Cognitive Systems Integrated Project Abstract
Area / Call: FP6-2002-IST-2 / IST-2002-
Proposal Number: 004250

'CoSy': Cognitive Systems for Cognitive Assistants

Coordinator: Henrik I. Christensen,
Centre for Autonomous Systems
Kungl Tekniska Högskolan (KTH), Sweden
Partners: Jeremy Wyatt & Aaron Sloman
School of Computer Science, University of Birmingham - UK
Hans Uszkoreit & Geert-Jan Kruijff
Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI) - DE
Ales Leonardis
Faculty of Computer & Information Science
University of Ljubljana, Slovenia, SI
Bernhard Nebel & Wolfram Burgard
Alfred Ludvig University of Freiburg - DE
J. Kevin O'Regan
Laboratory of Experimental Psychology CNRS,
University of Paris V - FR
Bernt Schiele
Dept of Computer Science, TU Darmstadt, DE
An additional partner with expertise in psychology will be recruited later.

Cognitive Systems for Cognitive Assistants

This document is a summary of a proposal produced in October 2003, inspired by the visionary FP6 objective
"To construct physically instantiated ... systems that can perceive, understand ... and interact with their environment, and evolve in order to achieve human-like performance in activities requiring context-(situation and task) specific knowledge"
We assume that this is far beyond the current state of the art and will remain so for many years. However we have devised a set of intermediate targets based on that vision. Achieving these targets will provide a launch pad for further work towards the long term vision. In particular we aim to advance the science of cognitive systems through a multi-disciplinary investigation of requirements, design options and trade-offs for human-like, autonomous, integrated, physical (e.g. robot) systems, including requirements for architectures, for forms of representation, for perceptual mechanisms, for learning, planning, reasoning, motivation, action, and communication. The results of the investigation will provide the basis for a succession of increasingly ambitious working robot systems to test and demonstrate the ideas. Devising demanding but achievable test scenarios, including scenarios in which a machine not only performs some task but shows that it understands what it has done, and why, is one of the challenges to be addressed in the project. Preliminary scenarios have been proposed. Further scenarios, designs and implementations will be developed on the basis of (a) their potential contribution to the long term vision, (b) their achievability and (c) the possibility of practical applications. Tools will be developed to support this exploration. The work will use an `open' framework facilitating collaboration with a variety of international projects with related objectives.

The problem

Despite impressive progress in many specific sub-topics in AI and Cognitive Science, work on building integrated cognitive systems moves slowly. Most systems able to perform complex tasks that humans and other animals can perform easily, for instance robot manipulators, or intelligent advisers, have to be very carefully crafted, normally their field of expertise is very narrow, and they are hard to extend. Whatever intelligence they have could be described as `insect-like', with very little flexibility or self-understanding. Part of the reason for this is that over the last few decades research has become highly fragmented: with many individuals and research teams focusing their efforts on narrowly defined problems, for instance in vision, or learning, or language processing, or problem solving, or mobile robotics.
We propose to try to overcome these limitations by using ideas from several relevant disciplines to investigate an ambitious vision of a highly competent robot, combining many different capabilities in a coherent manner, for instance a non-trivial subset of the capabilities of a typical human child a few years old. This work will pursue two main types of objectives concerned with theory and implementation, and related subsidiary objectives.

Theory objectives

We aim to produce a body of theory, at different levels of abstraction, regarding requirements, architectures, forms of representation, kinds of ontologies, types of reasoning, kinds of knowledge, and varieties of mechanisms relevant to embodied, integrated, multi-functional intelligent systems. The results should be useful both for enhancing scientific understanding of naturally occurring intelligent systems (e.g. humans) and for the design of artificial intelligent systems.
We expect such a theory to be built around the core idea of a self-modifying architecture combining many capabilities which develop over time, which are deployed concurrently and which interact with one another asynchronously. The theory would cover both analysis of requirements for such an architecture and also design options with their trade-offs. Sub-theories would be concerned with different sorts of components of the architecture and the forms of representation and varieties of knowledge that they can use. Theory construction will build on empirical results in related disciplines (e.g. psychology and linguistics) and achievements of computer science, software engineering and AI (including robotics).
Since different sorts of designs are possible the theory will include an analysis of architectural options and trade-offs as well as design-options and trade-offs concerning components.

Implementation objectives

We expect to produce well-documented implementations of a succession of increasingly sophisticated working systems demonstrating applications of parts of the theory, e.g. in a robot capable of performing a diverse collection of tasks in a variety of challenging scenarios, including various combinations of visual and other forms of perception, learning, reasoning, communication and goal formation. Initially two main kinds of robot will be investigated both of which will learn from and interact with human teachers. One of them, the Explorer, will be concerned with finding its way around a complex building, showing others where to go and answering questions about routes and locations. The other robot, the PlayMate, will be concerned with manipulation of structured objects on a table top. These two require somewhat different physical, perceptual, reasoning, planning and learning capabilities, though both can be combined with natural language capabilities and some social competence. A parallel strand of investigation (the Philosopher scenario) will investigate common requirements for self-understanding, for reasoning, for motivation, and for reflection on what is perceived and learnt.
A common problem in all these tasks is deciding where to draw the nature/nurture boundary, between what is designed in initially and what arises through learning and development. Alternative options will be explored. Another common feature is the requirement to integrate different forms of representation, needed for different sub-capabilities. Another is the requirement for the robot to have multiple ontologies which are used as appropriate for different activities. We shall avoid dogmatism on all these issues, exploring various alternatives and analysing trade-offs.

Subsidiary activities

The project will also produce a succession of workshops and summer schools, publications, and an `open' web site containing code, development tools, theoretical papers, various kinds of re-usable libraries, demonstration packages, etc, including contributions from external collaborators, academic and industrial. We expect to have to share development of tools with other projects.
For more information see the Cosy Web site: http://

File translated from TEX by TTH, version 3.49.
On 6 Apr 2004, 12:51.
With slight post-editing by A.S.