{"id":75,"date":"2007-09-30T14:41:32","date_gmt":"2007-09-30T13:41:32","guid":{"rendered":"http:\/\/www.pauljorion.com\/blog_en\/?p=75"},"modified":"2007-10-01T00:19:52","modified_gmt":"2007-09-30T23:19:52","slug":"thought-as-word-dynamics","status":"publish","type":"post","link":"https:\/\/www.pauljorion.com\/blog_en\/2007\/09\/30\/thought-as-word-dynamics\/","title":{"rendered":"Thought as Word Dynamics"},"content":{"rendered":"

On two occasions already on my French blog, I\u2019ve written an article in a serialized format, posting each part whenever it was ready then creating a link to a copy of the whole text when it had reached a final form. In both instances has the process taken about two months (Les t\u00e2ches et les responsabilit\u00e9s qui sont aujourd\u2019hui les n\u00f4tres <\/a>; Ce qu\u2019il est raisonnable de comprendre et partant d\u2019expliquer<\/a>).
\nI will proceed in the same way with Thought as Word Dynamics<\/strong>. I envision that the process will take longer as the text is structured at inception as having twenty-five chapters. I will try to post simultaneously an English and a French version.<\/p>\n

I worked full-time as an Artificial Intelligence researcher from 1988 to early 1990. My final report for British Telecom <\/strong>(Martlesham Heath \u2013 U.K.) is entitled An alternative neural network representation for conceptual knowledge<\/a>. My work at the Laboratoire d\u2019Informatique pour les Sciences de l\u2019Homme<\/strong> (Paris) led to a book entitled Principes des syst\u00e8mes intelligents <\/a>(Paris: Masson, 1990).<\/p>\n

Thought as Word Dynamics<\/strong><\/p>\n

The model presented here has been built over a number of years from several angles, combining theoretical knowledge with feedback obtained from implementing it as a piece of software. I regard philosophy, a twenty-five century speculative pursuit by the best minds of every period, as a legitimate source of knowledge on cognition. Some other – and possible unlikely – sources have shown to be of essential benefit for both this study and my previous work in Artificial Intelligence: Freudian psychoanalysis, mediaeval contributions to logic and the work of the ancient Chinese logicians.<\/p>\n

The ambition here is to provide a framework for speech acts, being specific enough about both its architecture and its dynamics to be testable as an Artificial Intelligence application. The test began several years back when, being part of British Telecom\u2019s \u201cConnex\u201d Project, I designed ANELLA as an \u201cAssociative Network with Emergent Logic and Learning Abilities.\u201d <\/p>\n

I. General principles<\/strong>
\n1. Speech acts are generated as the outcome of a dynamics operating on a network
\n2. The network in question is stored in the human brain
\n3. A talking subject experiences the dynamics of speech generation as emotional or \u201caffective\u201d <\/p>\n

II. Architecture<\/strong>
\n4. The network comprises a subset of the words (the \u201ccontent words\u201d) of a particular natural language
\n5. The individual unit in the network as far as speech generation is concerned is a word-pair
\n6. Each such word-pair has at any time an affect value attached to it
\n7. The affect value of the word-pairs results from Hebbian reinforcement
\n8. The network has two principles of organization: hereditary and endogenous
\n9. The hereditary principle is isomorphic to the mathematical object called a \u201cGalois Lattice\u201d
\n10. The endogenous principle is isomorphic to the mathematical object called a \u201cP-graph\u201d
\n11. The endogenous principle is primary
\n12. The hereditary principle is historical: it allows syllogistic reasoning and amounts to the emergence of \u201creason\u201d in history <\/p>\n

III. Dynamics<\/strong>
\n13. The skeleton of each speech act is a path of finite length in the network
\n14. A speech act is the outcome of several \u201ccoatings\u201d on a path in the network
\n15. The generation of a speech act is a gradient descent in the phase space of the network when submitted to an affect dynamics
\n16. The utterance of a speech act modifies the affect values of the word-pairs activated in the act
\n17. The gradient descent (relaxation) restores an equilibrium in the network
\n18. Imbalance in the affect values attached to the network has four possible sources<\/p>\n

1. Bodily processes experienced by the speaking subject as \u201cmoods\u201d
\n 2. Speech acts of an external origin, heard by the speaking subject
\n 3. Speech acts of an internal origin: thought processes as \u201cinner speech\u201d or hearing oneself speak (being a sub-case of 2.)
\n 4. Empirical experience (perception)<\/p><\/blockquote>\n

19. In the healthy subject, each path has inherent logical validity; this is a consequence of the topology of the network
\n20. Neurosis results from imbalance of affect values on the network impairing normal flow (Freudian \u201crepression\u201d)
\n21. Psychosis amounts to defects in the Network\u2019s structure (Lacanian \u201cforeclosure\u201d)<\/p>\n

IV. Consequences<\/strong>
\n22. Speech generation is automatic and only involves the four sources mentioned above (18)
\n23. Speech generation is deterministic
\n24. There is no room for any additional \u201csupra-factor\u201d in speech act generation than the four mentioned above (18)
\n25. One such superfluous \u201csupra-factor\u201d would be \u201cintentionality,\u201d triggered by consciousness or otherwise<\/p>\n","protected":false},"excerpt":{"rendered":"

On two occasions already on my French blog, I\u2019ve written an article in a serialized format, posting each part whenever it was ready then creating a link to a copy of the whole text when it had reached a final form. In both instances has the process taken about two months (Les t\u00e2ches et […]<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_crdt_document":"","footnotes":""},"categories":[3],"tags":[],"class_list":["post-75","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence"],"_links":{"self":[{"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/posts\/75","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/comments?post=75"}],"version-history":[{"count":0,"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/posts\/75\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/media?parent=75"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/categories?post=75"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/tags?post=75"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}