Agent-Based Modeling and Simulation

In academic research, the term "agent-based" modeling and simulation (M&S) is used ambiguously both for individual-based M&S and cognitive agent M&S. The former, which is also called "microscopic" simulation (or microsimulation), is focused on modeling (collections of) individuals and their interactions with each other and with their environment for modeling complex systems, whereas the latter is more concerned with modeling the cognitive state and cognitive operations of an agent.

Consequently, it seems natural to distinguish between a weak concept of agents, which we call basic agents, as commonly used in individual-based simulation where agents are entities that interact with their environment and with each other, and a strong concept, called cognitive agents, that is based on modeling the cognitive (or mental) state and operations of agents.

Since the interactions of agents are based on discrete perception and action events, it is natural to define an agent-based M&S approach as an extension of a DES approach, such that it is an option to use the concept of agents along with the more basic concepts of objects and events. Along these lines, OEM&S can be extended by adding the concept of agents, together with concepts of perception and action events as well as communication, resulting in Agent/Object Event Modeling and Simulation (A/OEM&S).

Examples of Agent-Based DES Models

A four stage supply chain consists of a retailer, a wholesaler, a distributor and a factory.
A simulation of a signaling reinforcement learning (RL) process, where two agents learn to communicate with each other via signals.