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Abstract intelligent agent : ウィキペディア英語版
Intelligent agent

In artificial intelligence, an intelligent agent (IA) is an autonomous entity which observes through sensors and acts upon an environment using actuators (i.e. it is an agent) and directs its activity towards achieving goals (i.e. it is "rational", as defined in economics). Intelligent agents may also learn or use knowledge to achieve their goals. They may be very simple or very complex: a reflex machine such as a thermostat is an intelligent agent.〔According to the definition given by 〕
Intelligent agents are often described schematically as an abstract functional system similar to a computer program. For this reason, intelligent agents are sometimes called abstract intelligent agents (AIA) to distinguish them from their real world implementations as computer systems, biological systems, or organizations. Some definitions of intelligent agents emphasize their autonomy, and so prefer the term autonomous intelligent agents. Still others (notably ) considered goal-directed behavior as the essence of intelligence and so prefer a term borrowed from economics, "rational agent".
Intelligent agents in artificial intelligence are closely related to agents in economics, and versions of the intelligent agent paradigm are studied in cognitive science, ethics, the philosophy of practical reason, as well as in many interdisciplinary socio-cognitive modeling and computer social simulations.
Intelligent agents are also closely related to software agents (an autonomous computer program that carries out tasks on behalf of users). In computer science, the term ''intelligent agent'' may be used to refer to a software agent that has some intelligence, regardless if it is not a rational agent by Russell and Norvig's definition. For example, autonomous programs used for operator assistance or data mining (sometimes referred to as ''bots'') are also called "intelligent agents".
==A variety of definitions==

Intelligent agents have been defined many different ways.〔Some definitions are examined by and .〕 According to Nikola Kasabov IA systems should exhibit the following characteristics:
* Accommodate new problem solving rules incrementally
* Adapt online and in real time
* Are able to analyze itself in terms of behavior, error and success.
* Learn and improve through interaction with the environment (embodiment)
* Learn quickly from large amounts of data
* Have memory-based exemplar storage and retrieval capacities
* Have parameters to represent short and long term memory, age, forgetting, etc.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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