given
set of constraints. In this prior work, users manually specify the set of
constraints and the numeric parameters for each. A typical two subject shot can
be described by eleven constraints involving sixty numeric parameters. This
work aims to develop a high-level interface to automatically generate such
constraint sets. Photographic composition techniques such as composition in
depth can be realized by automatically constructing appropriate sets of camera
constraints then submitting them to a constraint solver. Keywords: Computing Methodologies -Computer Graphics - Methodology and Techniques
(I.3.6): Interaction techniques; Information Systems -Information Interfaces
and Presentation - User Interfaces (H.5.2): Interaction styles; Design, Human
Factors, Management, Performance, Theory; generation of constraints,
photographic composition, visualization interfaces | |||
| An Integrated Environment for Knowledge Acquisition | | BIBAK | PDF | 13-20 | |
| Jim Blythe; Jihie Kim; Surya Ramachandran; Yolanda Gil | |||
| This paper describes an integrated acquisition interface that includes
several techniques previously developed to support users in various ways as
they add new knowledge to an intelligent system. As a result of this
integration, the individual techniques can take better advantage of the context
in which they are invoked and provide stronger guidance to users. We describe
the current implementation using examples from a travel planning domain, and
demonstrate how users can add complex knowledge to the system. Keywords: Computing Methodologies -Artificial Intelligence - Learning (I.2.6):
Knowledge acquisition; Information Systems -Information Interfaces and
Presentation - User Interfaces (H.5.2); Design, Human Factors, Management,
Performance, Theory | |||
| When Policies are Better than Plans: Decision-Theoretic Planning of Recommendation Sequences | | BIBAK | PDF | 21-24 | |
| Thorsten Bohnenberger; Anthony Jameson | |||
| An intelligent user interface sometimes needs to present a sequence of
related recommendations to a user, in spite of being uncertain in advance as to
whether (and with what success) the user will follow each recommendation. There
are potential advantages to the use of decision-theoretic planning methods
which yield an optimal policy for the situation-dependent presentation of
recommendations. This approach is discussed with reference to an example
involving route instructions given by an airport assistance system. Keywords: Information Systems -Information Systems Applications - Types of Systems
(H.4.2): Decision support; Information Systems -Information Interfaces and
Presentation - User Interfaces (H.5.2); Computing Methodologies -Artificial
Intelligence - Problem Solving, Control Methods, and Search (I.2.8): Plan
execution, formation, and generation; Computing Methodologies -Artificial
Intelligence - Applications and Expert Systems (I.2.1); Design, Human Factors,
Management, Performance, Theory; decision-theoretic planning, intelligent user
interfaces, recommendations, route planning | |||
| A Hybrid Indoor Navigation System | | BIBAK | PDF | 25-32 | |
| Andreas Butz; Jorg Baus; Antonio Kruger; Marco Lohse | |||
| We describe a hybrid building navigation system consisting of stationary
information booths and a mobile communication infrastructure feeding small
portable devices. The graphical presentations for both the booths and the
mobile devices are generated from a common source and for the common task of
way finding, but they use different techniques to convey possibly different
subsets of the relevant information. The form of the presentations is depending
on technical limitations of the output media, accuracy of location information,
and cognitive restrictions of the user. We analyze what information needs to be
conveyed, how limited resources influence the presentation of this information,
and argue, that by generating all different presentations in a common
framework, a consistent appearance across devices can be achieved and that the
different device classes can complement each other in facilitating the
navigation task. Keywords: Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2); Information Systems -Information Interfaces and
Presentation - Hypertext/Hypermedia (H.5.4): Navigation; Design, Human Factors,
Measurement, Management, Performance, Theory; hybrid user interfaces,
navigation, resource adaptivity, user adaptivity | |||
| Implicit Interest Indicators | | BIBAK | PDF | 33-40 | |
| Mark Claypool; Phong Le; Makoto Wased; David Brown | |||
| Recommender systems provide personalized suggestions about items that users
will find interesting. Typically, recommender systems require a user interface
that can "intelligently" determine the interest of a user and use this
information to make suggestions. The common solution, "explicit ratings", where
users tell the system what they think about a piece of information, is
well-understood and fairly precise. However, having to stop to enter explicit
ratings can alter normal patterns of browsing and reading. A more "intelligent"
method is to use implicit ratings, where a rating is obtained by a method other
than obtaining it directly from the user. These implicit interest indicators
have obvious advantages, including removing the cost of the user rating, and
that every user interaction with the system can contribute to an implicit
rating.
