Causal Cognitive Architecture 1: Integration of Connectionist Elements into a Navigation-Based Framework

EasyChair Preprint no. 4348

Abstract

The brain-inspired Causal Cognitive Architecture 1 (CCA1) tightly integrates the sensory processing capabilities found in neural networks with many of the causal abilities found in human cognition. Sensory input vectors are processed by robust association circuitry and then propagated to a navigational temporary map. Instinctive and learned objects and procedures are applied to the same temporary map, with a resultant navigational signal obtained. Navigation can similarly be for the physical world as well as for a landscape of higher cognitive concepts. Causality emerges from the architecture, with good explainability for causal decisions. A simulation of the CCA1 controlling a search and rescue robot is presented with the goal of finding and rescuing a lost hiker within a grid world.

Keyphrases: Artificial General Intelligence, causality, cognitive architecture, Explainability, spatial navigation

@Booklet{EasyChair:4348,
  author = {Howard Schneider},
  title = {Causal Cognitive Architecture 1: Integration of Connectionist Elements into a Navigation-Based Framework},
  howpublished = {EasyChair Preprint no. 4348},

  year = {EasyChair, 2020}}