K2LAB - Knowledge Engineering and Communication
This document is a preliminary version and does not contain the
full or final text. Mon Oct 10 11:40:26 MET 1994
calle@dsv.su.se
Scope
The overall objective for the laboratory is to tune the design and use
of computer-based systems to the human user's cognitive capabilities
and to let models and theories of human cognitive processes inspire
design principles for computer-based systems.
Cognitive capabilities include our conception of the world, how we
acquire and apply knowledge and skills (learning, memory and problem
solving) and how we communicate and act in interplay with our
environment.
The goal is to develop formal models for representation, problem
solving, adaptation (learning) and communication which can serve as
the basis for realization of computerized support systems within
application areas like decision making, design, validation, monitoring
and diagnosis, communication (electronic mail and tele- and video
conferences), education (both at universities, schools and
training-services) and the dissemination of current and rapidly
changing information (legislation, environmental, medical and
technical expertise).
We need to combine techniques from areas like programming methodology
(PM), artificial intelligence (AI), human-machine interaction (HCI),
computer supported cooperative work (CSCW) and natural language
processing technology (NLP). The research methodology should include
task analysis and user oriented design, formal modelling and algorithm
design, exploratory implementations and analytic and empirical
validation.
Table of Contents
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This area is concerned with research topics related to the whole
development cycle of knowledge-based systems systems, in particular
with the question of how to support the activities of eliciting and
representing knowledge in such systems. The approach is to develop
reusable problem-solving methods and domain models (reusable knowledge
modelling components) for industrially important knowledge-based
systems applications. These includes technical diagnose,
configuration, prediction planning and design support. The major goal
within the field is to create a level of abstraction where automated
problemsolving can be understood, and thus controlled, by domain
experts and users, allowing them to take active part in the
development process.
The main question with which this area is concerned is how to create
adaptive systems by integration of learning algorithms as
components. This involves technical work on representation, reasoning
and learning algorithms as well a studies of the cognitive relevance
of the proposed solutions and the application of solutions in
realistic applications.
Of secondary importance is the use of learning algorithms as an aid
for knowledge acquisition, inducing elements of a theory from observed
cases. The research focusses on symbolic machine learning
techniques. The emphasis is on the revision of theories in Horn clause
logic by combination of techniques from the specialized areas of
Inductive Logic Programming and Explanation-based learning. Another
important topic is conceptual clustering applied in real-time
scenarios. To a smaller extent nonsymbolic approaches have been used
(genetic algorithms).
An important methododological foundation is the application of formal
logic for representation as well as problem solving and logic
programming (LP) as a basis for computation. Within this general
scheme there is a spectrum of approaches from Horn clause logic, via
extensions of logic programming to standard FOL and to non-standard
logics.
The main research question is to extend knowledge-based methods to
deal with large amounts of real-world information. Rather than
modelling information statically as a consistent set of atomic
relational positive facts, the store of knowledge or information is
supposed to be distributed over a network of nodes in less than
perfect communication with each other. At each node, the store
of information can be fluctuating in time, incomplete or inconsistent
and the individual pieces of information can be logically complex,
negative or indefinite.
The proposed methods are techniques from mathematical logic, the
theory of logic programming and the study of formal representation of
non-monotonic reasoning. To model interaction between nodes, axiomatic
modal logic as well as temporal logic can be applied. To represent the
state at each node a particular approach to non-monotonic reasoning
based on a a prolog-type language with both classical negation and
negation as failure is used (Busch, Boman).
This research concerns the area of mechanizing decision analysis. The
work includes both mathematical models, psychological studies and
models, the design of computer support systems and practical
applications. One approach is the model for decision analysis
proposed by Malmnäs. A particular system based upon this model
includes well-founded routines that enable the decision maker to work
with a vague and numerically imprecise basis for decision and, despite
this, reach a conclusive result. Particular problems to be
investigated in this context are to develop:
- suitable algorithms for evaluating decision problems,
- methodologies and algorithms for taking account of different
kinds of probability and utility distributions according to a set of
criteria,
- the interpretation of evaluation of fixed alternatives over vague
domains, and
- methodologies and algorithms for generating optimal alternatives
out of an unspecified set of alternatives.
It is also important to study to what extent an automated system would
be able to model different behavior in decision situations (Malmnäs,
Ekenberg, Montgomery).