Current recommender systems mostly do not use implicit ratings, nor is the ability of implicit ratings to predict actual user interest well-understood. This research studies the correlation between various implicit ratings and the explicit rating for a single Web page. A Web browser was developed to record the user's actions (implicit ratings) and the explicit rating of a page. Actions included mouse clicks, mouse movement, scrolling and elapsed time. This browser was used by over 80 people that browsed more than 2500 Web pages. Using the data collected by the browser, the individual implicit ratings and some combinations of implicit ratings were analyzed and compared with the explicit rating. We found that the time spent on a page, the amount of scrolling on a page and the combination of time and scrolling had a strong correlation with explicit interest, while individual scrolling methods and mouse-clicks were ineffective in predicting explicit interest. Keywords: Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2); Computing Methodologies -Artificial Intelligence -
Applications and Expert Systems (I.2.1); Computing Methodologies -Artificial
Intelligence - Distributed Artificial Intelligence (I.2.11); Design,
Experimentation, Human Factors, Measurement, Management, Performance, Theory | |||
| Providing Adaptive Support to the Understanding of Instructional Material | | BIBAK | PDF | 41-47 | |
| Cristina Conati; Kurt VanLehn | |||
| We present an adaptive interface designed to provide tailored support for
the understanding of written instructional material. The interface relies on a
user model based on a Bayesian network, that assesses users' understanding as
users read the instructional material and try to understand it by generating
explanations to themselves. The user model's assessment is used by the
interface to generate tailored scaffolding of further user's explanations that
can improve the user's comprehension. After illustrating how the Bayesian user
model assesses understanding from the user's explanations and from latency data
on the user's attention, we discuss initial results on the effectiveness of the
interface's adaptive interventions. Keywords: Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2); Information Systems -Models and Principles - User/Machine
Systems (H.1.2); Computing Methodologies -Artificial Intelligence - General
(I.2.0): Cognitive simulation; Design, Human Factors, Measurement, Management,
Performance, Theory; Bayesian networks, adaptive tutoring, modeling attention,
user modeling | |||
| XLibris: An Automated Library Research Assistant | | BIBAK | PDF | 49-52 | |
| Andrew Crossen; Jay Budzik; Mason Warner; Larry Birnbaum; Kristian J. Hammond | |||
| While recent work has focused on providing tools and infrastructure for
users to access electronic information over the Internet, the relationship
between the physical world and information available online has been relatively
unexplored. Information about a user's location, and the objects she interacts
with, can be sufficient to recognize enough of the user's task to drive
retrieval of online information relevant to the task at hand. The XLibris
system automatically retrieves, aggregates, and delivers information about
books to users as they are checked out of the library, using information about
the books themselves and the user's task. XLibris locates books in the Dewey
Decimal subject hierarchy to automatically search for the most relevant
information about the book for the user, tailoring both the sources queried and
the information returned based on the book's position in the hierarchy. Keywords: Information Systems -Information Storage and Retrieval - Library Automation
(H.3.6); Information Systems -Information Storage and Retrieval - Information
Search and Retrieval (H.3.3): Retrieval models; Information Systems
-Information Interfaces and Presentation - User Interfaces (H.5.2); Design,
Documentation, Human Factors, Management, Performance, Theory; automated
retrieval, information aggregation, metasearch, ubiquitous computing | |||
| Incorporating Tutorial Strategies Into an Intelligent Assistant | | BIBAK | PDF | 53-56 | |
| Jim R. Davies; Abigail S. Gertner; Neal Lesh; Charles Rich; Candace L. Sidner; Jeff Rickel | |||
| Computer tutors and intelligent software assistants have traditionally been
thought of as different kinds of systems. However tutors and assistants share
many properties. We have incorporated tutorial strategies into an intelligent
assistant based on the COLLAGEN architecture. We are working on an agent, named
Triton, which teaches and helps users with the graphical user interface of an
air travel planning system. We found that the collaborative model underlying
