Defining Intelligence
From ResearchID.org
Scope
The scope of this project is to generate consistent formalized teleological definitions of intelligence that are tractable and measurable. This is to be achieved by use of other existing branches of science.
The definition of Intelligence is too broad, so it is necessary to break it down into constituent characteristics that can each be defined separately. It will then be shown how each characteristic of intelligence can be quantitatively measured.
Many Definitions of Intelligence
There are many definitions of intelligence because Intelligence is too broad of a subject for any one simplistic definition to cover alone. There is no need to develop many new concepts for intelligence, but rather merely recognizing and categorizing current concepts like foresight, volition, imagination, awareness, knowledge, understanding and wisdom and cross referencing these concepts across the disciplines of engineering design, artificial intelligence, IQ testing, and human cognition. Failure to recognize the various characteristics within the definition of intelligence is like failure to recognize the various parts of an automobile or the various parts and systems of the human body. It will then be shown how each characteristic of intelligence can be quantitatively measured.
An example of why this is important can be seen in how IBM's Deep Blue computer had enough of the intelligence characteristic of foresight to see many levels deep into chess games so that it was able to beat the world's best chess player, but is an idiot savant when it comes to its ability to frame (define) new problems that are not related to the game of chess. It was not intelligent at all in the area of volition and its internal chess game simulation modeling tools (imagination) and knowledge database were specifically designed for only the game of chess. In other words, it is not capable of deciding to do something different by its own volition as in learning space navigation like NASA's Deep Space 1.
Simplistic definitions of intelligence are clearly inadequate to capture all that is required to operate above an idiot savant level of intelligence. How do we define intelligence in a way that unifies many definitions in various fields of study?
A General Theory of Intelligence
The application of pioneering Teleological Engineering Design in the areas of AI and control systems theory, as well as, in the fields of cognitive psychology and IQ testing psychology has already provided foundational groundwork for a general theory of intelligence. Michael Behe's work in the area of Irreducible Complexity(IC) is a huge step towards explaining how those foundational teleological intelligence fields applies to IDT. In fact, the definition of purposeful behavior (Teleology) of the Weiner paper matches what is required to produce irreducible complexity; compare them here:
- "The term purposeful is meant to denote that the act or behavior may be interpreted as directed to the attainment of a goal – i.e., to a final condition in which the behaving object reaches a definite correlation in time or in space with respect to another object or event."
- According to William Dembski in his No Free Lunch, Irreducible Complexity is explained as:
- "A system performing a given basic function is irreducibly complex if it includes a set of well-matched, mutually interacting, non-arbitrarily individuated parts such that each part in the set is indispensable to maintaining the system's basic, and therefore original, function. The set of these indispensable parts is known as the irreducible core of the system."[1] Irreducible_Complexity
So the definition of IC describes the results of purposeful behavior, while the definition of purposeful behavior describes what is required to produce IC systems. This leads to the creation of the ultimate of purposeful behavior, it is what is called Accurate and Precise Irreducibly Complex Behavior.
The baggage of IQ testing, AI research, and ID may all be one in the same; that is namely, lack a General Theory of Intelligence. Further Research presented here into the definition of various intelligence characteristics is expected to lead to a more universally accepted General Theory of Intelligence that will be based on foundational scientific concepts that are already well established. This will require more consistency of terms and concepts across all areas of study. Please notice how the definitions presented on this page are consistent with the Preliminary Definitions section found below.
For Intelligent Design Theory, this will also allow for an intelligence model of the ID designer that can also be shown to be more than just an idiot savant, mostly in that a wide variety of systems (showing evidence of volition, vivid imagination, and wisdom) have already been found to be required to form the abstract model written in DNA, as well as, the self-replication machinery required by the first living cells.
A Behavioral Model of the Internal Dynamics of the Designer
In response to Robin Collins' proposal, this is a proposal of a general teleological and behavioristic model definitions that apply to the internal dynamics of any designer, whether human, artificial, extraterrestrial, or transcendent. These definitions need to be examined from the origin of life (OOL) perspective to avoid circular reasoning (as in this link) that invokes mechanisms like RM&NS that could not possibly operate before the first self-replicating cell.
