Concept Combination and the Origins of Complex Cognition

Abstract

At the core of our uniquely human cognitive abilities is the capacity to see things from different perspectives, or to place them in a new context. We propose that this was made possible by two cognitive transitions. First, the large brain of Homo erectus facilitated the onset of recursive recall: the ability to string thoughts together into a stream of potentially abstract or imaginative thought. This hypothesis is supported by a set of computational models where an artificial society of agents evolved to generate more diverse and valuable cultural outputs under conditions of recursive recall. We propose that the capacity to see things in context arose much later, following the appearance of anatomically modern humans. This second transition was brought on by the onset of contextual focus: the capacity to shift between a minimally contextual analytic mode of thought, and a highly contextual associative mode of thought, conducive to combining concepts in new ways and ‗breaking out of a rut'. When contextual focus is implemented in an art-generating computer program, the resulting artworks are seen as more creative and appealing. We summarize how both transitions can be modeled using a theory of concepts which highlights the manner in which different contexts can lead to modern humans attributing very different meanings to the interpretation of one concept.What is the essence of our human-ness? We propose that what is at the core of our uniquely human cognitive abilities is the capacity to place things in context, or see things from different perspectives. This enables us to be not just creative, but to put our own spin on the inventions of others, modifying them to suit our own needs and tastes, in turn leading to new innovations that build cumulatively on previous

A Contextualised General Systems Theory

“…Indeed, this process has begun already; quantum inspired models have already been used to model a wide range of non-physical systems [52,53], including: decision making [54][55][56][57][58], attitude change [59], language and memory [60][61][62][63], biology [15,[64][65][66], creativity and cultural evolution [67,68], vision [69], economics [70,71] and information retrieval [72][73][74], to name just a few examples.…”

Visual divergence in humans and computers

“…An analysis of 22 tasks used in studies of computational creativity is summarised here (Cohen 1999;Colton 2008;Cook et al 2013;French and Hofstadter 1991;Gabora and Kitto 2013;Gero and Sosa 2008;Hemberg et al 2007;Hsiao and Chen 1997;Jadhav et al 2012;Lewis and Parent 2000;Machado and Pereira 2012;McGraw and Hofstadter 1993;McGreggor et al 2010;Norton et al 2013;Orsborn et al 2006;Pereira and Cardoso 2006;Pérez et al 2007;Ross et al 2006 ;Saunders and Gero 2004;Schnier and Gero 1998;Sosa 2005). Since we are interested in developing design tasks applicable in studies of humans and computational systems, comparing the ways in which these fields define the experimental settings to study creativity reveals important features to consider.…”

“…A number of problem statements used in computational creativity appear to be defined mainly to demonstrate the feasibility or to benchmark the performance of a research approach (French and Hofstadter 1991, Saunders and Gero 2004, Sosa 2005. However, other cases more clearly articulate problem-solving goals to generate novel solutions in a domain (Cohen 1999, Colton 2008, Gabora and Kitto 2013, Jadhav et al 2012.…”

“…High variance is observed in the themes covered in computational creativity, including: font design (McGraw and Hofstadter 1993); architectural designs (Pereira and Cardoso 2006); fine art (Cohen 1999, Gabora andKitto 2013); product design (Hsiao andChen 1997, Orsborn et al 2006); videogame dynamics (Cook et al 2013); narratives (Perez et al 2007); and choreographic movements (Jadhav et al 2012). A wide range of modelling techniques is seen across these models, and ad-hoc assessment practices make it difficult to compare measures of creativeness across the field.…”

Toward a Quantum Theory of Humor

“…The last two decades have witnessed an explosion of applications of quantum models to psychological phenomena that feature ambiguity and/or contextuality [2][3][4]. Many psychological phenomena have been studied using quantum models, including the combination of words and concepts [5][6][7][8][9][10], similarity and memory [11,12], information retrieval [13,14], decision making and probability judgment errors [15][16][17][18][19], vision [20,21], sensation-perception [22], social science [23,24], cultural evolution [25,26], and creativity [27,28]. These quantum inspired approaches make no assumption that phenomena at the quantum level affect the brain, but rather, draw solely on abstract formal structures that, as it happens, found their first application in quantum mechanics.…”