COLLAGEN is an excellent foundation for both an assistant and a tutor, and that
both modes of interaction can be implemented in the same system with different
parameter settings. Keywords: Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2); Computing Methodologies -Artificial Intelligence -
Applications and Expert Systems (I.2.1); Design, Human Factors, Management,
Performance, Theory; collaboration, discourse, intelligent assistants,
intelligent tutoring systems, software agents | |||
| Example Based Generation of Custom Data Analysis Appliances | | BIBAK | PDF | 57-64 | |
| Mark Derthick; Steven F. Roth | |||
| Custom interfaces, which we call appliances, allow users to efficiently
carry out specialized tasks. Without one, a user is often required to perform
repetitive mechanical steps using general purpose interfaces, which we call
tools. Much research has attempted to enable non-programmers to create
appliances for themselves.
We present a system in which a user can choose an example of the task behavior to be automated from a visualization of his past operations. The example is transformed into a visual language, using two simple rules to generalize from the single example to a class of tasks. The user can then edit this representation directly, or continue to refine the example using selective undo and redo. The visual representation can be transformed into an esthetically pleasing appliance by deleting irrelevant components, and rearranging, resizing, and relabeling other components. Restricting the domain to data analysis tasks enables a well-matched visual query language to be used. Appliance interactions are automatically provided by the underlying interactive visualization system in which the appliance is embedded. An observational study suggests that this system represents a useful point on the ease-of-use vs. expressive power tradeoff appropriate for data analysis, and that the ability to choose and modify examples after the fact is helpful. Keywords: Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2): Graphical user interfaces (GUI); Computing Methodologies
-Computer Graphics - Methodology and Techniques (I.3.6): Languages; Information
Systems -Database Management - Languages (H.2.3): Query languages; Algorithms,
Design, Human Factors, Languages, Management, Performance, Theory; GUI builder,
programming with examples, visual query language | |||
| What do Users Prefer?: A Personalized Intelligent User Interface for Searching Information -- An Empirical Study | | BIBAK | PDF | 65-68 | |
| Dina Goren-Bar; Tsvi Kuflik; Tali Lavie | |||
| Searching the web for information becomes a tedious task. As a result of any
query, the user gets large numbers of responses, most of them irrelevant.
Existing search tools fail to cope with this information overload, mainly due
to lack of personalization. Current developments emphasize better
representation of user interests and dynamic adaptation based on relevance
feedback, but personalization is much more then just that. The present study
examines the impact of search tools adaptation to their users. A significant
preference toward user-oriented search method over the conventional
content-based method was found. The results clearly demonstrate the need for
self-adapting personalized interfaces as mediators between users and
information repositories of all kinds. Keywords: Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2); Computing Methodologies -Artificial Intelligence -
Applications and Expert Systems (I.2.1); Information Systems -Models and
Principles - User/Machine Systems (H.1.2); Information Systems -Information
Storage and Retrieval - Information Search and Retrieval (H.3.3): Information
filtering; Design, Experimentation, Human Factors, Measurement, Management,
Performance, Theory; adaptive user-interface, user modeling | |||
| Applying Model-Based Techniques to the Development of UIs for Mobile Computers | | BIBAK | PDF | 69-76 | |
| Jacob Eisenstein; Jean Vanderdonckt; Angel Puerta | |||
| Mobile computing poses a series of unique challenges for user interface
design and development: user interfaces must now accommodate the capabilities
of various access devices and be suitable for different contexts of use, while
preserving consistency and usability. We propose a set of techniques that will
aid UI designers who are working in the domain of mobile computing. These
techniques will allow designers to build UIs across several platforms, while
respecting the unique constraints posed by each platform. In addition, these
techniques will help designers to recognize and accommodate the unique contexts
in which mobile computing occurs. Central to our approach is the development of
