Representation Methods in AI. Searching by Graphs

• Main Author: Angel GARRIDO
• Format: Article
• Language: English
• Published: Editura Universităţii "Petru Maior" 2012-12-01
• Series: Scientific Bulletin of the ''Petru Maior" University of Tîrgu Mureș
• Subjects: knowledge representation; heuristic; graph theory; bayesian networks; A I.
• Online Access: http://scientificbulletin.upm.ro/papers/2012/v2/A.GARRIDO%20-%20Representation%20Methods%20in%20AI.%20Searching%20by%20Graphs.pdf
• ISSN: 1841-9267; 2285-438X

The historical origin of the Artificial Intelligence (A I) is usually established in the Darmouth Conference, of 1956. But we can find many more arcane origins [1]. Also, we can consider, in more recent times, very great thinkers, as Janos Neumann (then, John von Neumann, arrived in USA), Norbert Wiener, Alan Mathison Turing, or Lofti Zadehfor instance [6, 7]. Frequently A I requires Logic. But its classical version shows too many insufficiencies. So, it was necessary to introduce more sophisticated tools, as fuzzy logic, modal logic, non-monotonic logic and so on [2]. Among the things that A I needs to represent are: categories, objects, properties, relations between objects, situations, states, time, events, causes and effects, knowledge about knowledge, and so on. The problems in A I can be classified in two general types [3, 4]: search problems and representation problems. In this last “mountain”, there exist different ways to reach their summit. So, we have [3]: logics, rules, frames, associative nets, scripts and so on, many times connectedamong them. We attempt, in this paper, a panoramic vision of the scope of application of such Representation Methods in A I. The two more disputable questions of both modern philosophy of mind and A I will be Turing Test and The Chinese Room Argument. To elucidate these very difficult questions, see both final Appendices.