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The areas of computer-mediated communication (CMC) and computer
supported cooperative work (CSCW) are closely related and share the
objective to develop computer-based aids for cooperation and
communication in groups of individuals. The term CMC is mainly used
for applications where the participants do not need to be connected
all at the same time, while CSCW also includes same-time
applications.
Among applications should be mentioned electronic mail, computer
conferencing and bulletin board systems, computer support for
particular cooperative processes like idea collection, text editing,
voting and question answering. Typical research issues for these kinds
of systems are: to develop good interfaces, studies of effects on
people and organizations, software support systems, hypermedia
databases, distributed protocols, economical and market issues and
standardization processes.
Mikael Kindborg, Robert Ramberg, (Klas Karlgren) and Carl Gustaf Jansson.
Klas Karlgren, Ann Lantz, Fredrik Kilander, Carl Gustaf Jansson (and Jacob Palme).
The focus of research lies in marrying user-centered design methods and
user-controlled interface designs, with the advanced communication
strategies from intelligent interfaces. This is achieved by focussing on
the development of adaptive interfaces. The same emphasis is put on finding
mechanisms (models and algorithms) for user and context adaptation as well
as methods for requirement engineering in this area. Mechanisms of
particular interest are user modelling techniques, planning and plan
inference algorithms.
Magnus Boman, Douglas Busch (and Love Ekenberg).
Peter Idestam-Almquist, Henrik Boström, Carl Gustaf Jansson, and Lars Asker.
Love Ekenberg, Mats Danielsson (and Magnus Boman).
Jacob Palme, Torgny Tholérus and Tarja Lintunen.
Anita Kollerbaur, Carl Gustaf Jansson and Douglas Busch.
Research management
Carl Gustaf Jansson, acting professor, PhD,
(coordinator), artificial intelligence, knowledge representation,
machine learning, intelligent interfaces and computer supported
education.
Jacob Palme, associate professor, Techn. Lic.
computer supported cooperative work and computer mediated
communication.
Senior researchers, lecturers and postdocs
Lars Asker, lecturer, PhD., artificial intelligence,
machine learning, speedup-learning.
Henrik Boström, lecturer, PhD., artificial
intelligence, machine learning, logic programming, inductive logic
programming.
Magnus Boman, lecturer, PhD., knowledge
representation, modelling of autonomous deductive systems,
multi-agent architectures and decision analysis.
Douglas Busch, associate professor, PhD., knowledge
representation in logic, multi-agent architectures and logic
programming.
Love Ekenberg, lecturer, PhD., decision modelling,
reasoning under uncertainty.
Peter Idestam Almquist, PhD., artificial
intelligence, machine learning, logic programming, inductive logic
programming.
Fredrik Kilander, PhD., artificial intelligence,
machine learning.
Harald Kjellin, PhD., knowledge-based systems,
knowledge representation and knowledge acquisition.
Anita Kollerbaur, senior lecturer, Fil. Lic.,
human-computer-interaction and computer-based education.
Graduate students with graduate positions/research engineers
Bassam Michel El Khouri, Fil. lic., artificial
intelligence, machine learning and statistics, reasoning under
uncertainty.
Peter Holm, Fil. lic., knowledge-based systems,
cognitive science, social and organizational aspects of
computerization.
Klas Karlgren BA., human-computer-interaction,
cognitive psychology.
Hercules Dalianis, Techn. lic., natural language
processing, text generation.
Ann Lantz, Fil. Lic., human-computer-interaction,
cognitive psychology.
Robert Ramberg, Fil. Lic.,
human-computer-interaction, learning, cognitive psychology.
Mats Danielsson, MSc., decision modelling, reasoning
under uncertainty.
Tarja Lintunen BA., computer mediated communication.
Åsa Rudström, BA., artificial intelligence,
knowledge representation, machine learning.
Torgny Tholerus, BA., computer mediated communication.
Pierre Wijkman, MSc., artificial intelligence,
machine learning, genetic algorithms.
Associated graduate students
At SICS:
- in natural language processing
-
- Ivan Bretan
- Martin Eineborg
- Mikael Ericsson
- Björn Gambäck
- in knowledge-based systems
-
- Per Lindevall, Fil. Lic.
- Klas Orsvärn
- Fredrik Holmgren
- in human-computer interaction
-
- Annika Waern, Techn. Lic.
- Kristina Höök, Fil. Lic.
- Anna Lena Ereback
- Jussi Karlgren, Fil. Lic.
At the Sweden Mid University: Åke Malmberg.
