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{{Short description|Psychological theory
'''Perceptual control theory''' ('''PCT''') is a model of [[behavior]] based on the properties of [[negative feedback]] control loops. A control loop maintains a sensed variable at or near a reference value by means of the effects of its outputs upon that variable, as mediated by physical properties of the environment. In [[Control theory|engineering control theory]], reference values are set by a user outside the system. An example is a thermostat. In a living organism, reference values for controlled perceptual variables are endogenously maintained. Biological [[homeostasis]] and [[reflex]]es are simple, low-level examples. The discovery of mathematical principles of control introduced a way to model a negative feedback loop closed through the environment (circular causation), which spawned perceptual control theory. It differs fundamentally from some models in [[Behavioral psychology|behavioral]] and [[cognitive psychology]] that model [[Stimulus (psychology)|stimuli]] as causes of behavior (linear causation). PCT research is published in [[experimental psychology]], [[neuroscience]], [[ethology]], [[anthropology]], [[linguistics]], [[sociology]], [[robotics]], [[developmental psychology]], [[organizational psychology]] and management, and a number of other fields. PCT has been applied to design and administration of educational systems, and has led to a psychotherapy called the [[method of levels]].
==Principles and differences from other theories==
The perceptual control theory is deeply rooted in [[biological cybernetics]], [[systems biology]] and [[control theory]] and the related concept of feedback loops. Unlike some models in behavioral and cognitive psychology it sets out from the concept of circular causality. It shares, therefore, its theoretical foundation with the concept of [[
The plant control theory focuses on neuro-computational processes of movement generation, once a decision for generating the movement has been taken. PCT spotlights the embeddedness of agents in their environment. Therefore, from the perspective of perceptual control, the central problem of motor control consists in finding a sensory input to the system that matches a desired perception.<ref name="Floegel_2023"/>
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==History==
PCT has roots in the 19th-century physiological insights of [[Claude Bernard]] and in
A key insight of PCT is that the controlled variable is not the output of the system (the behavioral actions), but its input, that is, a sensed and transformed function of some state of the environment that the control system's output can affect. Because these sensed and transformed inputs may appear as consciously perceived aspects of the environment, Powers labelled the controlled variable "perception". The theory came to be known as "Perceptual Control Theory" or PCT rather than "Control Theory Applied to Psychology" because control theorists often assert or assume that it is the system's output that is controlled.<ref name=Astrom>{{cite book | last1 =Astrom | first1 =Karl J. | last2 =Murray | first2 =Richard M. | title =Feedback Systems: An Introduction for Scientists and Engineers | publisher =Princeton University Press | date =2008 | url =http://www.cds.caltech.edu/~murray/books/AM08/pdf/am08-complete_28Sep12.pdf | isbn =978-0-691-13576-2 }}</ref> In PCT it is the internal representation of the state of some variable in the environment—a "perception" in everyday language—that is controlled.<ref>For additional information about the history of PCT, see:
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* [http://www.pctweb.org/BillPowersAudioInterview2.mp3 Interview with William T. Powers on origin and history of PCT (Part Two – 20070728 (57.7M)]</ref> The basic principles of PCT were first published by Powers, Clark, and MacFarland as a "general feedback theory of behavior" in 1960,<ref name=PCM1960>{{cite journal | last1 =Powers | first1 =William T. | last2 =Clark | first2 =R.K. | last3 =McFarland | first3 =R.L. | title =A general feedback theory of human behavior (Part I) | journal =Perceptual and Motor Skills | volume =11 | issue =1 | pages =71–88 | date =1960 | doi = 10.2466/pms.1960.11.1.71| s2cid =145256548 }} and {{cite journal | last1 =Powers | first1 =William T. | last2 =Clark | first2 =R.K. | last3 =McFarland | first3 =R.L. | title =A general feedback theory of human behavior (Part II) | journal =Perceptual and Motor Skills | volume =11 | issue =3 | pages =309–323 | date =1960 | doi = 10.2466/pms.1960.11.3.309| s2cid =220712715 }} [Reprinted in {{citation | last1 =Bertalanffy | first1 =Ludwig von | last2 =Rapoport | first2 =Anatol | title =General Systems: Yearbook of the Society for General Systems Research | place =Ann Arbor, Michigan | publisher =Society for General Systems Research | volume =5 | year =1960 }}, pages 63-73, 75-83. Partial reprint in {{cite book | last =Smith | first =A. G. | title =Communication and Culture | publisher =Holt, Rinehart, and Winston | date =1966 | ___location =New York | url =https://archive.org/details/communicationcul00smit| url-access =registration }}]</ref> with credits to cybernetic authors [[Norbert Wiener|Wiener]] and [[William Ross Ashby|Ashby]]. It has been systematically developed since then in the research community that has gathered around it.