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The diagram consists of a set of words and arrows. Causal loop diagrams are accompanied by a narrative which describes the causally closed situation the CLD describes. Closed loops, or causal feedback loops, in the diagram are very important features of CLDs because they may help identify non-obvious vicious circles and virtuous circles.
A causal loop diagram is a simple map of a system with all its constituent components and their interactions. By capturing interactions and consequently the feedback loops (see figure below), a causal loop diagram reveals the structure of a system. By understanding the structure of a system, it becomes possible to ascertain a system's behavior ...
The causal loop diagram below shows escalation archetype as a single reinforcing loop. It can be read simply as that more action done by X creates bigger results of action done by X. The bigger results of X, the bigger difference between X and Y results. The bigger difference means more action by Y and more action by Y leads to bigger result of Y.
A causal loop diagram of growth and underinvestment The growth and underinvestment archetype is one of the common system archetype patterns defined as part of the system dynamics discipline. System dynamics is an approach which strives to understand, describe and optimize nonlinear behaviors of complex systems over time, using tools such as ...
A system archetype is a pattern of behavior of a system.Systems expressed by circles of causality have therefore similar structure.Identifying a system archetype and finding the leverage enables efficient changes in a system.
Causal mapping is the process of constructing, summarising and drawing inferences from a causal map, and more broadly can refer to sets of techniques for doing this. While one group of such methods is actually called “causal mapping”, there are many similar methods which go by a wide variety of names.
This is a list of causal mapping software. Causal mapping software enables users to create and/or work with causal maps: qualitative networks of interconnected nodes in which each connection represents a causal link. Software and services for concept mapping can also be used for causal mapping if they allow the creation of directed links.
A causal network is a Bayesian network with the requirement that the relationships be causal. The additional semantics of causal networks specify that if a node X is actively caused to be in a given state x (an action written as do( X = x )), then the probability density function changes to that of the network obtained by cutting the links from ...
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