(See more at: A Behavioral Model of the Internal Dynamics of the Designer)
Behavioristic Method of Study
-the behavioristic method of study omits the specific structure and the intrinsic organization of the object. This omission is fundamental because on it is based the distinction between the behavioristic and the alternative functional method of study. Today engineers call this black box testing. It is performed on active objects that perform work. Since designers perform work to create designed objects, then it is also the way to analyze objects for evidence of the active behavior of that is necessary to bring about complex and precise structures found within objects that are under investigation for having been designed.
On the other hand, in a functional method of study, as opposed to a behavioristic approach, the main goal is the intrinsic organization of the entity studied, its structure and its properties; the relations between the object and the surroundings are relatively incidental. Therefore, the "work" (active behavior) of a designer cannot be analyzed using this kind of functional analysis. This is the method of study that many ID critics use in a fundamentally flawed straw-man argument to invoke only natural causes for design. The scientific pioneers of cognitive study were already complaining of this flawed tendency well over 60 years ago as they advocated the behavioristic method of study. However, todays Engineers already know that the functional method of study is no way to analyze a designer or a design that has unknown intrinsic organization. This is also why an engineering perspective is the best way to investigate evidence for intelligent design.
( Click here to see more about the Behavioristic Method of Study)
Characteristics of Intelligence
Intelligence is not a binary quantity, but rather it is a range or spectrum that has many levels and also contains various types or characteristics. We do not need to develop new characteristic categories of intelligence. We already know them as:
- A. foresight,
- B. imagination,
- C. volition,
- D. wisdom
- E. and understanding.
This is not to say that these are the complete list of characteristics for a general theory of intelligence, but only a starting list of some of the most important. It is important to recognize the minimum levels of each characteristic of intelligence in design detection. Design behavior--the activity of designing something-- is a purposeful behavior that requires a minimum level of intelligence that corresponds to the complexity of the design.
The purpose of the characteristics of intelligence cognitive framework is to form a behavioral model of a designer that can be used to make predictions and in conducting research in design detection. Please study Robin Collins' paper, as well as, critical analysis of AI, IQ, and ID if you have not already.
We need to recognize that many of the objections that IQ critics have with IQ scores or the objections that AI system users have with artificial intelligence or that Intelligent Design critics have with ID are all based on false conclusions about the presence or absence of intelligence in only one or two areas of cognition. However, the problems that they see is more likely in not recognizing the importance of evaluating each and every major area of cognition when considering intelligence.
These intelligence characteristics form the "internal dynamics" that are used to represent that behavioral model of the designer. This may be a good way to use what we know about traditional IQ testing to map to what we know about cognitive abilities. By carefully examining objects for evidence of design, we can look for testable evidence for things like for example:
- language ability that can be mapped to the basic cognitive abilities like knowledge, foresight, imagination, and awareness of various range levels.
- Studying evidence for numerical competence would map to understanding and knowledge.
- Studying evidence for Abstract thinking would involve mapping to understanding and imagination.
- Studying evidence for problem formulation would map to volition.
So this kind of mapping may be a good way to show a separation between the detected evidence for various intelligence characteristics.
Again, by testing humans in various traditional IQ testing where we map the results to cognitive abilities, we should be able to separate the results in a meaningful way that corresponds to various types of design abilities. The testing of humans will serve as a baseline for each characteristic of intelligence (where the average human score will be 100 points just as in IQ testing), however; the scores of Designer of life may prove to be far above and beyond human scores as more research shows the extent of complexity found within microscopic nano-machines that are found within living cells.
Detecting Characteristics of Intelligence in design
Studying Characteristics of Intelligence in human cognition, Characteristics of Intelligence in IQ testing, and Characteristics of Intelligence in Artificial Intelligence
Formalized Definitions
Awareness
- Perception. The ability to monitor the environment (using appropriate and adequate sensory receptors) of a "controlled quantity" while using purposeful behavior.
This is a prerequisite to Self awareness, understanding, and purposeful goal directed behavior.
Studying Awareness in human cognition, Awareness in IQ testing, and Awareness in Artificial Intelligence
(Also see Purposeful Behavior, Negative Feedback Control Systems, model, imagination, understanding, and goal)
Self Awareness
- The ability to include ones self in a virtual world imagination model of ones own real world environment. This includes the ability to evaluate one's strengths and weaknesses in order to take self improvement actions and to use thought experiment simulations to evaluate the extrapolated changes. This also includes understanding of the significant implications of possible model simulation test results from real world condition and positional feedback. This is not the same as being aware of only virtual world objects that have no sensory feedback from the real world.
