  Agent-based systems have the capability to fuse information from many
distributed sources and create better plans faster. This feature makes
agent-based systems naturally suitable to address the challenges in Supply
Chain Management (SCM). Although agent-based supply chains systems have been
proposed since early 2000; industrial uptake of them has been lagging. The
reasons quoted include the immaturity of the technology, a lack of
interoperability with supply chain information systems, and a lack of trust in
Artificial Intelligence (AI). In this paper, we revisit the agent-based supply
chain and review the state of the art. We find that agent-based technology has
matured, and other supporting technologies that are penetrating supply chains;
are filling in gaps, leaving the concept applicable to a wider range of
functions. For example, the ubiquity of IoT technology helps agents "sense" the
state of affairs in a supply chain and opens up new possibilities for
automation. Digital ledgers help securely transfer data between third parties,
making agent-based information sharing possible, without the need to integrate
Enterprise Resource Planning (ERP) systems. Learning functionality in agents
enables agents to move beyond automation and towards autonomy. We note this
convergence effect through conceptualising an agent-based supply chain
framework, reviewing its components, and highlighting research challenges that
need to be addressed in moving forward.

Artificial Intelligence