The Ouroboros Model

TL;DR

The Ouroboros Model presents a recursive, self-monitoring framework for understanding human cognition, learning, and reasoning, emphasizing the role of expectations, memory schemata, and feedback mechanisms in adaptive behavior.

Contribution

It introduces a novel recursive model with a feedback loop involving expectations and emotions, applicable to goal-directed actions and rational reasoning.

Findings

Effective partial implementations in safety systems

Model explains various human behaviors including learning and meta-learning

Provides a unified framework for cognition and decision-making

Abstract

At the core of the Ouroboros Model lies a self-referential recursive process with alternating phases of data acquisition and evaluation. Memory entries are organized in schemata. Activation at a time of part of a schema biases the whole structure and, in particular, missing features, thus triggering expectations. An iterative recursive monitor process termed 'consumption analysis' is then checking how well such expectations fit with successive activations. A measure for the goodness of fit, "emotion", provides feedback as (self-) monitoring signal. Contradictions between anticipations based on previous experience and actual current data are highlighted as well as minor gaps and deficits. The basic algorithm can be applied to goal directed movements as well as to abstract rational reasoning when weighing evidence for and against some remote theories. A sketch is provided how the Ouroboros Model can shed light on rather different characteristics of human behavior including learning and meta-learning. Partial implementations proved effective in dedicated safety systems.