Bruza, Peter D. & Cole, Richard (2005) Quantum Logic of Semantic Space: An Exploratory Investigation of Context Effects in Practical Reasoning. In Artemov, S., Barringer, H., d'Avila Garcez, A.S., & Woods, J.H. (Eds.) We Will Show Them: Essays in Honour of Dov Gabbay. College Publications, London, UK, pp. 339-361. https://arxiv.org/abs/quant-ph/0612178
"Associations are often based on similarity (e.g., semantic or analogical similarity)....
The strength of associations between concepts change dynamically under the influence of context" (2).
"A product of the collapse is a change of state, or “meaning” of the word. As a consequence, word associations also change. QM is one of the few frameworks in which context is neatly integrated. Essentially, context is something akin to a quantum measurement which brings about collapse." ... However, "In QM, collapse results in an eigenstate, whereas the collapse of word meaning in semantic space may be partial" (20).
OK, so what this means, I think, is that formulas from quantum mechanics may be applied to representing how we categorize new conceptual information (aka knowledge). The categories we put concepts in are based on their associations with each other; the context they are in leads to specific meaning. When one puts a term in context, as in a phrase or sentence, the possible meanings of the term collapse, perhaps to a fewer number, or even to one (the "eigenstate"). How strongly we associate a concept with other concepts depends on their similarity.
Context is everything. So, if one chooses to categorize the concept of "light" as being made of "particles" (associating light with "matter"), that is what one detects and measures; and the same for "light" and "waves" (associating it with "sound").
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Busemeyer, Jerome & Bruza, Peter D. (2012) Quantum models of cognition and decision. Cambridge University Press, Cambridge.
This book follow up with applying quantum probability to semantics and applying the quantum entanglement state to neuroscience to understand how we process information - how we think and know, how we make decisions, word associations and memory.
Peter is now applying information processing to artificial intelligence, autonomous robots, health-related clinical decision-making, and trust. He is the Discipline Leader for Information Science, which is where my sabbatical QUT fellowship is situated.
"Associations are often based on similarity (e.g., semantic or analogical similarity)....
The strength of associations between concepts change dynamically under the influence of context" (2).
"A product of the collapse is a change of state, or “meaning” of the word. As a consequence, word associations also change. QM is one of the few frameworks in which context is neatly integrated. Essentially, context is something akin to a quantum measurement which brings about collapse." ... However, "In QM, collapse results in an eigenstate, whereas the collapse of word meaning in semantic space may be partial" (20).
OK, so what this means, I think, is that formulas from quantum mechanics may be applied to representing how we categorize new conceptual information (aka knowledge). The categories we put concepts in are based on their associations with each other; the context they are in leads to specific meaning. When one puts a term in context, as in a phrase or sentence, the possible meanings of the term collapse, perhaps to a fewer number, or even to one (the "eigenstate"). How strongly we associate a concept with other concepts depends on their similarity.
Context is everything. So, if one chooses to categorize the concept of "light" as being made of "particles" (associating light with "matter"), that is what one detects and measures; and the same for "light" and "waves" (associating it with "sound").
---------------------------
Busemeyer, Jerome & Bruza, Peter D. (2012) Quantum models of cognition and decision. Cambridge University Press, Cambridge.
This book follow up with applying quantum probability to semantics and applying the quantum entanglement state to neuroscience to understand how we process information - how we think and know, how we make decisions, word associations and memory.
Peter is now applying information processing to artificial intelligence, autonomous robots, health-related clinical decision-making, and trust. He is the Discipline Leader for Information Science, which is where my sabbatical QUT fellowship is situated.