a user-interface model that serves to isolate those features that are common to
the various contexts of use, and to specify how the user-interface should
adjust when the context changes. We claim that without some abstract
description of the UI, it is likely that the design and the development of
user-interfaces for mobile computing will be very time consuming, error-prone
or even doomed to failure. Keywords: Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2); Computer Systems Organization -Computer System
Implementation - Microcomputers (C.5.3): Portable devices (e.g., laptops,
personal digital assistants); Design, Human Factors, Measurement, Management,
Performance, Theory; adaptive user-interface, mobile computing, plastic
user-interface, platform constraints, task model, user-interface modeling | |||
| Towards a Computational Model of Sketching | | BIBAK | PDF | 77-83 | |
| Kenneth D. Forbus; Ronald W. Ferguson; Jeffery M. Usher | |||
| Sketching is a powerful means of interpersonal communication. While many
useful multimodal systems have been created, current systems are far from
achieving human-like participation in sketching. A computational model of
sketching would help characterize these differences and help us better
understand how to overcome them. This paper is a first step towards such a
model. We start with an example of a sketching system (nuSketch COA Creator)
designed to aid military planners, to provide context and a source of examples.
We then describe four dimensions of sketching, visual understanding, conceptual
understanding, language understanding, and drawing,that can be used to
characterize the competence of existing systems and identify open problems. The
issues involved will be illustrated by examples from our experience with
nuSketch. Three research challenges are posed, to serve as milestones towards a
computational model of sketching that can explain and replicate human abilities
in this area. Keywords: Computing Methodologies -Artificial Intelligence - Applications and Expert
Systems (I.2.1); Information Systems -Information Interfaces and Presentation -
User Interfaces (H.5.2); Computing Methodologies -Computer Graphics -
Three-Dimensional Graphics and Realism (I.3.7); Design, Human Factors,
Management, Performance, Theory; intelligent front-ends to knowledge-based
systems, multimodal interfaces, sketching | |||
| An Intelligent User Interface for Mixed-Initiative Multi-Source Travel Planning | | BIBAK | PDF | 85-86 | |
| Martin Frank; Maria Muslea; Jean Oh; Steve Minton; Craig Knoblock | |||
| A mixed-initiative planner in our context is one in which either the human
or the computer can spontaneously provide the content of the same input fields.
A multi-source planner is one that accesses multiple external information
sources in parallel, using separate threads. This type of highly dynamic user
interface is desirable but presents a challenge in "keeping the user in
control" because it can be confusing to understand which fields of the form
currently "belong" to the user, which ones "belong" to the system, how these
two interact, and when and how their ownership changes. Keywords: Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2); Computing Methodologies -Artificial Intelligence -
Applications and Expert Systems (I.2.1); Computing Methodologies -Artificial
Intelligence - Problem Solving, Control Methods, and Search (I.2.8): Plan
execution, formation, and generation; Design, Human Factors, Management,
Performance, Theory | |||
| Modeling User Preferences via Theory Refinement | | BIBAK | PDF | 87-90 | |
| Ben Geisler; Vu Ha; Peter Haddawy | |||
| We present an approach to elicitation of user preference models in which
assumptions can be used to guide but not constrain the elicitation process. We
show how to encode assumptions concerning preferential independence and
monotonicity in a Knowledge-Based Artificial Neural Network. We quantify the
degree to which user preferences violate a set of assumptions. We empirically
compare the KBANN network with an unbiased ANN in terms of learning rate and
accuracy for preferences consistent and inconsistent with the assumptions. We
go on to demonstrate how the technique can be used to learn a fine-grained
preference structure from simple binary classification data. Keywords: Computing Methodologies -Artificial Intelligence - General (I.2.0):
Cognitive simulation; Information Systems -Information Systems Applications -
Types of Systems (H.4.2): Decision support; Information Systems -Information
Interfaces and Presentation - User Interfaces (H.5.2); Computing Methodologies
-Artificial Intelligence - Learning (I.2.6): Connectionism and neural nets;
Design, Human Factors, Measurement, Management, Performance, Theory; decision
