A massively parallel architecture for a self-organizing neural pattern recognition machine
Computer Vision, Graphics, and Image Processing
Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought
Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Biological Cybernetics
Cognitive Social Simulation Incorporating Cognitive Architectures
IEEE Intelligent Systems
Effects of relevant and irrelevant primes on idea generation: a computational model
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Intuition, Insight, Imagination and Creativity
IEEE Computational Intelligence Magazine
Learning Complex Population-Coded Sequences
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Effects of relevant and irrelevant primes on idea generation: a computational model
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
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In this paper, we present a model for the generation of ideas within a creative thinking/brainstorming context. In the model, ideas emerge as conceptual combinations from the interaction of complex dynamics at several semantic levels: Features, concepts, categories, and previously generated ideas. This dynamics is shaped by external information on task context, constraints and goals, and is modulated by evaluative feedback from an internal critic working through reinforcement. While the model is abstract, it attempts to capture the interplay between semantic representations in the temporal, frontal and parietal cortices, working memory in the prefrontal cortex, attentional selection by the basal ganglia, and modulation from the dopaminergic reward system. We show that a context-specific itinerant search for novel but meaningful conceptual combinations (ideas) emerges naturally from the dynamics of this system. We also briefly describe a computational model for ideation in groups using a multi-agent formalism. The initial focus of this model is on studying the potential benefits of cognitive diversity in agent groups, e.g., the presence of convergent and divergent thinkers, or agents with different semantic organizations.