By Andreas L. Symeonidis
Wisdom, hidden in voluminous information repositories typically created and maintained by means of todays functions, could be extracted through facts mining. the next move is to rework this found wisdom into the inference mechanisms or just the habit of brokers and multi-agent structures. Agent Intelligence via facts Mining addresses this factor, in addition to the debatable problem of producing intelligence from facts whereas shifting it to a separate, very likely independent, software program entity. This booklet incorporates a method, instruments and strategies, and a number of other examples of agent-based purposes built with this procedure. This quantity focuses ordinarily at the use of knowledge mining for smarter, extra effective brokers.
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Additional info for Agent intelligence through data mining
Choose a data mining algorithm Select method(s) to be used for searching for patterns in the data. 7. Apply data mining 8. Evaluate data mining results Interpret mined patterns, possibly return to steps 1-7 for further iteration. Data Mining and Knowledge Discovery: A brief overview 15 9. Consolidate discovered knowledge Incorporate this knowledge into another system for further action, or simply document it and report it to interested parties. 4 Organizing Data Mining Techniques Data Mining can be applied to the vast majority of data organization schemes, most popular of which are the relational databases and data warehouses, as well as various transactional databases.
Wooldridge & Jennings have succeeded in combining general agent features into the following generic, nevertheless abstract, definition: An agent is a computer system that is situated in some environment, and that is capable of autonomous action in this environment, in order to meet its design objectives [Wooldridge and Jennings, 1995]. It should be denoted that Wooldridge & Jennings defined the notion of an "agent" and not an "intelligent agent". When intelligence is introduced, things get more complicated, since a nontrivial part of 42 AGENT INTELLIGENCE THROUGH DATA MINING the research community believes that true intelligence is not feasible [Nwana, 1995].
Data Mining and Knowledge Discovery: A brief overview 15 9. Consolidate discovered knowledge Incorporate this knowledge into another system for further action, or simply document it and report it to interested parties. 4 Organizing Data Mining Techniques Data Mining can be applied to the vast majority of data organization schemes, most popular of which are the relational databases and data warehouses, as well as various transactional databases. Data mining is also used on a variety of advanced databases and information repositories, such as the object-oriented databases, spatial and temporal databases, text and multimedia databases, heterogeneous and legacy databases, and, finally, genomics databases and the world wide web (www) databases.
Agent intelligence through data mining by Andreas L. Symeonidis