<ref>[http://www.pctresources.com/ Archives of the Control Systems Group (CSG)], also in the [http://discourse.iapct.org/ IAPCT Discourse forum].</ref> Initially, it was overshadowed by the [[cognitive revolution]] (later supplanted by [[cognitive science]]), but has now become better known.<ref name="Marken2009rev" /><ref name=Mansell2011>{{cite journal | last =Mansell | first =Warren | title =Control of perception should be operationalized as a fundamental property of the nervous system | journal =Topics in Cognitive Science | volume =3 | issue =2 | pages =257–261 | date =2011 | doi =10.1111/j.1756-8765.2011.01140.x | pmid =25164294 }}</ref><ref name=Mansell.Carey.revolution>{{cite journal | last1 =Mansell | first1 =Warren | last2 =Carey | first2 =Timothy A. | title =A perceptual control revolution? | journal =The Psychologist | publisher =The British Psychological Society | date =28 November 2015 | url =https://thepsychologist.bps.org.uk/volume-28/november-2015/perceptual-control-revolution | access-date =17 July 2016 }}</ref><ref>{{cite book |date=2020 |editor-last=Mansell |editor-first=Warren |title=The Interdisciplinary Handbook of Perceptual Control Theory: Living Control Systems IV |___location=Cambridge |publisher=Academic Press |doi= |isbn=978-0128189481 }}</ref>
Powers and other researchers in the field point to problems of purpose, causation, and teleology at the foundations of psychology which control theory resolves.<ref>{{cite journal |last1=Powers |first1=William T. |date=1978 |title=Quantitative analysis of purposive systems: Some spadework at the foundations of scientific psychology |journal=Psychological Review |volume=85 |issue=5 |pages=417–435 |doi=10.1037/0033-295X.85.5.417 }}</ref> From [[Aristotle]] through [[William James]] and [[John Dewey]] it has been recognized that behavior is purposeful and not merely reactive, but how to account for this has been problematic because the only evidence for intentions was subjective. As Powers pointed out, behaviorists following [[Wilhelm Wundt|Wundt]], [[Edward Thorndike|Thorndike]], [[John B. Watson|Watson]], and others rejected introspective reports as data for an objective science of psychology. Only observable behavior could be admitted as data.<ref>"The behaviorist asks: Why don't we make what we can observe the real field of psychology? Let us limit ourselves to things that can be observed, and formulate laws concerning only those things. Now what can we observe? We can observe behavior—what the organism does or says." Watson, J.B. (1924). ''Behaviorism''. New York: People's Institute Publishing Company.</ref> Such behaviorists modeled environmental events (stimuli) as causing behavioral actions (responses). This causal assumption persists in some models in [[cognitive psychology]] that interpose [[cognitive maps]] and other postulated [[Information processing (psychology)|information processing]] between stimulus and response but otherwise retain the assumption of linear causation from environment to behavior, which Richard Marken called an "open-loop causal model of behavioral organization" in contrast to PCT's closed-loop model.<ref name=Marken2009rev>{{cite journal | last =Marken | first =Richard S. | title =You say you had a revolution: Methodological foundations of closed-loop psychology | journal =Review of General Psychology | volume =13 | issue =2 | pages =137–145 | date =June 2009 | doi =10.1037/a0015106 | s2cid =145458091 |url=https://www.researchgate.net/publication/232499797}}</ref>
Another, more specific reason that Powers observed for psychologists' rejecting notions of purpose or intention was that they could not see how a goal (a state that did not yet exist) could cause the behavior that led to it. PCT resolves these philosophical arguments about [[teleology]] because it provides a model of the functioning of organisms in which purpose has objective status without recourse to [[introspection]], and in which causation is circular around [[feedback loops]].<ref name=Runkel-PLT>{{cite book | last =Runkel | first =Philip J. | title =People as living things | publisher =Living Control Systems Publishing | date =2003 | ___location =Hayward, CA | isbn =978-0-9740155-0-7 }}</ref>
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To illustrate the mathematical calculations employed in a PCT simulation, consider a pursuit tracking task in which the participant keeps a mouse cursor aligned with a moving target on a computer monitor.
