Complexity equals change

Aksentijevic, Aleksandar; Gibson, Keith

doi:10.1016/j.cogsys.2011.01.002

Cited by 24 publications

(30 citation statements)

References 34 publications

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“…Psychologists adopted this view and argued the minimal length corresponds to the minimal work for the brain, and therefore, to energy economy [1]. From the physiological viewpoint, the diversity of information corresponds to the range of stimulation input a human can perceive.…”

Section: Amount Of Informationmentioning

confidence: 99%

Visual impressions of mobile app interfaces

Miniukovich

Angeli

2014

Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational

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First impressions are formed very fast but they last. Consecutive approach-avoidance behavior is formed almost instantly and persists over time. The effect of the first impression of graphical user interfaces (GUIs) of desktop webpages on subsequent evaluation is well documented in the literature. Less research has focused on mobile interfaces. To cover this gap, this paper reports two studies. The first study confirmed the persistence of first impressions on mobile interfaces evaluation, although it suggested that exposure time may be longer. The second study extends previous work on automatic evaluation from desktop to mobile interfaces. The linking theme between the studies is that of visual complexity, which is a more objective, yet powerful, predictor of aesthetic evaluation. Using six automatic metrics (color depth, dominant colors, visual clutter, symmetry, figure-ground contrast and edge congestion), in study 2 we explained 40 of variation in subjective complexity scores and 36 of variation in aesthetics scores

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Section: Amount Of Informationmentioning

confidence: 99%

Visual impressions of mobile app interfaces

Miniukovich

Angeli

2014

Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational

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“…However, faced with that series of digits, humans are unlikely to see any regularity: algorithmic complexity identifies as non-random some series that will look random to most humans. When it comes to assessing perceived complexity, the tool developed by Aksentijevic and Gibson (2012), named "change complexity", is an interesting alternative. It is based on the idea that humans' perception of complexity depends largely on the changes between one symbol and the next.…”

Section: Main Functionsmentioning

confidence: 99%

Algorithmic complexity for psychology: a user-friendly implementation of the coding theorem method

et al. 2015

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Kolmogorov-Chaitin complexity has long been believed to be impossible to approximate when it comes to short sequences (e.g. of length 5-50). However, with the newly developed coding theorem method the complexity of strings of length 2-11 can now be numerically estimated. We present the theoretical basis of algorithmic complexity for short strings (ACSS) and describe an R-package providing functions based on ACSS that will cover psychologists' needs and improve upon previous methods in three ways: (1) ACSS is now available not only for binary strings, but for strings based on up to 9 different symbols, (2) ACSS no longer requires time-consuming computing, and (3) a new approach based on ACSS gives access to an estimation of the complexity of strings of any length. Finally, three illustrative examples show how these tools can be applied to psychology. Keywords Algorithmic complexity · Randomness · Subjective probability · Coding theorem method Randomness and complexity are two concepts which are intimately related and are both central to numerous recent developments in various fields, including finance (Taufemback et al., 2011, Brandouy et al., 2012, linguistics (Gruber, 2010;Naranan, 2011), neuropsychology (Machado et al., 2010;Fernández et al., 2011Fernández et al., , 2012, psychiatry (Yang and Tsai, 2012;Takahashi 2013), genetics (Yagil, 2009;Ryabko et al. 2013), sociology (Elzinga, 2010 and the behavioral sciences (Watanabe et al., 2003;Scafetta et al., 2009). In psychology, randomness and complexity have recently attracted interest, following the realization that they could shed light on a diversity of previously undeciphered behaviors and mental processes. It has been found, for instance, that the subjective difficulty of a concept is directly related to its "boolean complexity", defined as the shortest logical description of a concept (Feldman, 2000(Feldman, , 2003(Feldman, , 2006. In the same vein, visual detection of shapes has been shown to be related to contour complexity (Wilder et al., 2011).More generally, perceptual organization itself has been described as based on simplicity or, equivalently, likelihood (Chater, 1996;Chater and Vitányi, 2003), in a model reconciling the complexity approach (perception is organized to minimize complexity) and a probability approach (perception is organized to maximize likelihood), very much in line with our view in this paper. Even the perception of similarity may be viewed through the lens of (conditional) complexity (Hahn et al., 2003).Randomness and complexity also play an important role in modern approaches to selecting the "best" among a set of candidate models (i.e., model selection; e.g., Myung et Behav Res (2016) 48:314-329 315 al., 2006Kellen et al., 2013), as discussed in more detail below in the section called "Relationship to complexity based model selection".Complexity can also shed light on short term memory storage and recall, more specifically, on the process underlying chunking. It is well known that the short term memory span lies b...

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“…Very recently, a more sophisticated approach based on changes has been suggested (Aksentijevic & Gibson, 2012). Given an n -long string s , define the change function of s , c (s ), as the (n-1)-long string f(s) whose ith term is 0 if s(i) =s(i + 1), and 1 if not.…”

Section: Cognitive Complexitymentioning

confidence: 99%

Algorithmic complexity for short binary strings applied to psychology: a primer

et al. 2013

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As human randomness production has come to be more closely studied and used to assess executive functions (especially inhibition), many normative measures for assessing the degree to which a sequence is randomlike have been suggested. However, each of these measures focuses on one feature of randomness, leading researchers to have to use multiple measures. Although algorithmic complexity has been suggested as a means for overcoming this inconvenience, it has never been used, because standard Kolmogorov complexity is inapplicable to short strings (e.g., of length l ≤ 50), due to both computational and theoretical limitations. Here, we describe a novel technique (the coding theorem method) based on the calculation of a universal distribution, which yields an objective and universal measure of algorithmic complexity for short strings that approximates Kolmogorov-Chaitin complexity.

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Complexity equals change

Cited by 24 publications

References 34 publications

Visual impressions of mobile app interfaces

Visual impressions of mobile app interfaces

Algorithmic complexity for psychology: a user-friendly implementation of the coding theorem method

Algorithmic complexity for short binary strings applied to psychology: a primer

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