DeepAI AI Chat
Log In Sign Up

Radically Compositional Cognitive Concepts

11/14/2019
by   Toby B. St Clere Smithe, et al.
University of Oxford
0

Despite ample evidence that our concepts, our cognitive architecture, and mathematics itself are all deeply compositional, few models take advantage of this structure. We therefore propose a radically compositional approach to computational neuroscience, drawing on the methods of applied category theory. We describe how these tools grant us a means to overcome complexity and improve interpretability, and supply a rigorous common language for scientific modelling, analogous to the type theories of computer science. As a case study, we sketch how to translate from compositional narrative concepts to neural circuits and back again.

READ FULL TEXT

page 1

page 2

page 3

page 4

03/01/2022

Compositional Inverses of AGW-PPs

In this paper, we present two methods to obtain the compositional invers...
04/22/2020

Categories of Semantic Concepts

Modelling concept representation is a foundational problem in the study ...
12/13/2004

Vector Symbolic Architectures answer Jackendoff's challenges for cognitive neuroscience

Jackendoff (2002) posed four challenges that linguistic combinatoriality...
09/05/2022

On the Horizon: Interactive and Compositional Deepfakes

Over a five-year period, computing methods for generating high-fidelity,...
01/10/2022

A Statistical Analysis of Compositional Surveys

A common statistical problem is inference from positive-valued multivari...
05/20/2021

Flexible Compositional Learning of Structured Visual Concepts

Humans are highly efficient learners, with the ability to grasp the mean...
07/01/2019

A Compositional Framework for Scientific Model Augmentation

Scientists construct and analyze computational models to understand the ...