(Also see Awareness, model, and imagination)
Foresight
- Use of Extrapolated Future conditions (usually consisting of multilevel hierarchical extrapolations) that are modeled in the imagination using memory of past conditions, as well as, current conditions to take insightful action. This is a pre-requisite to Extrapolated Predictive behavior, or Extrapolative behavior.
This definition is supported by the class of behavior called "predictive behavior" in the paper "BEHAVIOR, PURPOSE AND TELEOLOGY"
Studying foresight in human cognition, foresight in IQ testing, and foresight in Artificial Intelligence
(Also see Irreducibly Complex Behavior and Predictive Behavior)
Imagination
- is a virtual world modeling environment where intelligent agents have control of constants like time, gravity and size of objects to model, practice, and simulate the results of their plans, goals, and priorities. Intelligent agents have the capacity to venture far into the past and future and even go beyond great distances to evaluate our situations and plans in life by creating internal models of our environment. This is accomplished in the virtual worlds of the imagination. It is a required tool necessary for foresight in the design behavior characteristic called “predictive behavior”.
This definition is supported by the Good Regulator theorem "EVERY GOOD REGULATOR OF A SYSTEM MUST BE A MODEL OF THAT SYSTEM", as well as, by the Law of Regulatory Models
Detecting Imagination in design
Studying Imagination in human cognition, Imagination in IQ testing, and Imagination in Artificial Intelligence
(Also see Model, Predictive Behavior, and Thought Experiments)
Knowledge
- Learned, prioritized, organized data, Information Libraries, and Stored Models of the environment that has been observed or controlled. When information is learned, it becomes knowledge that can be used for understanding. Knowledge is generally learned, however; it becomes clear in AI systems that a certain minimum initial level of knowledge is required for intelligent systems to be able to interpret input: "... a machine which is to trail predictively a moving luminous object should not only be sensitive to light (e.g., by the possession of a photoelectric cell), but should also have the structure adequate for interpreting the luminous input."
This definition is supported by The Law of Requisite Knowledge. "In order to adequately compensate perturbations, a control system must "know" which action to select from the variety of available actions".
Studying Knowledge in human cognition, Knowledge in IQ testing, and Knowledge in Artificial Intelligence
(Also see Model, Understanding, volition and Thought Experiments)
Thought Experiments (Imagination Device)
http://plato.stanford.edu/entries/thought-experiment/
- "Thought experiments are devices of the imagination used to investigate the nature of things. We need only list a few of the well-known thought experiments to be reminded of their enormous influence and importance in the sciences: Newton's bucket, Maxwell's demon, Einstein's elevator, Heisenberg's gamma-ray microscope, Schrödinger's cat."
Predictive behavior is based on changing conditions with respect to time. However, well designed Imagination provides the ability to take simulated processes to extremes of time, size, gravity and other parameters to foresee the effects of what may otherwise be subtle problems. Engineers and scientists use these methods in their own imaginations (thought experiments), as well as, in virtual world simulations or accelerated life testing of products or theories.
(Also see Imagination, Volition, and Wisdom)
Understanding
- the ability to ascertain the significant activities (functions and procedures) and priorities required to control objects, events, or information by formation of imagination models and foresight. i.e. - putting experience together with the ability to properly analyze, evaluate and use information, data or knowledge. Foresight is important to understanding because the implications of future conditions, positions, and trends must be extrapolated, evaluated, prioritized, and considered to properly sort imagination models for proper storage and retrieval according to their importance. Therefore, foresight (predictive behavior and extrapolation) is a prerequisite to understanding.
"... a machine which is to trail predictively a moving luminous object should not only be sensitive to light (e.g., by the possession of a photoelectric cell), but should also have the structure adequate for interpreting the luminous input." http://www.uni-essen.de/~bj0063/doc/Wiener_1943.pdf
Detecting Understanding in design
Studying Understanding in human cognition, Understanding in IQ testing, and Understanding in Artificial Intelligence
Volition
- the ability to choose (by the capacity for rational or purposive or deliberate or premeditated choice) whether or not to act and also the ability to choose how to act (selecting from an unlimited variety of choices) in formulating new problems by setting goals for timing, as well as, prioritizing. Volition is necessary to devise thought experiments and "define" novel new problems from an infinite set of possibilities.
