Understand-able Rudements in World Modeling

Abstract
In pursuing an “Understanding of Understanding”, this paper poses scientific rudiments for AI world/super-intelligent modeling. To start, one must first see that terms like understanding, intelligence, knowledge, etc. are “suitcase words” that must be ”unpacked” to reveal core concepts . For example, this paper targets global world modeling (hereafter WM) as an a priori role, beyond today’s AI ‘world modeling’ of narrow agent environs. It thus starts by noting early human habits as an initial world view (instinctual understanding). It next ‘unpacks’ five related empiric/logical/philosophic WM roles that evoke scientific ‘sense-making’. As such, the paper poses a continuum of understanding from instinct, onto intuition and fluid cognition; all toward initial WM Rules. Lastly, a grasp of all innately Entropic forms (generic expansion) is posed as the most-central understandable WM rudiment. More advanced detail is given in a companion paper at: https://drive.google.com/file/d/1huM4P1scPtcUT4r3EH4mC4Ss16B6KLgB/view, with more detailed videos also posted at: https://www.youtube.com/@MarcusAbundis

1. Introduction and Background
Recent gains in narrow artificial intelligence (AI) and debate on its future in science, business, and society calls for deep thought on needed fundaments—beyond today’s broad promises, ‘black boxes’, ‘hallucinations’, and ‘logical gaps’. For example, we expect the eventual advent of general/super AI, which I call true World Modeling (WM), where understanding ‘What exactly is being modeled?’ is needed to avoid naive onto catastrophic results. This paper thus targets deep thought on AI’s eternal human links, from a most-wide philosophic/scientific perspective, working toward detailed understandable WM.

2. A World Modeling Context
Foremost, a natural WM starting point is Earth as it holds all that we see as ‘intelligent’ (widely defined). For example, we have no firm grasp of life beyond Earth, where other intelligences also elude us, all marking an Earthly ‘core context’. But we also see that Earth inhabits a vast cosmos, dating to Copernicus and before, where much remains to be revealed. In this broad Earth↔cosmos context—the thing we must ultimately grasp—I pose three most-central initial WM roles as ‘instinctual understanding’, and that I later use to frame early WM Rules. I see those central instinctual aspects as:

Adaption: We first see WM intelligence as driven Life ‘agents’ amid Earthly conflicts, using bare genomic and behavioral (informatic) variation to survive and reproduce. Here, agents with poor related object-oriented material results become extinct;
Cognitive Adaption: Beyond bare adaptive genomic-behavioral acts, cognition marks a behaviorally-plastic ‘psyche’ with more-fluid (selectable) functional scales. Here, agents with poor cognition (bare psychomotor↔larger space-time acuity), struggle.
Creative Adaption: An Earth↔cosmos context is ‘open’ (creatively dynamic), versus science’s imagined ‘closed systems’ (energy exchanges, but omits matter) and ‘isolated systems’ (no energy/matter exchanges) ; all calling for ‘better science’.This all reduces to ‘an agent drive for coordinated material creativity ≈ adaptive instinct’—seen in early discoveries (fire) and inventions (handaxe) onto today’s vast techno-cultural ecology. More-usual listed instincts hold much more, but I use this bare adaptive view since ideas on ‘What is instinctual?’ versus ‘learned’, etc. vary widely, not easily seen as ‘science’. Still, the above holds enough to initiate WM. For example, no. 1 points to ‘Who, What and Why?’, no. 2 evokes ‘When and Where?’, and no. 3 suggests ‘How?’ Following this adaptive instinct, the paper next ‘unpacks’ a few empiric proto-Rules. Lastly, those observed ‘Rules’, and their application, are explored further in mixed short studies.

• FIRST PROTO-RULE, OPEN SYSTEMS & CREATIVITY: Creativity infuses our earliest, most successful scientific model, Darwin’s Tree as evolution by means of natural selection (EvNS), alongside Natural “order for free” and “adjacent possibilities”—all as a bounded-yet-ambiguous ‘creative space’. This contrasts to modern science’s forced closed and isolated system views, aiming to: describe-and-explain, cause-and-effect, in measurable-and repeatable ways, with necessary-and-sufficient detail. But here, omitting Nature’s open energy-matter exchanges is odd, if the most interesting thing about Earthly intelligence is creative adaption. Open uncontrolled variables, the bane of science, are fated as cosmic and solar winds/radiation, space debris, mixed informatic exchanges, and shifting environs jointly marking an Earth↔cosmos dialectic-dichotomy (‘Entropy’). But science asserts Earth is closed due to low matter capture, ignoring things like dinosaur extinction, a possible origin of Life, the moon’s genesis, a likely cause of the Younger-Dryas era, and perhaps more. Thus, true WM must surpass today’s science as innately creative, to fully mirror Nature. Moreover, our notoriously imaginal psyche (God[s], etc.) allows us to ‘ponder’ further adaptions, where the quality of curiosity and creativity is key. Today, the Santa Fe Institute’s complex adaptive systems and chaos theory/‘butterfly effect’ arise, onto Stephen Wolfram’s A New Kind of Science with a ‘Ruliad’ for ‘mining a computational universe’, all partly-addressing Nature’s empiric evolving creativity (EvNS).
• SECOND PROTO-RULE, INANIMATE & ANIMATE MATTER: Inanimate and animate matter fill Earth, where no other third aspect (spirits, etc.) is clearly seen. But in a cosmos of mostly plain matter, animate Life remains a mystery (hence, God[s], etc.) Still, Life amid abundant inanimate matter demands we confront four bare facts:

