Artificial Intelligence - Revision history

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← Older revision		Revision as of 02:24, 16 December 2021
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	* [[Artificial Intelligence/Agent Learning \| Agent Learning]]		* [[Artificial Intelligence/Agent Learning \| Agent Learning]]
	* [[Artificial Intelligence/Constraint Satisfaction \| Constraint Satisfaction]]		* [[Artificial Intelligence/Constraint Satisfaction \| Constraint Satisfaction]]
			* [[Artificial Intelligence/Logic Types \| Logic Types]]

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	* [[Artificial Intelligence/Knowledge Representation \| Knowledge Representation]]		* [[Artificial Intelligence/Knowledge Representation \| Knowledge Representation]]
	* [[Artificial Intelligence/Agent Learning \| Agent Learning]]		* [[Artificial Intelligence/Agent Learning \| Agent Learning]]
			* [[Artificial Intelligence/Constraint Satisfaction \| Constraint Satisfaction]]

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	* [[Artificial Intelligence/Basic Problem Solving \| Basic Problem Solving]]		* [[Artificial Intelligence/Basic Problem Solving \| Basic Problem Solving]]
	** [[Algorithms/Search Types \| Search Algorithms for AI]]		** [[Algorithms/Search Types \| Search Algorithms for AI]]
			* [[Artificial Intelligence/Knowledge Representation \| Knowledge Representation]]
			* [[Artificial Intelligence/Agent Learning \| Agent Learning]]

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← Older revision		Revision as of 22:30, 5 October 2021
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	See also:		See also:
	* [[Artificial Intelligence/Intelligent Agents \| Intelligent Agents]]		* [[Artificial Intelligence/Intelligent Agents \| Intelligent Agents]]
	* [[Algorithms/Search Types \| Search Algorithms for AI]]		* [[Artificial Intelligence/Basic Problem Solving \| Basic Problem Solving]]
			** [[Algorithms/Search Types \| Search Algorithms for AI]]

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← Older revision		Revision as of 18:47, 5 October 2021
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	See also:		See also:
	* [[Artificial Intelligence/~~Implementation~~ \| ~~AI Implementation~~]]		* [[Artificial Intelligence/Intelligent Agents \| Intelligent Agents]]
	* [[Algorithms/Search Types \| Search Algorithms for AI]]		* [[Algorithms/Search Types \| Search Algorithms for AI]]

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 Artificial Intelligence (AI) was originally coined in 1956 to describe "machines capable of performing tasks which have characteristics resembling human intelligence".<br>
 As of 2021, AI now describes theory and development of overall systems which "can perform tasks that normally require human intelligence".
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 * Agent - An entity that can act. Generally does so to achieve the "best possible" outcome.
 * Intelligent Agent - An agent that takes input from the environment in some manner.
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-== Condensed History of Major Events in AI ==
+== AI Timeline ==
 * 1943 - McCulloch and Pitts - Introduced the concept of [[Neural Networks]].
 * 1949-1950 - Hebb and Minsky - Improved methods of building Neural Network weights.
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 * 2001-Present - Internet of Things (IoT). Also, the "big data" boom, in large part due to easy accessibility to "the cloud".
 * 2011-Present - Deep learning boom. Processing of complex subjects became more computational feasible, and we already had the "big data" storage to supplement it.
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 Note that it's often far less useful to make an AI that "thinks" in the desired way but takes no corresponding action.<br>
 Thus discussion tends towards AI that takes action in some manner.
 === Humanistic AI Systems ===
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 In particular, these types of AI have been used to try to emulate emotions, creation of types of art (such as generating music), and otherwise dynamically respond to humans.
 === Rational AI Systems ===

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	* Economics - Theory of actors/individuals making rational decisions. on both micro and macro scale.		* Economics - Theory of actors/individuals making rational decisions. on both micro and macro scale.
	* Linguistics - Determining complicated knowledge representations.		* Linguistics - Determining complicated knowledge representations.


			== Condensed History of Major Events in AI ==
			* 1943 - McCulloch and Pitts - Introduced the concept of [[Neural Networks]].
			* 1949-1950 - Hebb and Minsky - Improved methods of building Neural Network weights.
			* 1956 - Dartmouth Conference - Coined the term "Artifical Intelligence". Created major programs that would build the foundation for the first decades of AI research.
			* 1952-1969 - Early stages of AI growth.
			* 1969-1986 - Expert systems came about from domain specific knowledge. Such as early medical systems designed to help diagnose patients.
			* 1986 - Probabilistic reasoning and machine learning was introduced. Prior to this, it was difficult to represent uncertainties and probabilities.
			* 2001-Present - Internet of Things (IoT). Also, the "big data" boom, in large part due to easy accessibility to "the cloud".
			* 2011-Present - Deep learning boom. Processing of complex subjects became more computational feasible, and we already had the "big data" storage to supplement it.