The ability to choose items from an otherwise infinite set of possibilities seems to be the key to the volition of intelligent agents to first define problems even before setting out to solve those new problems. Artificial Volition has thus far eluded Artificial Intelligence (AI) designers. One reason why it has eluded them is because volition is often defined as simply "decision making". But how does one make decisions (choices) without identifying a finite set of choices after firstly defining a problem to be solved and resolving to invest time, materials, work and other resources before taking action? Here is an example of problem definition and action mapping for a thermostat:
- if condition (perceived disturbance), _____ == > then action
- temperature too low _____________________ == > heat
- temperature high enough _________________ == > do not heat
However, the “if condition (perceived disturbance)” could also have been “speed too fast” mapped to an erroneous action of “heat”. These things are set by the volition of intelligent agents at the time of problem definition and setting of requirement goals and objectives. Again, each column is chosen from unlimited sets. So even DNA cannot possibly contain the infinite knowledge required to cover all the possibilities like the way intelligent agents show by novel new designs. This is not to say that intelligent agents have infinite knowledge, but rather this ability to constrain the set of knowledge to a finite size can only be accomplished by the intelligence characteristic that we call volition.
"Engineers do much more than build things. They perceive a need. Then, they develop something that will fit that need. The answer must be aesthetic, practical, economical, and safe. That’s where design comes in." http://www.jhu.edu/virtlab/finals/FINALS/2/2design.pdf
This need to "perceive a need" leads to the question: Do problems really exist before they are even defined? The word "problem" seems to be void of meaning when viewed from the perspective of the origin of life (Who perceived the need for living cells before they ever existed?). So the definition of the word "problem" requires the choices and decisions that are made by the volition of a designer to formulate, constrain, restrict, frame (see the Frame Problem of AI) or define problems.
This definition is supported by Ashby's Law of Requisite Variety, as well as, by The Law of Requisite Knowledge. "Ashby has called this principle the law of requisite variety: in active regulation only variety can destroy variety. It leads to the somewhat counterintuitive observation that the regulator must have a sufficiently large variety of actions in order to ensure a sufficiently small variety of outcomes in the essential variables E. This principle has important implications for practical situations: since the variety of perturbations a system can potentially be confronted with is unlimited, we should always try maximize its internal variety (or diversity), so as to be optimally prepared for any foreseeable or unforeseeable contingency."
Studying Volition in human cognition, Volition in IQ testing, and Volition in Artificial Intelligence
(Also see Autonomous Behavior, goal, ID-conceptualization, hierarchical systems, Accurate and Precise Irreducibly Complex behavior, and Thought Experiments)
Wisdom
- has to do with taking action with the best use of time, imagination, thought experiments, volition, knowledge (information, data, procedures), understanding, planning, prioritizing, and resources. It also has to do with using the best means of evaluating results of how well goals and priorities are met, as well as, evaluating the integrity of information and information sources (same as for Detecting Innovation) in striving for truth. As can be extrapolated from the reference papers listed below, very high orders or predictive behavior is required to attain wisdom.
It is one thing to have imagination machinery, but it is another thing to have the wisdom and understanding like Einstein to devise the parameters, as well as, properly interpreting the results of thought experiments that shows genius. Artificial Wisdom has thus far eluded Artificial Intelligence (AI) designers in that while chess programs like Deep Blue have high levels of predictive behavior of only one type, it has no wisdom or volition to learn other fields of study (idiot savant) without being reprogrammed and assigned to other tasks by intelligent agents. This is not to say that Artificial Wisdom will not one day be accomplished.
http://whyfiles.org/052einstein/genius.html
Studying Wisdom in human cognition, Wisdom in IQ testing, and Wisdom in Artificial Intelligence
(Also see Volition and Thought Experiments)
- Wisdom can be empirically tested quantitatively by examining the minimum amount each of work, understanding, proper prioritizing, and imagination memory required to model the functionality or environment that is being controlled for each level of predictive behavior in a hierarchical system. The ability to see through mis-information can also be measured. This can be accomplished by providing minimum resources of time, information, materials, and tools to solve difficult, multilevel problems. Problems can be designed to require specific levels of predictive behavior at each level of hierachy to solve.
