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| Main Authors: | , |
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| Format: | Preprint |
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2025
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| Online Access: | https://arxiv.org/abs/2511.05580 |
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| _version_ | 1866908637758226432 |
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| author | Bagley, Bryce-Allen Khoshnan, Navin |
| author_facet | Bagley, Bryce-Allen Khoshnan, Navin |
| contents | The complexity of human cognition has meant that psychology makes more use of theory and conceptual models than perhaps any other biomedical field. To enable precise quantitative study of the full breadth of phenomena in psychological and psychiatric medicine as well as cognitive aspects of AI safety, there is a need for a mathematical formulation which is both mathematically precise and equally accessible to experts from numerous fields. In this paper we formalize human psychodynamics via the diagrammatic framework of process theory, describe its key properties, and explain the links between a diagrammatic representation and central concepts in analysis of cognitive processes in contexts such as psychotherapy, neurotechnology, AI alignment, AI agent representation of individuals in autonomous negotiations, developing human-like AI systems, and other aspects of AI safety. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_05580 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Approximating the Mathematical Structure of Psychodynamics Bagley, Bryce-Allen Khoshnan, Navin Neurons and Cognition Computation and Language Computers and Society Human-Computer Interaction 18M35 (primary) 47N99, 47A50, 60H25, 68T37, 68T42, 81V99, 91C99, 91E10, 94A99 (secondary) E.4; G.3; I.2.0; I.2.4; J.3; J.4 The complexity of human cognition has meant that psychology makes more use of theory and conceptual models than perhaps any other biomedical field. To enable precise quantitative study of the full breadth of phenomena in psychological and psychiatric medicine as well as cognitive aspects of AI safety, there is a need for a mathematical formulation which is both mathematically precise and equally accessible to experts from numerous fields. In this paper we formalize human psychodynamics via the diagrammatic framework of process theory, describe its key properties, and explain the links between a diagrammatic representation and central concepts in analysis of cognitive processes in contexts such as psychotherapy, neurotechnology, AI alignment, AI agent representation of individuals in autonomous negotiations, developing human-like AI systems, and other aspects of AI safety. |
| title | Approximating the Mathematical Structure of Psychodynamics |
| topic | Neurons and Cognition Computation and Language Computers and Society Human-Computer Interaction 18M35 (primary) 47N99, 47A50, 60H25, 68T37, 68T42, 81V99, 91C99, 91E10, 94A99 (secondary) E.4; G.3; I.2.0; I.2.4; J.3; J.4 |
| url | https://arxiv.org/abs/2511.05580 |