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Artificial Intelligence (AI) was originally coined in 1956 to describe "machines capable of performing tasks which have characteristics resembling human intelligence". 
As of 2021, AI now describes theory and development of overall systems which "can perform tasks that normally require human intelligence".

A few examples are:
* Visual Perception
* Speech Recognition
* Decision Making
* Language Translation

== Terminology ==
* Agent - An entity that can act. Generally does so to achieve the "best possible" outcome.
* Intelligent Agent - An agent that takes input from the environment in some manner.

== Related Fields ==

{{ todo | Link to these related wiki pages, if applicable. }}
By now, almost every field you can think of has some application of AI either being used, or actively developed. 
But some of the fields that originally contributed to the foundations of AI are:
* Philosophy - Examination of logic, reasoning, and the mind as a physical system.
* Mathematics - Introduction of lgorithms, computers, formal proofs.
* Psychology - Study of adaptation, perception, motor control.
* Economics - Theory of actors/individuals making rational decisions. on both micro and macro scale.
* Linguistics - Determining complicated knowledge representations.

== Turing Tests ==
The "turing test" is one of the first tests for classifying something as an AI. 
In short, a system passes this test if it can behave in such a manner that its behavior is indistinguishable from a human's behavior.

The original test goes as follows:
* Test has a single human "interrogator" in one room. This interrogator has access to a terminal.
* Then in a different room, one or more other humans participate and have access to a separate terminal.
* At least one AI participant is also present, and communicates through the terminals as well.
* The goal is for the interrogator to determine which other participants are AI, and which ones are humans.

The point of all this is to answer the questions such as:
* "Can machines think?"
* "Can computers imitate humans?"
* "Are computers able to fool humans?"

While this is neat idea, this base concept isn't very compatible with mathematical analysis. 
In other words, it is very hard to objectively analyze or quantify in any meaningful way.

== General Types of AI ==

Generally speaking, AI can focus on either thinking or acting. And they try to do so either "rationally", or "like humans".

Note that it's often far less useful to make an AI that "thinks" in the desired way but takes no corresponding action. 
Thus discussion tends towards AI that takes action in some manner.

=== Humanistic AI Systems ===
Entire schools of thought have stemmed from researching how to make AI "like humans". 
For example, Cognitive Science and Cognitive Neuroscience have both been created to learn how humans behave.

In particular, these types of AI have been used to try to emulate emotions, creation of types of art (such as generating music), and otherwise dynamically respond to humans.

=== Rational AI Systems ===
"Rational behavior" is generally associated with logical "correct/false" thinking. IE: "This task was done correctly."

The problem with attributing everything to rationality is that not everything can be associated with "right and wrong". 
Some ideas and concepts have a degree of uncertainty. While others are simply not easily expressible in objective "this is correct" analysis.

Note that a "rational system" can still be rational, even when it makes "incorrect" decisions. 
A system is still considered rational as long as it makes "the most rational choice possible" at every given moment, using the information it had available. 
The problem comes in when an AI system does not have full knowledge at a given moment, due to the environment or other factors. See below section for further details.

← Older revision		Revision as of 02:24, 16 December 2021
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	* [[Artificial Intelligence/Agent Learning \| Agent Learning]]		* [[Artificial Intelligence/Agent Learning \| Agent Learning]]
	* [[Artificial Intelligence/Constraint Satisfaction \| Constraint Satisfaction]]		* [[Artificial Intelligence/Constraint Satisfaction \| Constraint Satisfaction]]
			* [[Artificial Intelligence/Logic Types \| Logic Types]]

← Older revision		Revision as of 05:40, 14 December 2021
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	* [[Artificial Intelligence/Knowledge Representation \| Knowledge Representation]]		* [[Artificial Intelligence/Knowledge Representation \| Knowledge Representation]]
	* [[Artificial Intelligence/Agent Learning \| Agent Learning]]		* [[Artificial Intelligence/Agent Learning \| Agent Learning]]
			* [[Artificial Intelligence/Constraint Satisfaction \| Constraint Satisfaction]]

← Older revision		Revision as of 20:00, 17 November 2021
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	* [[Artificial Intelligence/Basic Problem Solving \| Basic Problem Solving]]		* [[Artificial Intelligence/Basic Problem Solving \| Basic Problem Solving]]
	** [[Algorithms/Search Types \| Search Algorithms for AI]]		** [[Algorithms/Search Types \| Search Algorithms for AI]]
			* [[Artificial Intelligence/Knowledge Representation \| Knowledge Representation]]
			* [[Artificial Intelligence/Agent Learning \| Agent Learning]]

