The Quest for a Common Model of the Intelligent Decision Maker

TL;DR

This paper proposes a unified, discipline-agnostic model of the intelligent decision maker, emphasizing shared core concepts across psychology, AI, economics, control theory, and neuroscience to foster interdisciplinary understanding.

Contribution

It introduces a comprehensive, neutral framework for the decision maker that unifies diverse disciplinary perspectives and terminology, promoting cross-disciplinary collaboration.

Findings

Identifies core components of decision making across disciplines

Highlights the convergence of diverse fields on a common model

Discusses challenges and benefits of interdisciplinary terminology

Abstract

The premise of the Multi-disciplinary Conference on Reinforcement Learning and Decision Making is that multiple disciplines share an interest in goal-directed decision making over time. The idea of this paper is to sharpen and deepen this premise by proposing a perspective on the decision maker that is substantive and widely held across psychology, artificial intelligence, economics, control theory, and neuroscience, which I call the "common model of the intelligent agent". The common model does not include anything specific to any organism, world, or application domain. The common model does include aspects of the decision maker's interaction with its world (there must be input and output, and a goal) and internal components of the decision maker (for perception, decision-making, internal evaluation, and a world model). I identify these aspects and components, note that they are given different names in different disciplines but refer essentially to the same ideas, and discuss the challenges and benefits of devising a neutral terminology that can be used across disciplines. It is time to recognize and build on the convergence of multiple diverse disciplines on a substantive common model of the intelligent agent.