theory, neural networks, personalization, user modeling | |||
| Community Search Assistant | | BIBAK | PDF | 91-96 | |
| Natalie S. Glance | |||
| This paper describes a new software agent, the community search assistant,
which recommends related searches to users of search engines. The community
search assistant enables communities of users to search in a collaborative
fashion. All queries submitted by the community are stored in the form of a
graph. Links are made between queries that are found to be related. Users can
peruse the network of related queries in an ordered way: following a path from
a first cousin, to a second cousin to a third cousin, etc. to a set of search
results. The first key idea behind the use of query graphs is that the
determination of relatedness depends on the documents returned by the queries,
not on the actual terms in the queries themselves. The second key idea is that
the construction of the query graph transforms single user usage of information
networks (e.g. search) into collaborative usage: all users can tap into the
knowledge base of queries submitted by others. Keywords: Computing Methodologies -Artificial Intelligence - Distributed Artificial
Intelligence (I.2.11): Intelligent agents; Information Systems -Information
Storage and Retrieval - Information Search and Retrieval (H.3.3): Search
process; Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2); Mathematics of Computing -Discrete Mathematics - General
(G.2.0); Design, Human Factors, Measurement, Management, Performance, Theory;
intelligent agent, recommender system, search | |||
| Adaptively Constructing the Query Interface for Meta-Search Engines | | BIBAK | PDF | 97-100 | |
| Lieming Huang; Thiel Ulrich; Matthias Hemmje; Erich J. Neuhold | |||
| With the exponential growth of information on the Internet, current
information integration systems have become more and more unsuitable for this
"Internet age" due to the great diversity among sources. This paper presents a
constraint-based query user interface model, which can be applied to the
construction of dynamically generated adaptive user interfaces for meta-search
engines. Keywords: Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2); Information Systems -Database Management - Systems (H.2.4):
Query processing; Information Systems -Information Storage and Retrieval -
Information Search and Retrieval (H.3.3): Search process; Design,
Experimentation, Human Factors, Measurement, Management, Performance, Theory | |||
| An Integrated Interface for Proactive, Experience-Based Design Support | | BIBAK | PDF | 101-108 | |
| David B. Leake; Larry Birnbaum; Kristian Hammond; Cameron Marlow; Hao Yang | |||
| Many case-based reasoning systems have been developed to aid designers by
providing them with libraries of prior design experiences. Traditionally, these
systems are implemented as stand-alone "external memories" for the designer to
query manually. This paper presents a contrasting approach that integrates
proactive case retrieval into the designer's normal task processes,
automatically tailoring information selection and presentation emphasis to fit
changing designer needs and attention flow. The paper presents a set of
principles for this integrated intelligent design support and describes their
application in the Stamping Advisor, a system to support design feasibility
analysis for sheet metal automotive parts. The Stamping Advisor interface
proactively provides designers with relevant information to support feasibility
analysis, automatically prepares their information products, and unobtrusively
gathers the information needed to generate new cases to improve the quality of
future support. Keywords: Computing Methodologies -Artificial Intelligence - Applications and Expert
Systems (I.2.1); Information Systems -Information Interfaces and Presentation -
User Interfaces (H.5.2); Information Systems -Information Storage and Retrieval
- Information Search and Retrieval (H.3.3): Retrieval models; Design, Human
Factors, Management, Performance, Theory; case-based reasoning, context,
design, intelligent information systems, just-in-time retrieval, knowledge
management | |||
| Towards Context-Based Search Engine Selection | | BIBAK | PDF | 109-112 | |
| David B. Leake; Ryan Scherle | |||
| A well-known problem for web search is targeting search on information that
satisfies users' information needs. User queries tend to be short, and hence
often ambiguous, which can lead to inappropriate results from general-purpose
search engines. This has led to a number of methods for narrowing queries by
adding information. This paper presents an alternative approach that aims to
improve query results by using knowledge of a user's current activities to
