IJCAI-97 Invited Talks
Index
Let's Plan it Deductively!
Wolfgang Bibel
Creativity and Artificial Intelligence
Margaret A. Boden
Modeling Social Action for AI Agents
Cristiano Castelfranchi
Vehicles Capable of Dynamic Vision
Ernst D. Dickmanns
Remote-Brained Robots
Masayuki Inaba
Generating Multimedia Briefings:
Language Generation in a Coordinated Multimedia Environment to Convey
Information Concisely
Kathleen R. McKeown
Inheritance Comes of Age:
Applying Nonmonotonic Techniques to Problems in Industry
Leora Morgenstern
Machine Learning Techniques to Make Computers Easier to
Use
Hiroshi Motoda
The New Millennium Remote Agent:
To Boldly Go Where No AI System Has Gone Before
Nicola Muscettola, P. Pandurang Nayak, Barney Pell and Brian C. Williams
Reinforcement Learning: Lessons for AI
Richard S. Sutton
Numerica: A Modeling Language for Global Optimization
Pascal Van Hentenryck
The Origins of Syntax in Visually Grounded Robotic Agents
Luc Steels
Wolfgang Bibel
Technical University Darmstadt, Germany
abstract
Logic and its deductive machinery is in high academic regard but is
more or less irrelevant in industry. Even systems supporting an
obviously logical task such as planning rarely resort to logic and
deduction. Neither truly intelligent planning nor artificial
intelligence in general will ever be achieved unless deductive
mechanisms are given a more central role. State, results and issues of
deduction and deductive planning, and why these two areas matter for
AI, are thus the topics of this talk.
Margaret A. Boden
University of Sussex, United Kingdom
abstract
Creativity is a fundamental feature of human intelligence, and a challenge
for AI. AI techniques can be used to create new ideas in three ways: by
producing novel combinations of familiar ideas; by exploring the potential of
conceptual spaces; and by making transformations that enable the generation of
previously impossible ideas.
AI will have less difficulty in modelling the generation of new ideas
than in automating their evaluation.
Cristiano Castelfranchi
National Research Council and University of Siena, Italy
abstract
Agent-Based Computing needs social intelligence. Some basic issues for
understanding and designing social agents will be addressed: the
difference between social and collective, as well as between
interaction and communication; the trade-off between autonomy and
compliance with requests, norms and constraints; the relationships
between deliberate cooperation and emergent intelligence and
functions; and the foundational role of goal-delegation and
goal-adoption for defining different levels of agency and cooperation.
Ernst D. Dickmanns
University of the German Army at Munich, Germany
abstract
A survey will be given on two decades of developments in the field,
encompassing an increase in computing power by four orders of
magnitude. The '4-D approach' integrating expectation-based methods
from systems dynamics and control engineering with methods from AI has
allowed the creation of vehicles with unprecedented capabilities in the
technical realm: autonomous road vehicle guidance in public traffic on
freeways at speeds beyond 130 km/h, on-board-autonomous landing
approaches of aircraft, and landmark navigation for AGV's, for road
vehicles including turn-offs onto cross-roads, and for helicopters in
low-level flight (real-time, hardware-in-the-loop simulations in the
latter case).
Masayuki Inaba
The University of Tokyo, Japan
abstract
AI and Robotics once shared a dream. Technical advances have led to
an age where this dream seems within reach; but it also seems that
recent AI and robotics may fail to inspire the next generation of
researchers. Remote-Brained Robots may provide a way to reinvent and
revitalize the AI dream; this talk introduces the approach.
Kathleen R. McKeown
Columbia University, USA
abstract
Communication can be more effective when several media (such as text,
speech, or graphics) are integrated and coordinated to present
information. This changes the nature of media specific generation
(e.g., language generation) which must take into account the
multimedia context in which it occurs. In this talk, I will present
work on coordinating and integrating speech, text, static and animated
3D graphics, and stored images, as part of several systems we have
developed at Columbia University. A particular focus of our work has
been on the generation of presentations that brief a user on
information of interest.
Leora Morgenstern
IBM T. J. Watson Research Center, USA
abstract
Inheritance has long been considered the stepchild of formal AI:
a quick and convenient but unexciting way to model some of the
more routine patterns of commonsense reasoning. However,
a simple change in the inheritance paradigm - attaching formulas
to the nodes in a network - allows us to use semantic networks
to do general default reasoning. Moreover, we can retain many of
the positive features of inheritance networks to solve difficult
default reasoning problems in a straightforward manner.
This talk presents the new paradigm and describes how it has
been used for real applications in the medical insurance and
life insurance industries.
Hiroshi Motoda
Osaka University, Japan
abstract
Computers are still not easy to use. Difficulties come from their
ignorance about the user. Identifying user-dependent information that
can be automatically collected helps build a part of user model by
which to predict what the user wants to do next and to do relevant
preprocessing. How this is made possible by using machine learning
techniques is the topic of this talk. This is joint work with Kenichi
Yoshida of the Advanced Research Laboratory, Hitachi, Japan.
Nicola Muscettola
Recom Technologies, NASA Ames Research Center, US
P. Pandurang Nayak
Recom Technologies, NASA Ames Research Center, US
Barney Pell
Caelum Research Corporation, NASA Ames Research Center, US
Brian C. Williams
Recom Technologies, NASA Ames Research Center, US
abstract
The New Millennium Remote Agent (NMRA) is an autonomous spacecraft control
system being developed jointly by NASA Ames and JPL. It integrates
constraint-based planning and scheduling, robust multi-threaded execution,
model-based diagnosis and reconfiguration, and real-time monitoring and
control. NMRA will control Deep Space One (DS-1), the first flight of
NASA's New Millennium Program (NMP), which will launch in 1998. As the
first AI system to autonomously control an actual spacecraft, NMRA will
enable the establishment of a "virtual presence" in space through an
armada of intelligent space probes that autonomously explore the nooks and
crannies of the solar system.
Richard S. Sutton
University of Massachusetts at Amherst, USA
abstract
The field of reinforcement learning has recently produced world-class
applications and, as we survey in this talk, scientific insights that
may be relevant to all of AI. In my view, the main things that we
have learned from reinforcement learning are 1) the power of learning
from experience as opposed to labeled training examples, 2) the
central role of modifiable evaluation functions in organizing
sequential behavior, and 3) that learning and planning could be
radically similar.
Pascal Van Hentenryck
Brown University, USA
abstract
Numerica is a modeling language for stating and solving nonlinear
problems over the reals. From a syntactic standpoint, Numerica makes
it possible to state nonlinear problems as in textbooks or scientific
papers. From a semantic standpoint, Numerica is guaranteed to locate
all isolated solutions to nonlinear constraint systems and all global
optima in optimization problems. From an implementation standpoint,
Numerica combines methods from numerical analysis and constraint
satisfaction.
Luc Steels
VUB AI Laboratory, Belgium and Sony Computer Science Laboratory, France
abstract
Experiments are reported in which a group of software and/or
robotic agents are able to develop a shared set of conventions
with the multi-layered structure and complexity of natural
languages. The languages are grounded in the environmental
and bodily experiences as perceived by the agents. It is further
shown how there can be a co-evolution of language and meaning and
hence a progressive build up of cognitive competence.
higuchi@etl.go.jp
Last modified: Tue Jun 10 22:00:16 JST 1997