At Naturens Hus: Mikael Kindborg, Fil. Lic.,
human-machine interaction, multimedia technology.
Associated advisors
Jan Olsson, PhD., SICS.
Per Erik Malmnäs, Doc, Philosophy, Stockholm University.
Ywonne Waern, Prof., TEMA Communication, Linköping University.
The Lab has produced 10 PhDs and 18 Licentiates since 1990, a majority of
the PhDs during 1993-1994.
Algorithms and prototype systems in the area of Machine Learning:
- A set of algorithms for generalization under implication of Horn
Clauses (summer 1993).
- A set of algorithms for addition of non-redundant...
- Objectives
- To give technical contribution to symbolic machine learning techniques.
- Administrative facts
- Funding: NUTEK under the grant XXXXXXX.
Duration: six years 1987-1993.
Staff: Carl Gustaf Jansson, Peter Idestam Almquist, Henrik
Boström, Lars Asker, Fredrik Kilander, Bassam Michel El Khouri, Pierre
Wijkman and Åsa Rudström.
Collaboration: European partners within the COST 13 Acqusition and
Learning program.
- Main Results
- Five PhD theses completed during 1993/94.
An algorithm for generalization of hornclauses under implication
(Summer 1993).
An EBG algorithm that guarantees nonredundancy (Summer 1993).
An enhanced conceptual clustering algorithm that is
robust with respect to concept drift (Autumn 1993).
- Plans
- The project is finished in 1993 but as a side effect another two PhD
theses and one licentiate thesis will be finished in the autumn of 1994
- Objectives
- To give technical contribution to inductive symbolic machine learning
techniques in a logic programming project.
- Administrative facts
- Funding: TFR under the grant XXXXXXX.
Duration: three years 1993-1996.
Staff: Carl Gustaf Jansson, Peter Idestam Almquist.
Collaboration: European partners within the ILP project.
- Main Results
- An enhanced algorithm for generalization under implication.
- Administrative facts
- Funding: NUTEK under the grant XXXXXXX.
Duration: Three years 1993-1996.
Staff: Carl Gustaf Jansson, Lars Asker and Robert Engels.
Collaboration: The Högdalen energy plant, Ångpanneföreningen.
- Main Results
- A prototype system for optimizing a garbage burning energy plant
using two alternative inductive learning algorithms (Summer 1994).
- Administrative facts
- Funding: NUTEK under the grant XXXXXXX.
Duration: Three years 1993-1996.
Staff: Carl Gustaf Jansson, Klas Karlgren, Nils Dahlbäck,
(Catriona MacDermid).
Collaboration: SICS and Ellemtel.
- Main Results
- A help system for a software engineering method and its toolbox
(Summer 1994).
- Administrative facts
- Funding: NUTEK under the grant XXXXXXX.
Duration: One year 1993-1994, possible cont. for 94.
Staff: Carl Gustaf Jansson, Klas Karlgren, Robert Ramberg.
Collaboration: Telia
- Administrative facts
- Funding: NUTEK under the grant XXXXXXX.
Duration: One year 1993-1994.
Staff: Carl Gustaf Jansson, Joanna Dickinsson and Harald Kjellin.
Collaboration: Ångpanneföreningen.
- Main Results
- A prestudy of how a distributed multimedia system can assist in
planning for energy consultants (Summer 1994).
- Plans
- An extension of the project is planned involving a field study.
- Administrative facts
- Funding: graduate position and other faculty funding.
Duration: Three years 1990-1993.
Staff: Magnus Boman and Douglas Busch.
Collaboration: The COMPULOG NETWORK.
- Administrative facts
- Funding: graduate position and other faculty funding.
Duration: Three years 1991-1994.
Staff: Love Ekenberg and Mats Danielsson.
- Main Results
- A PhD thesis in april 1994.
- Administrative facts
- Funding: NUTEK and AMFO under the grant XXXXXXX.
Duration: Three years 1993-1996.
Staff: Jacob Palme, Fredrik Kilander, Ann Lantz,
Daniel Pargman, Carl Gustaf Jansson and Ywonne Waern.
- Administrative facts
- Funding: NUTEK and AMFO under the grant XXXXXXX.
Duration: three years 1993-1996.
Staff: Jacob Palme, Tarja Lintunen.
- Administrative facts
- Funding: NUTEK and AMFO under the grant XXXXXXX.
Duration: One years 1993-1996.
Staff: Jacob Palme, Anita Kollerbaur and Torgny Tholerus.
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