IDSSs should contribute to the enhancement of human performance, but their effectiveness can be guaranteed only in the case of certain decision types. The issues explored in this paper show that they can help to overcome some human limitations, especially in complex data and information processes, in uncertainty management, and in coherent reasoning. Integrating human and machine expertise is clearly beneficial, nevertheless with the aim of building intelligent solutions we should not ignore the role of human factors and the problems (...) deriving from the integration of knowledge of multiple experts. The risk is that the systems will become clumsy and vulnerable to embarrassing failures.The paper explores the opportunities for exploitation of IDSSs to provide intelligent advice, intelligent analysis and intelligent evaluation. Some suggestions for research have been proposed looking at the ideas put forward in a recent research project dealing with the development of a system supporting local government authorities on environmental impact assessment procedure. (shrink)

A process-oriented model of belief is presented which permits the representation of nested propositional attitudes within first-order logic. The model (NIM, for nested intensional model) is axiomatized, sense-based (via intensions), and sanctions inferences involving nested epistemic attitudes, with different agents and different times. Because NIM is grounded upon senses, it provides a framework in which agents may reason about the beliefs of another agent while remaining neutral with respect to the syntactic forms used to express the latter agent's beliefs. Moreover, (...) NIM provides agents with a conceptual map, interrelating the concepts of knowledge, belief, truth, and a number of cognate concepts, such as infers, retracts, and questions. The broad scope of NIM arises in part from the fact that its axioms are represented in a novel extension of first-order logic, -FOL (presented herein). -FOL simultaneously permits the representation of truth ascriptions, implicit self-reference, and arbitrarily embedded sentences within a first-order setting. Through the combined use of principles derived from Frege, Montague, and Kripke, together with context-sensitive semantic conventions, -FOL captures the logic of truth inferences, while avoiding the inconsistencies exhibited by Tarski. Applications of -FOL and NIM to interagent reasoning are described and the soundness and completeness of -FOL are established herein. (shrink)