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- W1490494317 abstract "In the development of disciplines addressing dynamics, a major role was played by the assumption that processes can be modelled by introducing state properties, called potentialities, anticipating in which respect a next state will be different. A second assumption often made is that these state properties can be related to other state properties, called reducers. The current paper proposes a philosophical framework in terms of potentialities and their reducers to obtain a common philosophical foundation for methods in AI and Cognitive Science to model dynamics. This framework provides a unified philosophical foundation for numerical, symbolic, and hybrid approaches." @default.
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- W1490494317 date "2007-01-06" @default.
- W1490494317 modified "2023-09-26" @default.
- W1490494317 title "Higher-order potentialities and their reducers: a philosophical foundation unifying dynamic modelling methods" @default.
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