Designed Systems
A number of design evidence features were required for the first living cell like Specified Complexity, Irreducible Complexity, Hierarchical Structure, Accuracy and Precision, designed autonomous behavior, front Loaded Knowledge and negative feedback control can all combine for extremely apparent design. Intelligent Design Theory has a very key advantage over theories that depend on natural undirected processes that depend on processes like random mutation and natural selection (RM&NS). The reason that this is important is because processes like natural selection cannot be invoked for the origin of the first self-replicating cell.
For more on this see: Designed Systems
(Also see Regulator and Goal)
Other Design items
Genius
http://whyfiles.org/052einstein/genius.html
- the ability to devise the parameters, as well as, properly interpreting the results of thought experiments. Predictive behavior is based on changing conditions with respect to time. However, well designed Imagination provides the ability to take simulated processes to extremes of time, size, gravity and other parameters to foresee the effects of what may otherwise be subtle problems. Engineers and scientists use these methods in their own imaginations (thought experiments), as well as, in virtual world simulations or accelerated life testing of products or theories.
(Also see Thought Experiments, Understanding, and Wisdom)
Goal
- Objective or set-point to be attained. The more specific the goals and requirements, the more complex, accurate, and precise the design will be and therefore, the more apparent and obvious the design will be for detection. Designs that are given subtle or vague general goals are more difficult to detect purpose and design. An example of a vague goal is as in the general purpose designed into an object to "provide fun". Accuracy and precision is measured in percent error of the actual value in relation to the goal.
DNA coding regions are used in gene expression to create very specific proteins and thusly indicate very obvious design as can be seen in the purposes of specific 3-D proteins as can be seen in how they are used in living cells.
Machine
"The living cell is a machine that obeys all of the known laws of physics. Within it is functional information, molecular machines, and is itself a very complex information-bearing code-program controlled machine operating with nano-scale precision. A machine can generally be seen as an energy-redirection force-multiplier, made with material formed into independent boundary conditions to fulfill proximate purposes." (From: Intelligent design, evolution, and the origin of life)
Model
- Something intended to serve as a pattern of something to be made. Dynamic models are used in simulations that are run in imagination systems.
The same behavioral "model" that is used in the science of Negative Feedback Control Systems Theory also applies to Purposeful Behavior like Design. Also it is important to note, this very same model applies to the Homeostasis systems found throughout living cells. Therefore, this is to propose that the Negative Feedback Control System model can be used as a far simpler model for the Origin of Life (OOL) computer simulations as opposed to the great complexity found in simulating the origin of the complete living cell.
(Also see Imagination, Regulator, and Negative Feedback Control System)
"The design of a complex regulator often includes the making of a model of the system to be regulated. The making of such a model has hitherto been regarded as optional, as merely one of many possible ways. m this paper a theorem is presented which shows, under very broad conditions, that any regulator that is maximally both successful and simple must be isomorphic with the system being regulated. (The exact assumptions are given.) Making a model is thus necessary. The theorem has the interesting corollary that the living brain, so far as it is to be successful and efficient as a regulator for survival, must proceed, in learning, by the formation of a model (or models) of its environment." EVERY GOOD REGULATOR OF A SYSTEM MUST BE A MODEL OF THAT SYSTEM
The need for the brain to model it's environment (for extrapolation ability that includes imagination machinery or environment simulation) and the study of cybernetics are both important to the design required by the ID designer.
Regulator (Closed Loop)
- A negative feedback control system
(Also see model, negative feedback control system, goal, purposeful behavior)
Work
Purposeful, goal directed behavior that sets specific constraints and achieves results that are above and beyond normal constraints of chance and natural undirected processes, like gravity for instance.
(Also see Machine, volition, and purposeful behavior)
Preliminary Definitions of Intelligence
1. The capacity to acquire and apply knowledge. 2. The faculty of thought and reason. 3. Superior powers of mind. See Synonyms at mind. An intelligent, incorporeal being, especially an angel. The American Heritage® Dictionary of the English Language, Fourth Edition Copyright © 2000 by Houghton Mifflin Company. Published by Houghton Mifflin Company. All rights reserved.
1. The capacity to acquire and apply knowledge, especially toward a purposeful goal. 2. An individual's relative standing on two quantitative indices, namely measured intelligence, as expressed by an intelligence quotient, and effectiveness of adaptive behavior. The American Heritage® Stedman's Medical Dictionary Copyright © 2002, 2001, 1995 by Houghton Mifflin Company. Published by Houghton Mifflin Company.
