If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Bredeweg, Bert (University of Amsterdam) | Liem, Jochem (University of Amsterdam) | Beek, Wouter (University of Amsterdam) | Linnebank, Floris (University of Amsterdam) | Gracia, Jorge (Universidad Politécnica de Madrid) | Lozano, Esther (Universidad Politécnica de Madrid) | Wißner, Michael (University of Augsburg) | Bühling, René (University of Augsburg) | Salles, Paulo (University of Brasília) | Noble, Richard (University of Hull) | Zitek, Andreas (University of Natural Resources and Applied Life Sciences) | Borisova, Petya (Institute of Biodiversity and Ecosystem Research) | Mioduser, David (Tel Aviv University)
Articulating thought in computer-based media is a powerful means for humans to develop their understanding of phenomena. We have created DynaLearn, an Intelligent Learning Environment that allows learners to acquire conceptual knowledge by constructing and simulating qualitative models of how systems behave. DynaLearn uses diagrammatic representations for learners to express their ideas. This article presents an overview of the DynaLearn system.
Bredeweg, Bert, Struss, Peter
Bredeweg, Bert, Forbus, Kenneth D.
We argue that qualitative modeling provides a valuable way for students to learn. Two modelbuilding environments, VMODEL and HOMER/- VISIGARP, are presented that support learners by constructing conceptual models of systems and their behavior using qualitative formalisms. Both environments use diagrammatic representations to facilitate knowledge articulation. Preliminary evaluations in educational settings provide support for the hypothesis that qualitative modeling tools can be valuable aids for learning.
Salles, Paulo, Bredeweg, Bert
Traditional approaches to ecological modeling, based on mathematical equations, are hampered by the qualitative nature of ecological knowledge. In this article, we demonstrate that qualitative reasoning provides alternative and productive ways for ecologists to develop, organize, and implement models. We present a qualitative theory of population dynamics and use this theory to capture and simulate commonsense theories about population and community ecology. Advantages of this approach include the possibility of deriving relevant conclusions about ecological systems without numeric data; a compositional approach that enables the reusability of models representing partial behavior; the use of a rich vocabulary describing objects, situations, relations, and mechanisms of change; and the capability to provide causal interpretations of system behavior.