select search engines relevant to their information needs, exploiting the
proliferation of high-quality special-purpose search services. The paper
introduces the PRISM source selection system and describes its approach. It
then describes two initial experiments testing the system's methods. Keywords: Information Systems -Database Management - Systems (H.2.4): Distributed
databases; Information Systems -Information Storage and Retrieval - Online
Information Services (H.3.5): Web-based services; Information Systems
-Information Interfaces and Presentation - Group and Organization Interfaces
(H.5.3): Web-based interaction; Information Systems -Information Storage and
Retrieval - Information Search and Retrieval (H.3.3): Search process;
Information Systems -Information Interfaces and Presentation - User Interfaces
(H.5.2); Design, Experimentation, Human Factors, Measurement, Management,
Performance, Theory; distributed information systems, intelligent web search,
just-in-time information access | |||
| Creating Tangible Interfaces by Augmenting Physical Objects with Multimodal Language | | BIBAK | PDF | 113-119 | |
| David R. McGee; Philip R. Cohen | |||
| Rasa is a tangible augmented reality environment that digitally enhances the
existing paper-based command and control capability in a military command post.
By observing and understanding the users' speech, pen, and touch-based
multimodal language, Rasa computationally augments the physical objects on a
command post map, linking these items to digital representations of the
same-for example, linking a paper map to the world and Post-it notes to
military units. Herein, we give a thorough account of Rasa's underlying
multiagent framework, and its recognition, understanding, and multimodal
integration components. Moreover, we examine five properties of
language-generativity, comprehensibility, compositionality, referentiality,
and, at times, persistence-that render it suitable as an augmentation approach,
contrasting these properties to those of other augmentation methods. It is
these properties of language that allow users of Rasa to augment physical
objects, transforming them into tangible interfaces. Keywords: Information Systems -Information Interfaces and Presentation - Multimedia
Information Systems (H.5.1): Artificial, augmented, and virtual realities;
Computing Methodologies -Computer Graphics - Three-Dimensional Graphics and
Realism (I.3.7): Virtual reality; Information Systems -Models and Principles -
User/Machine Systems (H.1.2); Information Systems -Information Interfaces and
Presentation - User Interfaces (H.5.2); Design, Human Factors, Languages,
Management, Performance, Theory; augmented reality, human factors, invisible
interfaces, mixed reality, multimodal interfaces, tangible interfaces | |||
| Inferring Calendar Event Attendance | | BIBAK | PDF | 121-128 | |
| Elizabeth Mynatt; Joe Tullio | |||
| The digital personal calendar has long been established as an effective tool
for supporting workgroup coordination. For the new class of ubiquitous
computing applications, however, the calendar can also be seen as a sensor,
providing both location and availability information to these applications. In
most cases, however, the calendar represents a sequence of events that people
could (or should) attend, not their actual daily activities. To assist in the
accurate determination of user whereabouts and availability, we present Ambush,
a calendar system extension that uses a Bayesian model to predict the
likelihood of one's attendance at the events listed on his or her schedule. We
also present several techniques for the visual display of these likelihoods in
a manner intended to be quickly interpreted by users examining the calendar. Keywords: Information Systems -Information Systems Applications - Office Automation
(H.4.1): Groupware; Information Systems -Information Interfaces and
Presentation - User Interfaces (H.5.2); Computing Methodologies -Artificial
Intelligence - Problem Solving, Control Methods, and Search (I.2.8):
Scheduling; Computing Methodologies -Artificial Intelligence - Deduction and
Theorem Proving (I.2.3): Uncertainty, "fuzzy," and probabilistic reasoning;
Design, Human Factors, Measurement, Management, Performance, Theory; bayesian
networks, calendars, context-aware, groupware calendar systems, informal
meeting scheduling, visualizing uncertainty | |||
| Heroes, Villains, Magicians, ...: Dramatis Personae in a Virtual Story Creation Environment | | BIBAK | PDF | 129-136 | |
| Ana Paiva; Isabel Machado; Rui Prada | |||
| One difficulty in creating synthetic characters for interactive stories is
that these characters must convey their role in the story in a believable way.
