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Informing Artificial Intelligence Generative Techniques using Cognitive Theories of Human Creativity
The common view that our creativity is what makes us uniquely human suggests that incorporating research on human creativity into generative deep learning techniques might be a fruitful avenue for making their outputs more compelling and human-like.
Deep Convolutional Networks as Models of Generalization and Blending Within Visual Creativity
We examine two recent artificial intelligence (AI) based deep learning algorithms for visual blending in convolutional neural networks (Mordvintsev et al. 2015, Gatys et al. 2015).
Generalizing Prototype Theory: A Formal Quantum Framework
We show how a formal quantum approach to concepts and their combinations can provide a powerful extension of prototype theory.
The Silver Lining Around Fearful Living
A first study showed that both killifish from a lake with predators and from a lake without predators explore a new environment to the same degree and plotting number of new spaces covered over time generates a hump-shaped curve.
Toward a Formal Model of the Shifting Relationship between Concepts and Contexts during Associative Thought
The quantum inspired State Context Property (SCOP) theory of concepts is unique amongst theories of concepts in offering a means of incorporating that for each concept in each different context there are an unlimited number of exemplars, or states, of varying degrees of typicality.
Contextualizing concepts using a mathematical generalization of the quantum formalism
We outline the rationale and preliminary results of using the state context property (SCOP) formalism, originally developed as a generalization of quantum mechanics, to describe the contextual manner in which concepts are evoked, used and combined to generate meaning.
A Computational Model of Two Cognitive Transitions Underlying Cultural Evolution
We tested the computational feasibility of the proposal that open-ended cultural evolution was made possible by two cognitive transitions: (1) onset of the capacity to chain thoughts together, followed by (2) onset of contextual focus (CF): the capacity to shift between a divergent mode of thought conducive to 'breaking out of a rut' and a convergent mode of thought conducive to minor modifications.
An Agent-based Model of the Cognitive Mechanisms Underlying the Origins of Creative Cultural Evolution
Using a computational model of cultural evolution in which neural network based agents evolve ideas for actions through invention and imitation, we tested the hypothesis that this is due to the capacity for recursive recall.
EVOC: A Computer Model of the Evolution of Culture
EVOC replicates using a different fitness function the results obtained with an earlier model (MAV), including (1) an increase in mean fitness of actions, and (2) an increase and then decrease in the diversity of actions.
Meme and Variations: A Computer Model of Cultural Evolution
Holland's (1975) genetic algorithm is a minimal computer model of natural selection that made it possible to investigate the effect of manipulating specific parameters on the evolutionary process.
Concept Combination and the Origins of Complex Cognition
We propose that the capacity to see things in context arose much later, following the appearance of anatomically modern humans.
A Model of the Mechanisms Underlying Exploratory Behaviour
A model of the mechanisms underlying exploratory behaviour, based on empirical research and refined using a computer simulation, is presented.
Should I Stay or Should I Go: Coordinating Biological Needs with Continuously-updated Assessments of the Environment
Wanderer responds to these events in a way that is adaptive in the short turn, and reassesses the probabilities of these events so that it can modify its long term behaviour appropriately.
Modeling the Role of Context Dependency in the Recognition and Manifestation of Entrepreneurial Opportunity
The role of contextual-fit in the generation and development of ideas is modeled as the collapse of their superposition state into one of the potential states that composes this superposition.
How Did Humans Become So Creative? A Computational Approach
Using a computational model of cultural evolution in which neural network based agents evolve ideas for actions through invention and imitation, we tested the hypothesis that human creativity began with onset of the capacity for recursive recall.
How Insight Emerges in a Distributed, Content-addressable Memory
The ability to pull out of memory something new and appropriate that was never stored there in the first place is what we refer to as the magic of creativity.
Recognizability of Individual Creative Style Within and Across Domains: Preliminary Studies
Moreover, creative writing students guessed significantly above chance which of their peers produced particular works of art, supporting the hypothesis that creative style is recognizable not just within but across domains.
An Agent-based Simulation of the Effectiveness of Creative Leadership
This paper investigates the effectiveness of creative versus uncreative leadership using EVOC, an agent-based model of cultural evolution.
Incorporating characteristics of human creativity into an evolutionary art algorithm
A perceived limitation of evolutionary art and design algorithms is that they rely on human intervention; the artist selects the most aesthetically pleasing variants of one generation to produce the next.
How Creative Should Creators Be To Optimize the Evolution of Ideas? A Computational Model
For all levels or creativity, the diversity of ideas in a population is positively correlated with the ratio of creative agents.
Modeling Cultural Dynamics
The model is based on a theory of culture according to which what evolves through culture is not memes or artifacts, but the internal models of the world that give rise to them, and they evolve not through a Darwinian process of competitive exclusion but a Lamarckian process involving exchange of innovation protocols.