The model assumes that a perceptual signal within the participant represents the magnitude of the input quantity ''q<sub>i</sub>''. (This has been demonstrated to be a rate of firing in a neuron, at least at the lowest levels.)<ref name=Powers73>{{cite book| title=Behavior: The Control of Perception| year=1973| first=William T.| last=Powers| isbn=978-0-7045-0092-1| title-link=Behavior: The Control of Perception| publisher=Wildwood House}}</ref><ref name=Yin.BG2014>{{cite journal | last =Yin | first =Henry H. | title =How Basal Ganglia Outputs Generate Behavior | journal =Advances in Neuroscience | volume =2014 | issue =768313 | pages =1–28 | date =18 November 2014 | doi =10.1155/2014/768313 | doi-access =free }}</ref> In the tracking task, the input quantity is the vertical distance between the target position ''T'' and the cursor position ''C'', and the random variation of the target position acts as the disturbance ''d'' of that input quantity. This suggests that the perceptual signal ''p'' quantitatively represents the cursor position ''C'' minus the target position T, as expressed in the equation ''p''=''C''–''T''.
Between the perception of target and cursor and the construction of the signal representing the distance between them there is a delay of ''τ'' milliseconds, so that the working perceptual signal at time ''t'' represents the target-to-cursor distance at a prior time, ''t'' – ''τ''. Consequently, the equation used in the model is
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This "reorganization system" is proposed to be part of the inherited structure of the organism. It changes the underlying parameters and connectivity of the control hierarchy in a random-walk manner. There is a basic continuous rate of change in intrinsic variables which proceeds at a speed set by the total error (and stops at zero error), punctuated by random changes in direction in a hyperspace with as many dimensions as there are critical variables. This is a more or less direct adaptation of Ashby's "[[homeostat]]", first adopted into PCT in the 1960 paper<ref name=PCM1960 /> and then changed to use E. coli's method of navigating up gradients of nutrients, as described by Koshland (1980).<ref>Koshland, Daniel. (1980). ''Bacterial chemotaxis as a model behavioral system''. New York: Raven Press.</ref>
Reorganization may occur at any level when loss of control at that level causes intrinsic (essential) variables to deviate from genetically determined set points. This is the basic mechanism that is involved in trial-and-error learning, which leads to the acquisition of more systematic kinds of learning processes.<ref name="Cziko 1995">{{cite book| title=Without Miracles| year=1995| first=Gary| last=Cziko| isbn=978-0-262-03232-2| title-link=Without Miracles| publisher=MIT Press}}.</ref>
==Psychotherapy: the method of levels (MOL)==
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Hierarchies of perceptual control have been simulated in computer models and have been shown to provide a close match to behavioral data. For example, Marken<ref name=Marken86>{{cite journal | last =Marken | first =Richard S. | title =Perceptual organization of behavior: A hierarchical control model of coordinated action. | journal =Journal of Experimental Psychology: Human Perception and Performance | volume =12 | issue =3 | pages =267–276 | date =Aug 1986 | doi =10.1037/0096-1523.12.3.267 | pmid =2943855 }}</ref> conducted an experiment comparing the behavior of a perceptual control hierarchy computer model with that of six healthy volunteers in three experiments. The participants were required to keep the distance between a left line and a centre line equal to that of the centre line and a right line. They were also instructed to keep both distances equal to 2 cm. They had 2 paddles in their hands, one controlling the left line and one controlling the middle line. To do this, they had to resist random disturbances applied to the positions of the lines. As the participants achieved control, they managed to nullify the expected effect of the disturbances by moving their paddles. The correlation between the behavior of subjects and the model in all the experiments approached 0.99. It is proposed that the organization of models of hierarchical control systems such as this informs us about the organization of the human subjects whose behavior it so closely reproduces.