1 a : the ability to learn or understand or to deal with new or trying situations b : the ability to apply knowledge to manipulate one's environment or to think abstractly as measured by objective criteria (as tests) 2 : mental acuteness —in•tel•li•gent /in-'tel-&-j&nt/ adjective —in•tel•li•gent•ly adverb
Source: Merriam-Webster's Medical Dictionary, © 2002 Merriam-Webster, Inc.
mind
1. The human consciousness that originates in the brain and is manifested especially in thought, perception, emotion, will, memory, and imagination. 2. The collective conscious and unconscious processes in a sentient organism that direct and influence mental and physical behavior. 3. The principle of intelligence; the spirit of consciousness regarded as an aspect of reality. 4. The faculty of thinking, reasoning, and applying knowledge: Follow your mind, not your heart. 1. Individual consciousness, memory, or recollection: I'll bear the problem in mind. 2. A person or group that embodies certain mental qualities: the medical mind; the public mind. 3. The thought processes characteristic of a person or group; psychological makeup: the criminal mind.
2. Upper Southern U.S. To have in mind as a goal or purpose; intend.
[Middle English minde, from Old English gemynd. See men-1 in Indo-European Roots.]minder n.
Synonyms: mind, intellect, intelligence, brain, wit, 1reason These nouns denote the capacity of thinking, reasoning, and acquiring and applying knowledge. Mind refers broadly to the capacities for thought, perception, memory, and decision: “No passion so effectually robs the mind of all its powers of acting and reasoning as fear” (Edmund Burke). Intellect stresses knowing, thinking, and understanding: “Opinion is ultimately determined by the feelings, and not by the intellect” (Herbert Spencer). Intelligence implies solving problems, learning from experience, and reasoning abstractly: “The world of the future will be an ever more demanding struggle against the limitations of our intelligence” (Norbert Wiener). Brain suggests strength of intellect: We racked our brains to find a solution. Wit stresses quickness of intelligence or facility of comprehension: “There is no such whetstone, to sharpen a good wit and encourage a will to learning, as is praise” (Roger Ascham). Reason, the capacity for logical, rational, and analytic thought, embraces comprehending, evaluating, and drawing conclusions: “Since I have had the full use of my reason, nobody has ever heard me laugh” (Earl of Chesterfield). See also synonyms at tend2
Source: The American Heritage® Dictionary of the English Language, Fourth Edition Copyright © 2000 by Houghton Mifflin Company. Published by Houghton Mifflin Company. All rights reserved.
mind In addition to the idioms beginning with mind, also see back of one's mind; bear in mind; blow one's mind; boggle the mind; bring to mind; call to mind; change one's mind; come to mind; cross one's mind; frame of mind; go out of one's mind; great minds; half a mind; have a good mind to; in one's mind's eye; in one's right mind; know one's own mind; load off one's mind; lose one's mind; make up one's mind; meeting of the minds; never mind; of two minds; one-track mind; on one's mind; open mind; out of sight (out of mind); piece of one's mind; presence of mind; prey on (one's mind); put one in mind of; read someone's mind; set one's mind at rest; slip one's mind; speak one's mind; to my mind.
Source: The American Heritage® Dictionary of Idioms by Christine Ammer. Copyright © 1997 by The Christine Ammer 1992 Trust. Published by Houghton Mifflin Company.
mind (m nd)
n.
1. The human consciousness that originates in the brain and is manifested especially in thought, perception, emotion, will, memory, and imagination.
2. The collective conscious and unconscious processes in a sentient organism that direct and influence mental and physical behavior.
Source: The American Heritage® Stedman's Medical Dictionary Copyright © 2002, 2001, 1995 by Houghton Mifflin Company. Published by Houghton Mifflin Company.
