By Uri Wilensky
The creation of common quickly computing has enabled us to paintings on extra complicated difficulties and to construct and study extra complicated types. This e-book presents an advent to 1 of the first methodologies for learn during this new box of wisdom. Agent-based modeling (ABM) bargains a brand new approach of doing technological know-how: through engaging in computer-based experiments. ABM is appropriate to complicated structures embedded in average, social, and engineered contexts, throughout domain names that diversity from engineering to ecology. An advent to Agent-Based Modeling deals a entire description of the center ideas, equipment, and functions of ABM. Its hands-on strategy -- with hundreds of thousands of examples and workouts utilizing NetLogo -- allows readers to start developing versions instantly, despite adventure or discipline.
The booklet first describes the character and purpose of agent-based modeling, then offers the technique for designing and construction ABMs, and eventually discusses tips to make the most of ABMs to reply to advanced questions. beneficial properties in every one bankruptcy contain step by step courses to constructing versions usually textual content; textual content containers with more information and ideas; end-of-chapter explorations; and references and lists of appropriate analyzing. there's additionally an accompanying site with the entire versions and code.
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Extra info for An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo
We use the term model implementation to refer to this process of transforming a textual model1 into a working computational simulation (written in some form of computer “code”). Besides textual models, there are other forms of conceptual models that describe processes, objects, or events but are not computational; conceptual models can also be diagrammatic or pictorial. This description lends itself particularly well to being implemented, since it results from a particular standpoint, that of an individual ant, or ant agent.
8 one action if the predicate is true and another if it is false. The first “if” in the preceding code asks if the ant is carrying food. If she is not carrying food, then she takes the first action, that is, to look for food. She does this by checking to see if there is food where she is standing, and if there is not she looks around to see if there is a pheromone trail nearby that she can follow to find food (this is all described in the “look-for-food” procedure). If she is carrying food, then she takes the second action, which is to turn back toward the nest.
Ants with food drop a chemical pheromone onto the ground as they are carrying their food. This pheromone interacts with the environment by diffusing and evaporating. Maybe this pheromone is the key to ant communication? 1 Ant trails. Pheromone trail networks of pharaoh ants on a smoked glass surface. (A) Part of a network showing bifurcations to smaller trails (scale bar: 1 cm). 5 This would explain not only the trails that the ants form but also additional phenomena that can be observed. For instance, if ants communicated directly about food sources (as in the first two hypotheses), then any ant would have to communicate with the ant that had discovered the food source, or communicate with an ant that had communicated with that ant.