==Robotics==
PCT has significant implications for Robotics and Artificial Intelligence. W.T. Powers introduced the application of PCT to robotics in 1978, early in the availability of home computers.<ref>{{cite magazine |last=Powers |first=William T. |date=1978 |title=The Nature of Robots: Part I: Defining Behavior |url=http://www.livingcontrolsystems.com/appendixes/byte_june_1979.pdf |url-status=dead |magazine=Byte: The Small Systems Journal |___location=Peterborough, NH |publisher=McGraw-Hill |issue=4 |pages=132–144 |archive-url=https://web.archive.org/web/20070604100935/http://www.livingcontrolsystems.com/appendixes/byte_june_1979.pdf |archive-date=June 4, 2007 |access-date=}}</ref>
<ref>{{cite magazine |last=Powers |first=William T. |date=1978 |title=The Nature of Robots: Part II: Simulated Control Systems |url=http://www.livingcontrolsystems.com/appendixes/byte_july_1979.pdf |url-status=dead |magazine=Byte: The Small Systems Journal |___location=Peterborough, NH |publisher=McGraw-Hill |issue=4 |pages=134–152 |archive-url=https://web.archive.org/web/20070604100935/http://www.livingcontrolsystems.com/appendixes/byte_july_1979.pdf |archive-date=June 4, 2007 |access-date=}}</ref>
<ref>{{cite magazine |last=Powers |first=William T. |date=1978 |title=The Nature of Robots: Part III: A closer look at human behavior |url=http://www.livingcontrolsystems.com/appendixes/byte_aug_1979.pdf |url-status=dead |magazine=Byte: The Small Systems Journal |___location=Peterborough, NH |publisher=McGraw-Hill |issue=4 |pages=94–116 |archive-url=https://web.archive.org/web/20070604100935/http://www.livingcontrolsystems.com/appendixes/byte_aug_1979.pdf" |archive-date=June 4, 2007 |access-date=}}</ref>
<ref>{{cite magazine |last=Powers |first=William T. |date=1978 |title=The Nature of Robots: Part IV: Looking for controlled variables |url=http://www.livingcontrolsystems.com/appendixes/byte_sep_1979.pdf |url-status=dead |magazine=Byte: The Small Systems Journal |___location=Peterborough, NH |publisher=McGraw-Hill |issue=4 |pages=96–112 |archive-url=https://web.archive.org/web/20070604100935/http://www.livingcontrolsystems.com/appendixes/byte_sep_1979.pdf |archive-date=June 4, 2007 |access-date=}}</ref> The comparatively simple architecture,<ref name=Young2017>{{cite journal | last =Young| first =Rupert | author-link = | title =A General Architecture for Robotics Systems: A Perception-Based Approach to Artificial Life. | journal =Artificial Life| volume =23 | issue =2 | pages =236–286 | date =Jun 2017 | access-date = | doi =10.1162/ARTL_a_00229 | pmid =28513206 }}</ref> a hierarchy of perceptual controllers, has no need for complex models of the external world, inverse kinematics, or computation from input-output mappings. Traditional approaches to robotics generally depend upon the computation of actions in a constrained environment. Robots designed this way are inflexible and clumsy, unable to cope with the dynamic nature of the real world. PCT robots inherently resist and counter the chaotic, unpredictable disturbances to their controlled inputs which occur in an unconstrained environment. The PCT robotics architecture has recently been applied to a number of real-world robotic systems including robotic rovers,<ref>
{{cite AV media
| people =Young, Rupert
| date =Feb 27, 2015
| title =HPCT Autonomous Rover (short version)
| medium =YouTube
| url =https://www.youtube.com/watch?v=JM9tSYpeLZA
| publisher =Perceptual Robots
}}
</ref> balancing robot<ref>
{{cite AV media
| people =Young, Rupert
| date =Mar 9, 2016
| title =Robot on a train
| medium =YouTube
| url =https://www.youtube.com/watch?v=FCPDEeosCPU
| publisher =Perceptual Robots
}}
</ref> and robot arms.<ref>{{cite AV media
| people =Young, Rupert
| date =Jul 1, 2016
| title =Dynamic Visual Robot Arm Control
| medium =YouTube
| url =https://www.youtube.com/watch?v=jmwH0AZtGG4
| publisher =Perceptual Robots
}}
</ref> Some commercially available robots which demonstrate good control in a naturalistic environment use a control-theoretic architecture which requires much more intensive computation. For example, Boston Dynamics has said<ref>{{Cite web |url=https://bostondynamics.com/blog/starting-on-the-right-foot-with-reinforcement-learning/#:~:text=The%20legged%20robots%20we've,to%20take%20in%20the%20moment |title=Starting on the Right Foot with Reinforcement Learning |author=<!--Not stated--> |date=March 19, 2024 |website=bostondynamics.com |publisher=Boston Dynamics |access-date=November 1, 2024 |quote=The legged robots we’ve built at Boston Dynamics have historically leveraged Model Predictive Control (MPC), a control strategy that predicts and optimizes the future states of the robot in order to decide what action to take in the moment.}}</ref> that its robots use historically leveraged [[Model_predictive_control |model predictive control]].
