2005 | OriginalPaper | Buchkapitel
Complex Knowledge in the Environmental Domain: Building Intelligent Architectures for Water Management
verfasst von : Dino Borri, Domenico Camarda, Laura Grassini
Erschienen in: Innovations in Applied Artificial Intelligence
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The upcoming argumentative approach to environmental planning is increasingly spreading out, challenging the traditional strong and absolute rationality of planning. Aiming at structuring the complex issues of the environmental domain, rather than simplify problems, several agents need to interact, locate and share behaviours and knowledge, meanwhile learning from each others’ attitudes and knowledge patterns. In this context, cybernetic rationality is being increasingly re-considered as a quite strong theoretical limitation to environmental planning, a background being founded on merely linear paths of elements and states which is hard to be removed. This rationality is indeed able to cope with deterministic processes, but unable to face the probabilistic and chaotic environmental phenomena, so making it extremely hard to point out elements, to schedule times, to respect consistencies. Given this starting conceptual condition, this paper discusses some theoretical and experimental issues for the development of cognitive architectures of intelligent agent communities in water resources management. This is done through the recognition of the common good nature of water resources, which in turn affects the features of social and individual cognitions involved, as well as the decisions processes. Throughout the paper, a special attention is paid to dilemmas of cognitive change and knowledge-in-actions development in multi-agent participatory environments, through references to both cognitive and organizational analysis.