Description: Agent-Based Modeling (ABM) is a modeling approach that uses agents to represent and simulate the actions and interactions of autonomous entities. These agents can be individuals, groups, or even entire systems, and are designed to act independently, making decisions based on predefined rules or their environment. This approach allows for the study of complex phenomena across various disciplines, such as economics, biology, sociology, and computer science, by providing a more realistic representation of system dynamics where local interactions can lead to large-scale emergent behaviors. Agents can be programmed to adapt and learn from their environment, adding a layer of complexity and realism to simulations. ABM is characterized by its ability to model nonlinear systems and its flexibility to incorporate different types of agents with diverse characteristics and behaviors. Additionally, it allows for the exploration of hypothetical scenarios and the evaluation of policies or strategies in a controlled environment, making it a valuable tool for researchers and professionals across multiple fields.
History: Agent-Based Modeling began to take shape in the 1970s with the development of simulations that incorporated autonomous entities. One significant milestone was John Holland’s work in the 1980s, who introduced concepts of complex and adaptive systems. Throughout the 1990s, ABM gained popularity across various disciplines, especially in social and biological sciences, due to improvements in computational capacity and the development of specialized software such as NetLogo and Repast.
Uses: Agent-Based Modeling is used in a variety of fields, including economics to simulate markets, in ecology to model interactions between species, and in sociology to study social dynamics. It is also applied in urban planning, resource management, and public health research, where the spread of diseases or consumer behavior can be modeled.
Examples: A practical example of Agent-Based Modeling is the use of NetLogo to simulate the spread of infectious diseases in a population, where each agent represents an individual who can become infected or recover. Another example is the use of ABM in economics to model consumer behavior and its impact on the market.
