  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).
