Traditionally, theories of complexity used in psychology have been based on geometric, probabilistic, and algorithmic paradigms. While these have been useful in highlighting the importance of complexity for psychology, they have not, in general, addressed the relationship between complexity and processing cost. In this paper, we review some of the classic and current complexity theories in psychology and suggest that psychological complexity and processing cost can be quantified using the notion of hierarchical change. Finally, we discuss the relationship between change, complexity, and the Gestalt principles of perceptual organization.
AksentijevicA.ElliottM. A.BarberP. J. (2001). Dynamics of perceptual grouping: Similarities in the organization of visual and auditory groups. Visual Cognition, 8, 349–358.
2.
AksentijevicA.GibsonK. (in press). Complexity equals change. Cognitive Systems Research.
3.
AlberoniF. (1962). Contribution to the study of subjective probability: I. Journal of General Psychology, 66, 261–264.
AttneaveF. (1954). Some informational aspects of visual perception. Psychological Review, 61, 183–193.
6.
AttneaveF. (1959). Applications of information theory to psychology: A summary of basic concepts, methods, and results. New York, NY: Henry Holt.
7.
BennettC. H. (1987). Demons, engines and the second law. Scientific American, 257, 88–96.
8.
BennettC. H. (1988). Logical depth and physical complexity. In HerkenR. (Ed.), The universal Turing machine, a half-century survey (pp. 227–257). Oxford, UK: Oxford University Press.
9.
ChaitinG. J. (1969). On the length of the programs for computing finite binary sequences: Statistical considerations. Journal of the Association for Computing Machinery, 16, 145–159.
10.
ChaitinG. J. (2001). Exploring randomness. London, UK: Springer.
11.
ChaterN. (1996). Reconciling simplicity and likelihood principles in perceptual organization. Psychological Review, 103, 566–581.
12.
CorcoranD. J. W. (1971). Pattern recognition. London, UK: Penguin Books.
13.
CuttingJ. E. (1998). Information from the world around us. In HochbergJ. (Ed.), Perception and cognition at century’s end: History, philosophy and theory (pp. 69–93). San Diego, CA: Academic Press.
14.
CuttingJ. E.GarvinJ. J. (1987). Fractal curves and complexity. Perception & Psychophysics, 42, 365–370.
15.
DonderiD. C. (2006). Visual complexity: A review. Psychological Bulletin, 132, 73–97.
16.
FalkR.KonoldC. (1997). Making sense of randomness: Implicit encoding as a bias for judgment. Psychological Review, 104, 301–318.
17.
FeldmanJ.HannaJ. F. (1966). The structure of responses to a sequence of binary events. Journal of Mathematical Psychology, 3, 371–387.
18.
FeynmanR. P.LeightonR. B.SandsM. (1977). The Feynman lectures on physics. Reading, MA: Addison-Wesley.
19.
FeynmanR. P. (1999). Six not-so-easy pieces: Einstein’s relativity, symmetry, and space-time. London, UK: Penguin.
20.
FrackowiakR. S. J.FristonK. J.FrithC.DolanR.PriceC. J.ZekiS.. . .PennyW. D. (2003). Human brain function. San Diego, CA: Academic Press.
21.
GalanterE. H.SmithW. A. S. (1958). Some experiments on a simple thought-problem. American Journal of Psychology, 71, 359–366.
22.
GambinoB.MyersJ. L. (1967). Role of event runs in probability learning. Psychological Review, 74, 410–419.
23.
GarnerW. R. (1974). The processing of information and structure. Potomac, MD: Lawrence Erlbaum.
24.
GarnerW. R.ClementD. E. (1963). Goodness of pattern and pattern uncertainty. Journal of Verbal Learning and Verbal Behavior, 2, 446–452.
25.
GarnerW. R.GottwaldR. L. (1967). Some perceptual factors in the learning of sequential patterns of binary events. Journal of Verbal Learning and Verbal Behavior, 6, 582–589.
26.
Gell-MannM. (1995). What is complexity?Complexity, 1, 1–9.
27.
GrassbergerP. (1986). How to measure self-generated complexity. Physica A: Statistical Mechanics and its Applications, 140, 319–325.
28.
HickW. E. (1952). On the rate of gain of information. Quarterly Journal of Experimental Psychology, 4, 11–26.
29.
HochbergJ.McAlisterE. (1953). A quantitative approach to figural “goodness”. Journal of Experimental Psychology, 46, 361–364.
30.
IchikawaS. (1985). Quantitative and structural factors in the judgment of pattern complexity. Perception & Psychophysics, 38, 101–109.
31.
KoffkaK. (1935). Principles of Gestalt psychology. London, UK: Lund Humphries.
32.
KolmogorovA. N. (1965). Three approaches to the quantitative definition of information. Problems in Information Transmission, 1, 1–7.
33.
LeeuwenbergE. L. J. (1969). Quantitative specification of information in sequential patterns. Psychological Review, 76, 216–220.
34.
LeeuwenbergE. L. J.van der HelmP. A. (1991). Accessibility, a criterion for regularity and hierarchy in visual pattern codes. Journal of Mathematical Psychology, 35, 151–213.
MillerG. A. (1953). What is information measurement?American Psychologist, 8, 3–11.
40.
NäätänenR.AlhoK. (1995). Mismatch negativity: A unique measure of sensory processing in audition. International Journal of Neuroscience, 80, 317–337.
41.
OliversC. N. L.ChaterN.WatsonD. G. (2004). Holography does not account for goodness: A critique of van der Helm and Leeuwenberg (1996). Psychological Review, 111, 242–260.
42.
PalmerS. E. (1983). The psychology of perceptual organization: A transformational approach. In BeckJ.HopeB.RosenfeldA. (Eds.), Human and machine vision (pp. 269–339). New York, NY: Academic Press.
43.
PollackI. (1952). The information of elementary auditory displays. Journal of the Acoustical Society of America, 24, 745–749.
44.
RestleF. (1970). Theory of serial pattern learning: Structural trees. Psychological Review, 77, 481–495.
45.
RoyerF. L.GarnerW. R. (1966). Response uncertainty and perceptual difficulty of auditory temporal patterns. Perception & Psychophysics, 1, 41–47.
46.
ShannonC. (1948). A mathematical theory of communication. The Bell Technical Journal, 27, 623–656.
47.
SimonH. A. (1972). Complexity and the representation of patterned sequences of symbols. Psychological Review, 79, 369–382.
48.
SimonH. A.KotovskyK. (1963). Human acquisition of concepts for sequential patterns. Psychological Review, 70, 534–546.
49.
SolomonoffR. J. (1964). A formal theory of inductive inference, part 1 and part 2. Information & Control, 7, 224–254.
50.
TylerC. W.BaselerH. A.KontsevichL. L.LikovaL. T.WadeA. R.WandellB. A. (2005). Predominantly extra-retinotopic cortical response to pattern symmetry. Neuroimage, 24, 306–314.
51.
van der HelmP. A. (2000). Simplicity versus likelihood in visual perception: From surprisals to precisals. Psychological Bulletin, 126, 770–800.
52.
van der HelmP. A. (2004). Transparallel processing by hyperstrings. Proceedings of the National Academy of Sciences, 101, 10862–10867.
53.
van der HelmP. A.LeeuwenbergE. L. J. (1996). Goodness of visual regularities: A nontransformational approach. Psychological Review, 103, 429–456.
54.
VitzP. C.ToddR. C. (1969). A coded element model of the perceptual processing of sequential stimuli. Psychological Review, 76, 433–449.
55.
WeylH. (1952). Symmetry. Princeton, CA: Princeton University Press.
