Causal Event Networks: Cognition, Complexity and Physical Laws

TL;DR

This paper explores a theoretical framework connecting information flow, cognition, and physical laws, proposing measures and postulates to formalize cognitive event networks and their temporal limits.

Contribution

It introduces a novel measure for partitioning cognitive information sets and formalizes cognition as a partially ordered set of events with temporal constraints.

Findings

Analyzes limitations of existing information theory in cognition

Proposes a set of postulates for cognitive event ordering

Defines the concept of a fundamental cognitive chain

Abstract

Information flow framed in a computational and complexity context is relevant to the understanding of cognitive processes and awareness. In this paper, we begin with analyzing an information theory framework developed in recent years under Information and Integration Theory (IIT) based on interactions among partitions of cognitive information sets. We discuss the scope and limitations of these ideas, introducing a related measure for partitioning information sets. We introduce a set of postulates describing cognition as a partially ordered set of events in space and time. We consider the relevant sequential and concurrent computational concepts in an idealized minimal cognitive device. The concept of fundamental cognitive chain formalizes temporal limits of cognition.