Main Entry: mind
Pronunciation: 'mInd
Function: noun
1 : the element or complex of elements in an individual that feels, perceives, thinks, wills, and especially reasons
2 : the conscious mental events and capabilities in an organism
3 : the organized conscious and unconscious adaptive mental activity of an organism
Source: Merriam-Webster's Medical Dictionary, © 2002 Merriam-Webster, Inc.
mind n 1: that which is responsible for one's thoughts and feelings; the seat of the faculty of reason; "his mind wandered"; "I couldn't get his words out of my head" [syn: head, brain, psyche, nous] 2: recall or remembrance; "it came to mind" 3: an opinion formed by judging something; "he was reluctant to make his judgment known"; "she changed her mind" [syn: judgment, judgement] 4: an important intellectual; "the great minds of the 17th century" [syn: thinker, creative thinker] 5: attention; "don't pay him any mind" 6: your intention; what you intend to do; "he had in mind to see his old teacher"; "the idea of the game is to capture all the pieces" [syn: idea] 7: knowledge and intellectual ability; "he reads to improve his mind"; "he has a keen intellect" [syn: intellect] v 1: be offended or bothered by; take offense with, be bothered by; "I don't mind your behavior" 2: be concerned with or about something or somebody 3: be in charge of or deal with; "She takes care of all the necessary arrangements" [syn: take care] 4: pay close attention to; give heed to; "Heed the advice of the old men" [syn: heed, listen] 5: be on one's guard; be cautious or wary about; be alert to; "Beware of telephone salesmen" [syn: beware] 6: keep in mind [syn: bear in mind] [ant: forget]
Source: WordNet ® 2.0, © 2003 Princeton University
- the ability to comprehend; to understand and profit from experience
wordnet.princeton.edu/perl/webwn
- Intelligence is a general mental capability that involves the ability to reason, plan, solve problems, think abstractly, comprehend ideas and language, and learn. In psychology, the study of intelligence is related to the study of personality but is not the same as creativity, personality, character, or wisdom.
en.wikipedia.org/wiki/Intelligence_(trait)
- Intelligence is a scientific journal dealing with intelligence and psychometrics.
en.wikipedia.org/wiki/Intelligence_(journal)
- Intelligence is the system's level of performance in reaching its objectives.
www.intelligent-systems.com.ar/intsyst/glossary.htm
- many competing definitions exist for one of the most controversial concepts in psychology. The most influential in the assessment of intelligence in workplace settings is ‘the innate ability to perceive relationships and identify co-relationships’. The assumption is that much of the variation in intelligence can be explained by one general ability factor (G).
www.oup.com/uk/booksites/content/0199253978/student/glossary/glossary.htm
- Intelligence is a generic term for various cognitive abilities. It is classified into different components, depending on the intelligence theory (eg in his work "The Berlin Model of Intelligence", AO Jäger lists: cognitive speed, memory, creativity, and reasoning to process verbal, numerical and figural material). ...
www.personalpsychologie.com/glossary.html
- Ability to follow a program and carry out a routine in an expedient and effective manner. Compare Knowledge.
www.cosmicledger.com/glossary/i
- is effectively perceiving, interpreting and responding to the environment. It is also taken to mean the ability of an organization to survive and meet desired goals and objectives.
www.mountainquestinstitute.com/definitions.htm
- The ability of an individual to understand and cope with the environment; generally assessed with intelligence or "10" tests that are measures of aptitude.
www.upei.ca/~xliu/measurement/glossary.htm
- The capacity to create constructively for the purpose of evolutionary gain. The ability to recognize that which is useful and that which is not, in the creation of internal and external change. Degree of sophistication in the manipulation of fact and materials on a progressive basis.
www.eoni.com/~visionquest/library/glossary.html
- Intelligence concerning foreign developments in basic and applied scientific and technical research and development including engineering and production techniques, new technology, and weapon systems and their capabilities and characteristics; it also includes intelligence that requires scientific or technical expertise on the part of the analyst in areas such as medicine, physical, health studies, and behavioral analyses.
www.intelligence.gov/0-glossary.shtml
- As ability: The ability to be able to correctly see similarities and differences and recognize things that are identical. Also the ability to figure out the correct relative importance of something.
www.geocities.com/clearbirds/study/glosstudy.htm
Future Developments for this Article
- Historical perspectives on how intelligence has been studied and defined,
- Philosophical understandings of intelligence from different schools of thought,
- Psychological and sociological perspectives on intelligence,
- Engineering perspectives on intelligence,
- Computer science perspectives, especially regarding “computational intelligence,”
- Biological perspectives on intelligence, especially “adaptive intelligence,”
- Cooperative dimensions of intelligence,
- Dynamic and synergetic results of the autonomous and cooperative nature of intelligence.
