Intelligent (AI) Information System

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An Intelligent (AI) Information System is an intelligent system that is an information processing system that implements AI algorithms to solve automated intelligence tasks.



References

2024-11-16

[1] https://www.vationventures.com/research-article/cognitive-ai-explained-impact-and-future-in-the-digital-world
[2] https://innovationatwork.ieee.org/can-artificial-intelligence-ai-learn/
[3] https://trainingindustry.com/articles/artificial-intelligence/forget-forgetting-ai-driven-strategies-for-learning-retention/
[4] https://cbmm.mit.edu/sites/default/files/documents/Langley_AAAI17_SoI.pdf
[5] https://www.mdpi.com/2227-7390/11/11/2420
[6] https://www.sciencedirect.com/science/article/pii/S2666920X2100014X
[7] https://csuglobal.edu/news-stories-press?type=post%2Fhow-does-ai-actually-work
[8] https://www.forbes.com/sites/cognitiveworld/2019/11/16/can-artificial-intelligence-learn-tolearn/

2021

  • (Pretz, 2021) ⇒ Kathy Pretz (2021). "Stop Calling Everything AI, Machine-Learning Pioneer Says". In: IEEE Spectrum.
    • Stop Calling Everything AI, Machine-Learning Pioneer Says Michael I. Jordan explains why today’s artificial-intelligence systems aren’t actually intelligent
    • QUOTE: ... Despite such developments being referred to as “AI technology," he writes, the underlying systems do not involve high-level reasoning or thought. The systems do not form the kinds of semantic representations and inferences that humans are capable of. They do not formulate and pursue long-term goals.

      “For the foreseeable future, computers will not be able to match humans in their ability to reason abstractly about real-world situations," he writes. “We will need well-thought-out interactions of humans and computers to solve our most pressing problems. We need to understand that the intelligent behavior of large-scale systems arises as much from the interactions among agents as from the intelligence of individual agents." ...

2013

2012

  • (Wikipedia, 2012) ⇒ http://en.wikipedia.org/wiki/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). 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, as is a human being, as is a community of human beings working together towards a goal.

      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 (Russell & Norvig, 2003) 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 software 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".


2010a

2009a

2009b

  • (Intelligent Systems, 2009) ⇒ http://www.intelligent-systems.com.ar/intsyst/defintsi.htm
    • It is a system.
    • It learns during its existence. (In other words, it senses its environment and learns, for each situation, which action permits it to reach its objectives.)
    • It continually acts, mentally and externally, and by acting reaches its objectives more often than pure chance indicates (normally much oftener).
    • It consumes energy and uses it for its internal processes, and in order to act.

1998

1959

  • (Samuel, 1959) ⇒ Arthur L. Samuel. (1959). “Some Studies in Machine Learning Using the Game of Checkers.” IBM Journal of research and development 3, no. 3