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) …
"In this article we take a step towards providing an analysis of the Soar architecture as a basis for general intelligence. Included are discussions of the basic assumptions underlying the development of Soar, a description of Soar cast in terms of the theoretical idea of multiple levels of description, an example of Soar performing multi-column subtraction, and three analyses of Soar: its natural tasks, the sources of its power, and its scope and limits"Artificial Intelligence, 47, 289-325.
ABSTRACT Classifier systems are massively parallel, message-passing, rule-based systems that learn through credit assignment (the bucket brigade algorithm) and rule discovery (the genetic algorithm). They typically operate in environments that exhibit one or more of the following characteristics: (1) perpetually novel events accompanied by large amounts of noisy or irrelevant data; (2) continual, often real-time, requirements for action; (3) implicitly or inexactly defined goals; and (4) sparse payoff or reinforcement obtainable only through long action sequences. Classifier systems are designed to absorb new information continuously from such environments, devising sets of compet- ing hypotheses (expressed as rules) without disturbing significantly capabilities already acquired. This paper reviews the definition, theory, and extant applications of classifier systems, comparing them with other machine learning techniques, and closing with a discussion of advantages, problems, and possible extensions of classifier systems. Artificial Intelligence, 40 (1-3), 235-82.
See also:Qualitative Reasoning: Modeling and Simulation With Incomplete Knowledge. MIT Press, 1994.Abstraction by Time-Scale in Qualitative Simulation (Extended Abstract). Qualitative Physics Workshop, University of Illinois, 1987.THE LIMITS OF QUALITATIVE SIMULATION.Qualitative Simulation as Causal Explanation, Systems, Man and Cybernetics, IEEE Transactions on , vol.17, no.3, pp.432,444, May 1987.Taming Intractible Branching in Qualitative Simulation. IJCAI-87.Qualitative simulation: then and now. In Artificial Intelligence in Perspective, D.G. Bobrow (ed.), MIT Press, 1994.Non-Intersection of Trajectories in Qualitative Phase Space: A Global Constraint for Qualitative Simulation. AAAI-88.Artificial Intelligence 29:289-338