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Content archived on 2024-06-18

Distributed Cognition Engineering

Objective

"The DICE project aims at the study of cognition in collective, swarm-like systems (swarm cognition), with two main goals: on the one hand, the theoretical understanding of the mechanisms that support cognitive processing and behavioural optimality in collective systems; on the other hand, the definition of an engineering methodology that provides formal methods and tools for the design of cognitive capabilities in large-scale distributed systems (e.g. distributed multi-robot systems). These two objectives are deeply intertwined. The theoretical understanding will support the definition of a suitable engineering methodology for cognitive systems through the identification of the basic mechanisms used in distributed cognitive processing, which must be translated into formal methods and guidelines for engineering artificial systems (e.g. the interactions observed between bees during nest site selection can be distilled into design patterns leading to an optimal decision making process). Similarly, the requirements for a suitable engineering methodology can support the identification of general mechanisms used in cognitive processes (e.g. the need to provide robustness to an engineered system could point to more detailed models of distributed cognitive processing). This challenging endeavour is instantiated in a coherent yet varied research program that starts from the study of multi-agent models of distributed cognitive processing, distills the fundamental mechanisms and proceeds to the definition of an engineering methodology for concrete applications, which will be tested on real-life swarm robotics demonstrators."

Call for proposal

FP7-PEOPLE-2013-CIG
See other projects for this call

Coordinator

CONSIGLIO NAZIONALE DELLE RICERCHE
EU contribution
€ 100 000,00
Address
PIAZZALE ALDO MORO 7
00185 Roma
Italy

See on map

Region
Centro (IT) Lazio Roma
Activity type
Research Organisations
Administrative Contact
Maria Elisa Rosati (Dr.)
Links
Total cost
No data