← Older revision		Revision as of 18:44, 12 October 2021
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	== Terminology ==		== Terminology ==
	* Agent - An entity that can act. Generally does so to achieve the "best possible" outcome.		* '''Agent''' - An entity that can act. Generally does so to achieve the "best possible" outcome.
	* Intelligent Agent - An agent that takes input from the environment in some manner.		* '''Intelligent Agent''' - An agent that takes input from the environment in some manner.
	* Expert Systems - Systems that generally require some kind of "domain knowledge". They must be explicitly told what do to before they can function.		* '''Expert Systems''' - Systems that generally require some kind of "domain knowledge". They must be explicitly told what do to before they can function.
	* Machine Learning - Systems that learn to solve problems by itself, over time. Generally requires a period of training before it can start.		* '''Machine Learning''' - Systems that learn to solve problems by itself, over time. Generally requires a period of training before it can start.
	* Neural Networks - Systems that attempt to mimic the human brain by having "nodes". These nodes are mathematically weighted, which controls what triggers on given input.		* '''Neural Networks''' - Systems that attempt to mimic the human brain by having "nodes". These nodes are mathematically weighted, which controls what triggers on given input.
	* Deep Learning - A ~~subtype~~ of neural networks which specifically have many layers of nodes.		* '''Deep Learning''' - A sub-type of neural networks which specifically have many layers of nodes.
	* Weak AI - AI that does only the specific, repetitive tasks it was programmed to do.		* '''Weak AI''' - AI that does only the specific, repetitive tasks it was programmed to do.
	* Strong AI - AI that has developed to learn tasks outside of what it was programmed to do.		* '''Strong AI''' - AI that has developed to learn tasks outside of what it was programmed to do.


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	But some of the fields that originally contributed to the foundations of AI are:		But some of the fields that originally contributed to the foundations of AI are:
	* Philosophy - Examination of logic, reasoning, and the mind as a physical system.		* Philosophy - Examination of logic, reasoning, and the mind as a physical system.
	* Mathematics - Introduction of ~~lgorithms~~, computers, formal proofs.		* Mathematics - Introduction of logarithms, computers, formal proofs.
	* Psychology - Study of adaptation, perception, motor control.		* Psychology - Study of adaptation, perception, motor control.
	* Economics - Theory of actors/individuals making rational decisions. on both micro and macro scale.		* Economics - Theory of actors/individuals making rational decisions. on both micro and macro scale.
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	=== Tentative Future of AI ===		=== Tentative Future of AI ===
	The expected future of AI (as of 2021) can be described in by the following stages:		The expected future of AI (as of 2021) can be described in by the following stages:
	* Artificial Narrow Intelligence (ANI) - AI that performs specific, narrow tasks. We are here.		* '''Artificial Narrow Intelligence''' (ANI) - AI that performs specific, narrow tasks. We are here.
	* Artificial General Intelligence (AGI) - AI that performs broad tasks. More importantly, can self-improve.		* '''Artificial General Intelligence''' (AGI) - AI that performs broad tasks. More importantly, can self-improve.
	** Generally has abilities roughly comparable to general human capabilities.		** Generally has abilities roughly comparable to general human capabilities.
	** This may lead to AI that starts competing for human jobs.		** This may lead to AI that starts competing for human jobs.
	* Artificial Super Intelligence (ASI) - AI that demonstrates high levels of intelligence and growth.		* '''Artificial Super Intelligence''' (ASI) - AI that demonstrates high levels of intelligence and growth.
	** Generally has abilities that far exceed human capabilities.		** Generally has abilities that far exceed human capabilities.
	** May end up being either very beneficial, or very detrimental to human society.		** May end up being either very beneficial, or very detrimental to human society.
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	Note that, as described below, both AI that "behaves humanly" and AI that "behaves rationally" have a place.<br>		Note that, as described below, both AI that "behaves humanly" and AI that "behaves rationally" have a place.<br>
	Which one is "better" depends on what the desired application is. But a majority of modern AI usage tends towards rational ones.		Which one is "better" depends on what the desired application is. But a majority of modern AI usage tends towards rational ones.


	=== Humanistic AI Systems ===		=== Humanistic AI Systems ===
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	However, note that humans have positive and negative emotions. As well as irrational emotions and behaviors.<br>		However, note that humans have positive and negative emotions. As well as irrational emotions and behaviors.<br>
	AI typically don't benefit from this, and it can be a very complex matter to explore.		AI typically don't benefit from this, and it can be a very complex matter to explore.


	=== Rational AI Systems ===		=== Rational AI Systems ===
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	Note that a "rational system" can still be rational, even when it makes "incorrect" decisions.<br>		Note that a "rational system" can still be rational, even when it makes "incorrect" decisions.<br>
	A system is still considered rational as long as it makes "the most rational choice possible" at every given moment, using the information it had available.<br>		A system is still considered rational as long as it makes "the most rational choice possible" at every given moment, using the information it had available.<br>
	The problem comes in when an AI system does not have full knowledge at a given moment, due to the environment or other factors. See ~~below section~~ for further details.		The problem comes in when an AI system does not have full knowledge at a given moment, due to the environment or other factors. See [[Artificial Intelligence/Intelligent Agents \| Intelligent Agents]] for further details.