Abstract
We have used a neural network formalism in order to analyze under which conditions a positive answer could be given to the following question: can neural networks self-organize so that not only structures and functions not explicitly programmed emerge from their dynamics, but also goals for intentional actions, set up and achieved by themselves?
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Notes
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Let us recall the classical description of intentional actions by the practical syllogysm:
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Agent A desires to be in state S.
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A knows or believe that C is a cause for S.
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Therefore A performs C.
This description assumes intentional mental states from the beginning, such as desire, knowledge, belief. In our model, knowledge or belief are just retrieved memories of previous causal events. In addition, as Elizabeth Anscombe rightfully noticed, the first proposition of the syllogism may be conflated with the third. Contrary to the usual demonstrative syllogism (Men are mortal, Socrates is a man, etc.), the first proposition here does not add information: it is contained in the “therefore” of the third proposition. Our model may be seen as a computer simulation of this modified syllogism, where intentional mental states causing intentional actions and different from them are not needed.
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Atlan, H., Louzoun, Y. (2010). Emergence of Intentional Procedures in Self-Organizing Neural Networks. In: Carsetti, A. (eds) Causality, Meaningful Complexity and Embodied Cognition. Theory and Decision Library A:, vol 46. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3529-5_2
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