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Goals in Adaptive Systems: Difference between revisions
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(Created page with "In the realm of adaptive systems, goals are a central concept around which different theorists have built their models. Three notable models that incorporate goals are Ashby's Law of Requisite Variety, Arthur Koestler's concept of bisociation, and the definition of intelligence offered by Marcus Hutter. This article explores the function of goals within each of these models and discusses how the principle of compounding can enhance the effectiveness of goal achievement....") |
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== Ashby's Law of Requisite Variety == | == Ashby's Law of Requisite Variety == | ||
W. Ross Ashby's Law of Requisite Variety is a foundational principle in cybernetics and control theory. It stipulates that for a system to be stable, the number of states that its control mechanism can attain must be greater than or equal to the number of states in the system being controlled. In this context, goals function as the desired states that the control system seeks to maintain or achieve. The variety in the control system must be sufficient to address the diverse challenges presented by the environment to meet these goals effectively. By applying the principle of compounding, a system can incrementally adjust its variety, learning and adapting from past experiences, thereby increasing its ability to swiftly and efficiently reach its goals with less energy expenditure over time. | W. Ross Ashby's Law of Requisite Variety is a foundational principle in cybernetics and control theory. It stipulates that for a system to be stable, the number of states that its control mechanism can attain must be greater than or equal to the number of states in the system being controlled. In this context, goals function as the desired states that the control system seeks to maintain or achieve. The variety in the control system must be sufficient to address the diverse challenges presented by the environment to meet these goals effectively. By applying the principle of compounding, a system can incrementally adjust its variety, learning and adapting from past experiences, thereby increasing its ability to swiftly and efficiently reach its goals with less energy expenditure over time. | ||
=== Example: Immune System Response === | |||
The human immune system is a real-life example of a complex control system that must deal with a vast array of pathogens. According to the Law of Requisite Variety, for the immune system to effectively protect the body, it must have a repertoire of responses that is at least as diverse as the pathogens it might encounter. The immune system achieves this through compounding in the form of adaptive immunity. When the body is exposed to a new pathogen, it not only fights off the current infection but also creates memory cells that "learn" the attributes of the pathogen. This evolutionary development allows the immune system to respond more quickly and efficiently should the same pathogen attack again, thus using less energy in subsequent encounters. | |||
== Arthur Koestler's Concept of Bisociation == | == Arthur Koestler's Concept of Bisociation == | ||