==Current situation and prospects==
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While many computer demonstrations of principles have been developed, the proposed higher levels are difficult to model because too little is known about how the brain works at these levels. Isolated higher-level control processes can be investigated, but models of an extensive hierarchy of control are still only conceptual, or at best rudimentary.
Perceptual control theory has not been widely accepted in mainstream psychology, but has been effectively used in a considerable range of domains<ref>{{Cite web | url=https://thepsychologist.bps.org.uk/volume-28/november-2015/perceptual-control-revolution |title = A perceptual control revolution? |website=The Psychologist}}</ref><ref name="IJHCS">The June 1999 Issue of ''The International Journal of Human-Computer Studies'' contained papers ranging from tracking through cockpit layout to self-image and crowd dynamics.</ref> in human factors,<ref name="CBUT">PCT lies at the foundation of [[Component-Based Usability Testing]].</ref> clinical psychology, and psychotherapy (the "[[Method of Levels]]"), it is the basis for a considerable body of research in sociology,<ref>For example: McClelland, Kent A. and Thomas J. Fararo, eds. 2006, ''Purpose, Meaning and Action: Control Systems Theories in Sociology'', New York: Palgrave Macmillan. (McClelland is co-author of Chapter 1, "Control Systems Thinking in Sociological Theory," and author of Chapter 2, "Understanding Collective Control Processes."). McClelland, Kent, 2004, "Collective Control of Perception: Constructing Order from Conflict", ''International Journal of Human-Computer Studies'' 60:65-99. McPhail, Clark. 1991, ''The myth of the madding crowd'' New York: Aldine de Gruyter.</ref> and it has formed the conceptual foundation for the reference model used by a succession of [[NATO]] research study groups.<ref name="IST">volume-28november-2015 Reports of these groups are available from the [[NATO Research and Technology Administration]] publications page: {{cite web
Recent approaches use principles of perceptual control theory to provide new algorithmic foundations for [[artificial intelligence]] and [[machine learning]].<ref>{{cite journal |last1=Monaco |first1=Joseph D. |last2=Hwang |first2=Grace M. |title=Neurodynamical Computing at the Information Boundaries of Intelligent Systems |journal=Cognitive Computation |date=27 December 2022 |volume=16 |issue=5 |pages=1–13 |doi=10.1007/s12559-022-10081-9|s2cid=255222711 |doi-access=free |pmid=39129840 |pmc=11306504 }}</ref>
==Selected bibliography==
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* Marken, Richard S. (1992) ''Mind readings: Experimental studies of purpose''. Benchmark Publications: New Canaan, CT.
* Marken, Richard S. (2002) ''More mind readings: Methods and models in the study of purpose''. Chapel Hill, NC: New View. {{ISBN|0-944337-43-0}}
* Pfau, Richard H. (2017). ''Your Behavior: Understanding and Changing the Things You Do.'' St. Paul, MN: Paragon House. {{ISBN|9781557789273}}
* Plooij, F. X. (1984). ''The behavioral development of free-living chimpanzee babies and infants''. Norwood, N.J.: Ablex.
* Plooij, F. X. (2003). "The trilogy of mind". In M. Heimann (Ed.), ''Regression periods in human infancy'' (pp. 185–205). Mahwah, NJ: Erlbaum.
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[[Category:Cybernetics]]
[[Category:Formal sciences]]
[[Category:Robotics engineering]]
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