Author
Abstract
This paper rigorously proves that Unified Cognitive Field Theory (UCFT) provides a fundamental, non-Markovian game-theoretic framework for cognition. I demonstrate that the seven core UCFT operators and field dynamics are necessary and sufficient to represent all cognitive game-theoretic phenomena, establishing a precise isomorphism between the evolution of the cognitive field and strategic dynamics. This framework explicitly accounts for history-dependent processes, offering a novel perspective on the physics of learning and the emergence of cognitive biases. A key implication explored is the concept of “Learning as a Solitaire Self-Game,” where individual cog- nition is viewed as a strategic optimization process against internal uncertainties, governed by substrate-dependent physical constants. This unification provides powerful new tools for understanding the complex interplay between physical substrate, strategic interaction, and the non-Markovian nature of intelligence. Keywords: non-Markovian game theory, cognitive field theory, quantum cognition, strategic dynamics, learning physics, cognitive bias, helical fiber bundles, substrate-dependent cognition, self-play optimization, temporal game theory, field-theoretic neuroscience, consciousness as strategy, memory persistence, cognitive temperature, strategic noise cancelling, belief revision dynamics, UCFT operators, Nash equilibria in cognitive space, Bayesian field updates, angle of attack learning This is an early draft and an excerpt from a larger monograph that will be posted later; this proof has some dependencies on that which are not explicitly proven because they are proven there. Furthermore, expect this to be updated. Commercial software implementations are patent pending (63/849,479), but academics and researchers are welcomed and encouraged to use freely if this proves accurate.
Suggested Citation
Leizerman, Samuel L, 2025.
"Non-Markovian Game Theory: The Physics and Strategy of Learning and Bias (UCFT),"
SocArXiv
hxfp9_v1, Center for Open Science.
Handle:
RePEc:osf:socarx:hxfp9_v1
DOI: 10.31219/osf.io/hxfp9_v1
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:socarx:hxfp9_v1. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://arabixiv.org .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.