Artificial Intelligence and Cognitive Science: 13th Irish by Miguel A. Alonso, Jesús Vilares, Víctor M. Darriba (auth.),

Artificial Intelligence and Cognitive Science: 13th Irish by Miguel A. Alonso, Jesús Vilares, Víctor M. Darriba (auth.),

By Miguel A. Alonso, Jesús Vilares, Víctor M. Darriba (auth.), Michael O’Neill, Richard F. E. Sutcliffe, Conor Ryan, Malachy Eaton, Niall J. L. Griffith (eds.)

This booklet constitutes the refereed lawsuits of the thirteenth Irish foreign convention on synthetic Intelligence and Cognitive technology, AICS 2002, held in Limerick, eire in September 2002.
The sixteen revised complete papers and 17 revised brief papers provided have been rigorously reviewed and chosen for inclusion within the booklet. one of the subject matters addressed are cognitive modeling, case-based reasoning, constraint processing, info mining, evolutionary computation, clever brokers, info retrieval, wisdom illustration, reasoning, desktop studying, typical language processing, neural networks, notion, AI making plans, robotics, and scheduling.

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Extra resources for Artificial Intelligence and Cognitive Science: 13th Irish Conference, AICS 2002 Limerick, Ireland, September 12–13, 2002 Proceedings

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But what conceptual repertoire might support a more insightful analyse of the internal dynamics of an agent of this kind? Dynamic systems theory is an established candidate [2,8], with analyses typically couched in terms of different types of attractor and of trajectories to and from them. An arguably more attractive possibility is, where appropriate, to find interpretations of the solutions in terms of higher-level cognitive processes such as predictive planning. This possibility is discussed in [3].

The above sentence is normally read as two intonational phrases (separated at the comma), so we can re-express the sequence of measurements such that each interval is now given as a proportion of the containing IP (or the measurement points most nearly located at the two ends of that IP). This is also a vector of intervals, but each is expressed as a function of the overall temporal organization of the phrase. Something rather surprising happens when we consider the similarity of two utterances using these two measures.

It also demonstrates RADAR’s ability to retrieve creative analogies such as the “Nuclear war is like a game of tic-tac-toe”, which again current models cannot retrieve. Identical results were obtained when presented other structurally identical domains that do share some semantic similarity, again Plate’s “Spot bit Jane causing Jane to flee from Spot”, Gick and Holyoak’s [8] surgeon/general analogy, etc. These domains contain identical structural and RADAR, as expected, retrieves the identical sources based on identical structural attribute values.

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