See also...
- Defining Design
- Intelligent Design Timeline
- The Essential Intelligent Design Bibliography
- Intelligent Design is not
- Logical propositions of ID
References and notes
- ↑ Dembski, WA (2001) No Free Lunch, ISBN 0742512975, p. 285.
eResources
BEHAVIOR, PURPOSE AND TELEOLOGY
"This essay has two goals. The first is to define the behavioristic study of natural events and to classify behavior. The second is to stress the importance of the concept of purpose. ... the singling out of the class of predictive behavior, a class particularly interesting since it suggests the possibility of systematizing increasingly more complex tests of the behavior of organisms. It emphasizes the concepts of purpose and of teleology, concepts which, although rather discredited at present, are shown to be important. Finally, it reveals that a uniform behavioristic analysis is applicable to both machines and living organisms, regardless of the complexity of the behavior." The authors are the physiologist Arturo Rosenblueth, theoretical and applied mathematician Norbert Wiener, and the computer scientist Julian Bigelow. Combined, their work has had tremendous impact on a whole set of diverse disciplines.
Can We Define Levels Of Artificial Intelligence?
The paper argues for a graded approach to the study of artificial intelligence. In contrast to the Turing test approach, such an approach permits the measurement of incremental progress in AI research. Results on the conceptual abilities of pigeons are summarized. These abilities far exceed the generalization abilities of current AI programs. It is argued that matching the conceptual abilities of animals would require new approaches to AI. Defining graded levels of intelligence would permit the identification of resources needed for implementation.
Homeostasis: a plea for a unified approach
"Carpenter, R. H. S. Homeostasis: a plea for a unified approach. Adv Physiol Educ 28: S180–S187, 2004; doi:10.1152/advan.00012.2004.—Accompanying the progressive erosion of a coherent sense of physiology as an intellectual discipline, there has been a tendency to lose sight of the homeostatic principles that underpin physiological science, and to teach them in an oversimplified form. When (as is increasingly the case) these principles are rediscovered, they are often treated as something both novel and distinct from homeostasis, fragmenting what is best understood and taught as a unified whole. This article urges a more unitary approach to homeostasis, and attempts to show how such an approach can be presented."
EVERY GOOD REGULATOR OF A SYSTEM MUST BE A MODEL OF THAT SYSTEM
by Roger C. Conant and W. Ross Ashby, "The design of a complex regulator often includes the making of a model of the system to be regulated. The making of such a model has hitherto been regarded as optional, as merely one of many possible ways. m this paper a theorem is presented which shows, under very broad conditions, that any regulator that is maximally both successful and simple must be isomorphic with the system being regulated. (The exact assumptions are given.) Making a model is thus necessary. The theorem has the interesting corollary that the living brain, so far as it is to be successful and efficient as a regulator for survival, must proceed, in learning, by the formation of a model (or models) of its environment."
Molecular Systems Biology and Control
"This paper, prepared for a tutorial at the 2005 IEEE Conference on Decision and Control, presents an introduction to molecular systems biology and some associated problems in control theory. It provides an introduction to basic biological concepts, describes several questions in dynamics and control that arise in the field, and argues that new theoretical problems arise naturally in this context. A final section focuses on the combined use of graph-theoretic, qualitative knowledge about monotone building-blocks and steadystate step responses for components."
An Introduction to Cybernetics
, by W. Ross Ashby, Chapman & Hall, London, 1956. Internet (1999): "Many workers in the biological sciences—physiologists, psychologists, sociologists—are interested in cybernetics and would like to apply its methods and techniques to their own speciality. Many have, however, been prevented from taking up the subject by an impression that its use must be preceded by a long study of electronics and advanced pure mathematics; for they have formed the impression that cybernetics and these subjects are inseparable. The author is convinced, however, that this impression is false. The basic ideas of cybernetics can be treated without reference to electronics, and they are fundamentally simple; so although advanced techniques may be necessary for advanced applications, a great deal can be done, especially in the biological sciences, by the use of quite simple techniques, provided they are used with a clear and deep understanding of the principles involved. It is the author’s belief that if the subject is founded in the common-place and well understood, and is then built up carefully, step by step, there is no reason why the worker with only elementary mathematical knowledge should not achieve a complete understanding of its basic principles."
