Tag: Social Modelling Agent-Based Simulation and Complexity
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SMABSC: Cognitive Agents
Cognitive models are a representation of an agent control mechanism resembling the cognitive architecture of a mind. It can be understood as a control system (e.g. a flow graph how to react) that takes sensory inputs and produces motor outputs (Piaget, 1985). More advanced models include adaptive memory (Anderson, 1983). Famous models include SOaR: State…
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SMABSC: Disease Propagation
The SIR model was introduced as a mathematical model with differential equations (Kermack & McKendrick, 1927). The basic states are Susceptible, Infected, and Recovered. [latex]N_i = \frac{dS}{dt}+\frac{di}{dt}+\frac{dR}{dt}[/latex] In the SIR model, the fundamental trajectory of disease propagation could be captured, immunity was acquired after disease and the population is homogeneous. But the SIR model has…
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SMADSC: Social Networks
Social networks often give structure to relations. They can be considered as abstract, mathematically, tractable and computationally instantiatable systems. Social networks have become a field of their own. It is very interdisciplinary touching mathematics (graph theory), computer science (algorithms), sociology (population group trends), psychology (individual and social behaviour), and complex network theory. Interpersonal contact caused…
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SMADSC: Introduction
Complex systems are the core topic of Social Modelling, Agent-Based Simulation, and Complexity. Complex systems usually emerge as an artefact of interaction. The output of a complex system follows the Power Law and may have a regime or phase changes, known as tipping points. Emergent properties and scale-free organisation are a typical feature of complex…