Paradigms of Computational Agency

TL;DR

This paper reviews the evolution of agent-based models, highlighting their diversification and potential for advancing artificial intelligence, especially with recent hardware innovations like GPUs.

Contribution

It provides a comprehensive perspective on how computational models of agency have evolved and discusses future directions influenced by hardware advancements.

Findings

Agent-based models have diversified significantly since the 1990s.

Recent hardware like GPUs can revitalize agent-based modeling and AI research.

The paper offers a historical and conceptual overview of agency in computational systems.

Abstract

Agent-based models have emerged as a promising paradigm for addressing ever increasing complexity of information systems. In its initial days in the 1990s when object-oriented modeling was at its peak, an agent was treated as a special kind of "object" that had a persistent state and its own independent thread of execution. Since then, agent-based models have diversified enormously to even open new conceptual insights about the nature of systems in general. This paper presents a perspective on the disparate ways in which our understanding of agency, as well as computational models of agency have evolved. Advances in hardware like GPUs, that brought neural networks back to life, may also similarly infuse new life into agent-based models, as well as pave the way for advancements in research on Artificial General Intelligence (AGI).