‘Dualist logic’ exists as direct material stimulus-response (plain matter dynamics) contra indirect stimulus-processing-response (genomic/behavioral adaption);
This also evokes an ‘adaptive boundary’ as a pure-matter context contra Life’s adaptive content. For example, oxygen atoms, etc. have no likely need or drive to maintain an ‘atomic identity’, in contrast to innately ‘mortal’ Life agents; Further, ‘functional abstracts’ that enable informatic processing (re no. 1) must also exist. This shows as bare genomics, agent trial-and-error behavior, and symbolic agent behavior, all pointing to some ‘material-informatic processing’ aspect;
Thus, a further motive cause or raison d’etre of ‘intelligent effects’ must also exist (enacted ‘informatic processing’)—a core aim-and-means for all above exploits.

Finally, this all supports a deep archetypal sense of Death-Life (Entropy, mortality), or a core empiric context (Death) for all empiric content (Life’s survival processing).

• THIRD PROTO-RULE, SCALABLE SELECTIVITY: In an Earth↔cosmos context, transient simple-to-complex facets with contiguous-but-differed phases abound, as seen in Darwin’s Tree. But this also shows in inanimate atoms onto a periodic table, molecules, proteins, etc., all composing one contiguous Entropic cosmos. Next-mapping Entropic detail (transient, simple, complex, contiguous, differed, inanimate, animate, material, and informatic) poses ‘structural fundaments’ for an empiric scalable-and-selectable/simple-to-complex ‘WM order’. This also shows in Shannon signal entropy as “the mother of all models” in a similar scalable-and-selectable/simple-to-complex empiric manner, therein supporting all of information technology.
• FOURTH PROTO-RULE, KNOWLEDGE & INTELLIGENCE AS Content: A ‘WM order’ also ties to agent sensorium inputs as ‘bare Entropic intelligence’, where some agents fail (extinct), and better detail builds intelligence (survival). In turn, codified intelligence
(working memory, etc.) has empiric content as ‘knowledge’ of selective-serial trial-and-error events (survival). Science lacks an equally cohesive (contiguously creative) WM view, due to its many closed and isolated ‘logical gaps’, where Nature has no gaps.
• FIFTH PROTO-RULE, SUBJECTIVE-SOCIABILITY: Functional abstracts (genomic and behavioral) come discretely. No one device informs all agents simultaneously/instantly. Here, empiric happenstance means agents ‘experience’ Earth as unique/discretely differed space-time events. Also, each agent’s own empiric properties-and-traits (height, strength, sight, etc.) varies sensorium inputs. Lastly, prior agent experience and needs, further affect perception—all driving innate subjectivity, often dismissed by science. But none of this stops agent experiences from being collectively shared and distilled ‘after the fact’, as with science and religion, via ‘language’ and sociability.

In toto, I believe the above supports the minimum needed for true scalable WM, beyond today’s science, and beyond today’s AI ‘world modeling’ of narrow (non-scalable) agent environs. It seeks to frame ‘What true WM is’, rather than hoping to reform ‘What science and AI might be’. It “unpacks”, as Marvin Minsky saw, “suitcase words” and concepts tied to contiguous WM/empiric vistas. But if ‘better detail builds intelligence’, these Rules are also expected to improve with more study—a question remains: ‘Are these Rules truly all that is necessary and sufficient for WM?’ Lastly, even if intelligence remains a hotly debated topic, enough is covered here to explore a few initial WM implications.

3. Initial ‘WM Order’ Implications
As stated, this paper targets deep thought on AI’s human links toward understandable WM. So far, the above merely offers a provisional account with no claim made that ‘All that is needed for true WM is now present’. The paper’s aim is more to incite further study and discourse, offering many likely further directions. With that disclaimer in place, I now explore a few of what I see as the most critical of those directions.

3.1. Embodiment—A ‘Work-able’ Platform
As this analysis starts with an instinctual view, one already asserts ‘some embodied form’ (an agent), genomically derived via: immediate environs (happenstance), material dimensions, and sensorium capacities jointly composing a work-able platform for empiric encounters . . .

REMAINING SUBSECTION TITLES MERELY SUGGEST MANY POSSIBLE FURTHER EXPLORATIONS.

3.2. Intelligence—A ‘Knowledge-able’ Platform

3.3. Analytic versus Synthetic Reasoning

3.4. Signal and Thermodynamic Entropy

4. Conclusion