Agent-based modelling and simulation
Introduction
Agent-based modelling and simulation or agent-based simulation (ABS) or agent-based modeling refers to a model and simulation technique that infers the behavior of a system from the action and interaction of individuals. Modeling techniques range from simple and easy to complex and hard. It is often argued that agent-based modeling and simulation starts from "natural" description of a system (i.e. observable behavior and interactions of individuals) and that it can capture emergent phenomena in a flexible way.
“Agent-based simulation (ABS) is an approach to modeling systems comprised of individual, autonomous, interacting “agents.” Agent-based modeling offers ways to more easily model individual behaviors and how behaviors affect others in ways that have not been available before. There is much interest in developing agent-based models for many application problem domains. Applications range from modeling agent behavior in supply chains and the stock market, to predicting the success of marketing campaigns and the spread of epidemics, to projecting the future needs of the healthcare system.” (Macal et al, 2014) [1]
Wikipedia (March 2019) defines an “agent-based model (ABM) is a class of computational models for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) with a view to assessing their effects on the system as a whole.” Agent-based modeling and simulation is not multi-agent simulation, the former attempts to gain insights about complex systems from the collective behavior of agents that follow simple rules for action and interaction (e.g. move or eat), the latter simulates intelligent agents in some context.
“In agent-based modeling (ABM), a system is modeled as a collection of autonomous decision-making entities called agents. Each agent individually assesses its situation and makes decisions on the basis of a set of rules. Agents may execute various behaviors appropriate for the system they represent—for example, producing, consuming, or selling. Repetitive competitive interactions between agents are a feature of agent-based modeling, which relies on the power of computers to explore dynamics out of the reach of pure mathematical methods (1, 2). At the simplest level, an agent-based model consists of a system of agents and the relationships between them. Even a simple agent-based model can exhibit complex behavior patterns (3) and provide valuable information about the dynamics of the real-world system that it emulates. In addition, agents may be capable of evolving, allowing unanticipated behaviors to emerge. Sophisticated ABM sometimes incorporates neural networks, evolutionary algorithms, or other learning techniques to allow realistic learning and adaptation.” (Eric Bonabeau, 2002, Abstract) [2]
Architectures
According to Jeffrey Schank (March 30, 2019), “Agent-based modeling (ABM) is a style of modeling in which individuals and their interaction with each other and their environment are explicitly represented in a program or even in another physical entity such as a robot. Individuals modeled are, for example, people, animals, groups, or cells, but they can model entities that do not have a physical basis, but are entities that are conceived as performing a task such as gathering information or theoretically modeling the evolution of cooperation. [..] ABM is a style of modeling that has both experimental and mathematical styles of thinking.”
According to wikipedia (March 2019), “Most agent-based models are composed of: (1) numerous agents specified at various scales (typically referred to as agent-granularity); (2) decision-making heuristics; (3) learning rules or adaptive processes; (4) an interaction topology; and (5) an environment.”
Software
In education, there are
- NetLogo is based on a multi-turtle model. Each agent is a turtle that can move and interact with other turtles. According to comMSES, it is used by tens of thousands of students, teachers and researchers worldwide.
- AgentSheets is based on a cellular automaton and diffusion mathematics.
See also on other web sites:
- Computational Modeling Platforms at coMSES). Probably the best up-to-date list of software.
- Simulators, at Agent-Based Models.
Links
- coMSES (network for Computational Modeling in Social and Ecological Sciences) is an international network of researchers, educators and professionals with the common goal of improving the way we develop, share, and use agent based modeling in the social and ecological sciences
Bibliography
Niazi, Muaz; Hussain, Amir (2011). "Agent-based Computing from Multi-agent Systems to Agent-Based Models: A Visual Survey" (PDF). Scientometrics. 89 (2): 479–499. arXiv:1708.05872. doi:10.1007/s11192-011-0468-9.
Schelling, T.C. (1969) Models of Segregation in: Strategic Theory and Its Applications, Schelling, T.C. The American Economic Review, 59 (2), Papers and Proceedings of the Eighty-first Annual Meeting of the American Economic Association. (May, 1969), pp. 488-493. https://www.jstor.org/stable/1823701?seq=1#metadata_info_tab_contents
Cited with a footnote
- ↑ Macal, C. M., & North, M. J. (n.d.). Tutorial on agent-based modeling and simulation. In Proceedings of the Winter Simulation Conference, 2005. (pp. 2–15). IEEE. https://doi.org/10.1109/WSC.2005.1574234
- ↑ Bonabeau, E. (2002). Agent-based modeling: methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences of the United States of America, 99 Suppl 3(suppl 3), 7280–7287. https://doi.org/10.1073/pnas.082080899