Cognitive Architecture for Decision-Making Based on Brain Principles Programming

TL;DR

This paper proposes a cognitive architecture inspired by brain principles, integrating logical-probabilistic inference, formal concepts, and systems theory to address diverse decision-making problems.

Contribution

It introduces a novel architecture based on five brain activity principles, with a task-driven approach and a foundational ontology for practical applications.

Findings

Implementation of a task-driven architecture for decision-making

Application of the architecture to practical problems

Demonstration of architecture's flexibility in various domains

Abstract

We describe a cognitive architecture intended to solve a wide range of problems based on the five identified principles of brain activity, with their implementation in three subsystems: logical-probabilistic inference, probabilistic formal concepts, and functional systems theory. Building an architecture involves the implementation of a task-driven approach that allows defining the target functions of applied applications as tasks formulated in terms of the operating environment corresponding to the task, expressed in the applied ontology. We provide a basic ontology for a number of practical applications as well as for the subject domain ontologies based upon it, describe the proposed architecture, and give possible examples of the execution of these applications in this architecture.