Paradigms of Computational Agency
It provides a perspective on the historical and conceptual development of agency in computing, which is incremental and foundational for researchers in AI and complex systems.
The paper examines the evolution of computational agency from its origins as a specialized object-oriented model to a diverse paradigm with potential for new insights into systems and AGI, highlighting how hardware advances like GPUs could revitalize agent-based models.
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).