Download Agent intelligence through data mining by Andreas L. Symeonidis PDF

By Andreas L. Symeonidis

Wisdom, hidden in voluminous info repositories sometimes created and maintained by way of todays functions, might be extracted by means of facts mining. your next step is to remodel this stumbled on wisdom into the inference mechanisms or just the habit of brokers and multi-agent structures. Agent Intelligence via information 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 e-book incorporates a method, instruments and methods, and several other examples of agent-based functions constructed with this method. This quantity focuses in most cases at the use of information mining for smarter, extra effective brokers.

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They could also be used as a roadmap for developing agent-based applications in three rather broad areas. These chapters can be read in any order depending on the reader's preferences or research interests. Having gone at least through the material in Chapters 6 and 7, the reader must have recognized the need and benefits of agent retraining and should be ready for Chapter 9. The last chapter can be read at any stage, even after this introduction, but its contents will be clearer to those of you who can wait till the end.

1 Intelligent Agents Agent Definition Although the word agent is used in a multitude of contexts and is part of our everyday vocabulary, there is no single all-encompassing meaning for it. Perhaps, the most widely accepted definitions for this term is that "an agent acts on behalf of someone else, after having been authorized". This definition can be applied to software agents, which are instantiated and act instead of a user or a software program that controls them. Thus, one of the most characteristic agent features is its agency.

4- A sample decision tree Decision trees are often used as inference engines or knowledge models to implement the behavior of agents. Since we are going to use them extensively in subsequent chapters, we present the ID3 algorithm in more detail, so that the unfamiliar reader can better comprehend the way DTs are built. 1 AGENT INTELLIGENCE THROUGH DATA MINING The ID3 algorithm ID3 aims to minimize the number of iterations during classification of a new data tuple and can be applied only to categorical data.

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