However, the relation between believability, on one side, and the role a
character plays in a drama, on the other, has not yet been fully addressed. In
this paper we will present a view on how to develop believable synthetic
characters whose behaviour is based on a set of predefined functions (Propp's
functions) associated with the role they play in the story. To illustrate the
approach, we will present a collaborative virtual environment, Teatrix,
designed for children to build their own stories-fairy tales. In Teatrix,
virtual actors play roles (such as villain, hero, magician, etc), which are
functional for the development of the story. Such roles have pre-defined goals
and plans, allowing the story to flow and climax situations to arise. Teatrixis
already in use by children ages between 7 and 9, in the context of a
Computer-Integrated Classroom scenario. Keywords: Computing Methodologies -Artificial Intelligence - Distributed Artificial
Intelligence (I.2.11): Intelligent agents; Information Systems -Information
Interfaces and Presentation - User Interfaces (H.5.2); Information Systems
-Information Interfaces and Presentation - Multimedia Information Systems
(H.5.1); Design, Human Factors, Measurement, Management, Performance, Theory;
application-specific intelligent interfaces, intelligent agents and agent-based
interaction | |||
| A Computational Model and Classification Framework for Social Navigation | | BIBAK | PDF | 137-144 | |
| Mark O. Riedl | |||
| Social navigation is the process of making navigational decisions in real or
virtual environments based on social and communicative interaction with others.
A computational model for social navigation is presented as an extension to an
existing framework for general navigation, reducing decision-making to the
minimization of cognitive costs. Consideration for social navigation gives rise
to a classification framework based on the synchronicity, directness, and
social presence during social interaction, each of which has direct effect on
the cognitive costs of navigational tasks. Finally, a new recommender system,
TRAILGUIDE, is presented as a tool that facilitates social navigation by
allowing authors to explicitly publish "trails" within and between World Wide
Web pages. Keywords: Information Systems -Information Interfaces and Presentation - User
Interfaces (H.5.2); Information Systems -Information Interfaces and
Presentation - Hypertext/Hypermedia (H.5.4): Navigation; Information Systems
-Information Storage and Retrieval - Online Information Services (H.3.5):
Web-based services; Information Systems -Information Interfaces and
Presentation - Group and Organization Interfaces (H.5.3): Web-based
interaction; Design, Human Factors, Management, Performance, Theory; World Wide
Web, embodied avatars, recommender systems, social navigation model, social
presence | |||
| Intelligent Profiling by Example | | BIBAK | PDF | 145-151 | |
| Sybil Shearin; Henry Lieberman | |||
| The Apt Decision agent learns user preferences in the domain of rental real
estate by observing the user's critique of apartment features. Users provide a
small number of criteria in the initial interaction, receive a display of
sample apartments, and then react to any feature of any apartment
independently, in any order. Users learn which features are important to them
as they discover the details of specific apartments. The agent uses interactive
learning techniques to build a profile of user preferences, which can then be
saved and used in further retrievals. Because the user's actions in specifying
preferences are also used by the agent to create a profile, the result is an
agent that builds a profile without redundant or unnecessary effort on the
user's part. Keywords: Computing Methodologies -Artificial Intelligence - Distributed Artificial
Intelligence (I.2.11): Intelligent agents; Information Systems -Information
Systems Applications - Types of Systems (H.4.2): Decision support; Computer
Applications - Administrative Data Processing (J.1): Business; Computing
Methodologies -Artificial Intelligence - Learning (I.2.6); Design, Human
Factors, Management, Performance, Theory; electronic profiles, infomediary,
interactive learning, personalization, profiling, real estate, user preferences | |||
| Intelligent Visualization in a Planning Simulation | | BIBAK | ABSTRACT | 153-159 | |
| Robert St. Amant; Christopher G. Healey; Mark Riedl; Sarat Kocherlakota; David A. Pegram; Mika Torhola | |||
