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2005-2006 Work Programme
2.4.8 Cognitive Systems
To develop artificial systems that can interpret data arising from real-world events and processes (mainly in the form of data-streams from sensors of all types and in particular from visual and/or audio sources); acquire situated knowledge of their environment; act, make or suggest decisions and communicate with people on human terms, thereby supporting them in performing complex tasks.
Focus is on research into ways of endowing artificial systems with high-level cognitive capabilities, typically perception, understanding, learning, knowledge representation and deliberation, thus advancing enabling technologies for scene interpretation, natural language understanding, automated reasoning and problem-solving, robotics and automation, that are relevant for dealing with complex real-world systems. It aims at systems that develop their reasoning, planning and communication faculties through grounding in interactive and collaborative environments, which are part of, or connected to the real world.
These systems are expected to exhibit appropriate degrees of autonomy and also to learn through "social" interaction among themselves and/or through human-agent cooperation; in a longer term perspective, research will explore models for cognitive traits such as affect, consciousness or theory of mind.
Research will aim at:
- Developing models and architectures for artificial cognitive systems, emphasising higher-level cognitive functions. It should yield new approaches towards understanding and improving cognitive capabilities in artefacts and explore new methods of integrating these in complete artificial systems.
Instruments: IPs, STREPs, CAs, NoEs
- Viable methods living up to demanding application requirements for autonomous or semi-autonomous systems, preferably in industrial inspection and monitoring, complex systems control, medicine or the life sciences.
Instruments: IPs, STREPs
Work is expected to be highly interdisciplinary, drawing on appropriate fields that contribute to cognitive science and cognitive engineering: artificial intelligence, computer vision and robotics, as well as relevant branches of mathematics (e.g. dynamical systems, information theory), the bio-sciences (e.g. neuroscience) and the humanities (e.g. linguistics, philosophy).
- IPs will be used to research the modelling and architecture of entire cognitive systems. They may also research systems-level integration of methods and tools, as well as the integration of different layers of the cognition process (e.g. combining low- and high-level cognitive functions). STREPs will primarily target specific research issues, cognitive functionalities or components which are best researched within small, flexible groupings. CAs are encouraged to promote collaboration across previously fragmented communities, with a view to forming future joint research networks. Alternatively to a CA, a well-balanced NoE combining a critical mass of interdisciplinary research would be welcome. All actions should promote pertinent aspects of community and skills building, where appropriate, with an outreach to and inclusion of industry and application service provision.
- Indicative budget:
- IPs, NoEs: 65%; STREPs, CAs: 35%
- Call information:
- IST Call 4