| This paper describes a set of visualization techniques for interactive
planning in a physical force simulation called AFS. We have developed a 3D
environment in which textures are overlaid on a simulated landscape to convey
information about environmental properties, agent actions, and possible
strategies. Scenes are presented, via automated camera planning, such that some
simple agent goals can be induced visually with little effort. These two areas
of visualization functionality in AFS exploit properties of human low-level and
intermediate-level vision, respectively. This paper presents AFS, its
visualization environment, and studies we have run to explore the relationship
between AFS visualizations and the high-level planning process. Keywords: Computing Methodologies -Artificial Intelligence - Problem Solving, Control
Methods, and Search (I.2.8): Plan execution, formation, and generation;
Computing Methodologies -Computer Graphics - Applications (I.3.8); Computing
Methodologies -Simulation and Modeling - Applications (I.6.3); Computing
Methodologies -Simulation and Modeling - Model Validation and Analysis (I.6.4);
Information Systems -Information Interfaces and Presentation - User Interfaces
(H.5.2): Graphical user interfaces (GUI); Design, Experimentation, Human
Factors, Management, Performance, Theory | |||
| Interfaces for Understanding Multi-Agent Behavior | | BIBAK | PDF | 161-166 | |
| Pedro Szekely; Craig Milo Rogers; Martin Frank | |||
| Synchronized punch-card displays are an interface technique to visualize
tens of thousands of variables by encoding their values as color chips in a
rectangular array. Our technique ties multiple such displays to a timeline of
events enabling the punch-card displays to show animations of the behavior of
complex systems. Punch-card displays not only make it easy to understand the
high-level behavior of systems, but also enable users to quickly focus on
individual variables and on fine-grained time intervals. This paper describes
synchronized punch-card displays and shows how this technique is extremely
powerful for understanding the behavior of complex multi-agent systems. Keywords: Computing Methodologies -Artificial Intelligence - Distributed Artificial
Intelligence (I.2.11): Multiagent systems; Algorithms, Design, Experimentation,
Human Factors, Management, Performance, Theory; agents, visualization | |||
| Mixed Initiative Interfaces for Learning Tasks: SMARTedit Talks Back | | BIBAK | PDF | 167-174 | |
| Steven A. Wolfman; Tessa Lau; Pedro Domingos; Daniel S. Weld | |||
| Applications of machine learning can be viewed as teacher-student
interactions in which the teacher provides training examples and the student
learns a generalization of the training examples. One such application of great
interest to the IUI community is adaptive user interfaces. In the traditional
learning interface, the scope of teacher-student interactions consists solely
of the teacher/user providing some number of training examples to the
student/learner and testing the learned model on new examples. Active learning
approaches go one step beyond the traditional interaction model and allow the
student to propose new training examples that are then solved by the teacher.
In this paper, we propose that interfaces for machine learning should even more
closely resemble human teacher-student relationships. A teacher's time and
attention are precious resources. An intelligent student must proactively
contribute to the learning process, by reasoning about the quality of its
knowledge, collaborating with the teacher, and suggesting new examples for her
to solve. The paper describes a variety of rich interaction modes that enhance
the learning process and presents a decision-theoretic framework, called
DIAManD, for choosing the best interaction. We apply the framework to the
SMARTedit programming by demonstration system and describe experimental
validation and preliminary user feedback. Keywords: Computing Methodologies -Artificial Intelligence - Learning (I.2.6);
Computing Milieux -Computers and Education - Computer Uses in Education
(K.3.1); Information Systems -Models and Principles - User/Machine Systems
(H.1.2); Information Systems -Information Systems Applications - Types of
Systems (H.4.2): Decision support; Design, Human Factors, Measurement,
Management, Performance, Theory; machine learning applications, mixed
initiative, programming by demonstration | |||