Selection Dynamics as an Origin of Reason

SELECTION DYNAMICS AS AN ORIGIN OF REASON (Causes of Cognitive Information - a Path to ‘Super Intelligence’) Marcus Abundis1 Abstract This study explores ‘adaptive cognition’ in relation to agents striving to abide entropic forces (natural selection). It enlarges on a view of Shannon (1948) information theory and a ‘theory of meaning’ (Abundis, 2016) developed elsewhere. The analysis starts by pairing classic selection pressure (purifying, divisive, and directional selection ) and agent acts (as flight, freeze, and fight responses), to frame a basic model. It next details ensuing environs-agent exchanges as marking Selection Dynamics, for a ‘general adaptive model’. Selection Dynamics are then shown in relation to chaos theory, and a fractal-like topology, for an initial computational view. Lastly, the resulting dualist-triune topology is detailed as sustaining many evolutionary and cognitive roles, thus marking an extensible adaptive informational/cultural fundament (13 pages: 5,700 words).

Keywords: adaptivity, natural selection, evolution, information theory, theory of meaning, information science, cognition, chaos theory, fractal, cultural ecology.

INTRODUCTION – The Evolutionary Landscape This paper explores general agent adaptivity as a living informatics, with agents ‘thinking like nature’ (natural informatics) as the adaptive goal.

To start, Earth’s reflexive unfolding (dynamic environs) presents a stage upon which all life arises and evolves. As such, earthly entropy must be mapped before naming any notion of adaptive agency or living informatics. Earthly entropy vis-à-vis life is often shown as purifying, divisive, and directional selection pressure (Figure 1). Here, dispersive or ‘entropic’ forces presumably overwhelm existing agents and drive a shift to new agent roles. Agents are seen as submitting to those forces, where genomic variations innate to each agent drive the difference between eventual survival or death. Only ‘survivors’ reproduce and come to present new agent roles for each species.

Figure 1: Classic Selection Pressure. Agent populations (areas under dashed lines) find new niche roles (solid lines), where material resource shifts (arrows) force new agent traits and roles to arise. ‘Agent selection’ occurs between remaining resources (niche affordance) and agent resource needs. As a Divisive example, a river crossing an elevating plain erodes a wide gap (natural boundary), where two squirrel species then arise from one ancestral species, as seen in Grand Canyon National Park. Lastly, Purifying selection is reductive, but Divisive selection and Directional selection are expansive, and thus afford ‘forced novelty’.

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Organizational Behavior (GFTP), Graduate School of Business, Stanford University (March 2011).

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A true account of speciation has many facets but a basic view is used in Figure 1 to facilitate the model’s development. Also, to map ‘general entropic dynamics’ within nature, classic selection pressures (purifying, divisive, and directional) are reduced to generic right-ward, down-ward, and left-ward resource shifts or Selection Vectors. These steps initiate a base map (Figure 2), which is then expanded upon.

Figure 2: Selection Dynamics – general map. Selection Vectors (resource shifts from Figure 1) surround agent responses (classic flight, freeze, and fight), framing an initial constrained-contested space. Environs-agent exchanges then yield a Bounded Affordance line (niche). Environs-agent interactions can be complex (uncontrolled variables, environmental happenstance) and difficult to predict. But here, all roles (i.e., Selection Dynamics: [a] classic agent responses, and [b] selection pressure) have a dualist-triune trait. For example, Selection Dynamics hold a 2-3 form: three roles below [a], and three roles above [b]. Agent responses [a] show a 3-2 form: 1) a ‘Set’ freeze, and 2) variable flight and fight roles. Lastly, Figure 1’s selection pressure also shows a 3-2 form: 1) reductive purifying, and 2) expansive divisive and directional. This dualist-triune topological aspect is explored further, later on in the paper.

The submissive agency implied in Figure 1 shows only a partial account (genomic affordance), and ignores cases where agents may drive resource shifts (phenotypic affordance). For example, humans often shift resources via agriculture, science, engineering, and the like, creating new adaptive options. Anthropocene artifacts (tools) allow us to materially alter resources such that humans occupy a cultural ecology as a main environment (Abundis, 2017). Those man-made environs hold many psycho-logical artifacts made into material forms (houses, cars, roads, ships, books, etc.), often as major adaptive gains – with new cultural/adaptive options still arising.

We once saw such ‘tool use’ as limited to humans, but we now accept that many agents use tools.

As such, to next allow for general agent driven resource shifts, classic agent responses of flight, freeze, and fight are added to Figure 2. Selection Vectors joined with agent responses present a general adaptive account for all agents, in every niche. This map of ‘adjacent possibilities’ also echoes Stuart Kauffman’s (2000) view in evolutionary biology. I call this composite evolutionary vista ‘Selection Dynamics’, as a constrained-contested space, occupied by all agents, at all times.

Despite the countervailing nature of agent enabled shifts, nothing here implies that agents ever become immune to selection pressure. Selection Dynamics merely differ material shifts driven by agents, versus those shifts driven by nature. For example, nothing in Figure 1 can explain the arrival of a thing like a ‘ballpoint pen’ upon the bare earth. Only agent behaviors help to explain the advent of such inventions, as is true for most human artifacts. Figure 2 thus maps a requiredbut-atypical starting point, for natural and man-made material shifts – as a ‘general adaptive model’.

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Selection Dynamics as Purifying, Divisive, and Directional selection pressure contra fight, freeze, or flight agent responses present a bounded-yet-ambiguous solution space, or ‘evolution by natural selection’. This ‘evolutionary system’ is bound by what comes before, while advances are defined ambiguously. For example, nature can present diverse (entropic) forces over varied timeframes. ‘Uncontrolled variables’ as happenstance can make scientifically predictive models rare. One facet may show clear annual patterns, seasons, and the like, where we easily derive useful habits (e.g., agriculture). But other facets, due to myriad seen and unseen variables, offer less insight. As such, how might we approach Selection Dynamics if we are to model evenfurther adaptive gains? Alternatively, we may wish to simply accept a level of intractable or noncomputable complexity when confronting happenstance (Kauffman, 2016).

Despite the seeming impossibility of the situation, chaos theory offers a way to model complexity in a bounded-yet-ambiguous role. For example, weather forecasts can easily name upper and lower temperature bounds that apply for years. But detailed weather forecasts (using chaos theory) rarely go beyond five days as they can take on a random appearance. Similarly, Lorenz attractors and bifurcation diagrams entail bounded-yet-ambiguous spaces (Figure 3).

Hence, chaos theory has a high intuitive appeal for modeling, as it essentially mirrors nature’s habits – but that appeal may be superficial. First, the above noted ‘limited visibility’ can dampen interest in chaos theory. Second, the formulas that typify chaos theory often seem simplistic, lacking detail on many presumably-involved variables. This leads some to see chaos theory as a ‘fact free science’ rather than a true empiric science (Smith, 1995). Third, within those formulas, the specific variable values that incite a bounded-yet-ambiguous result are limited. All this gives chaos theory a rather quirkish air, in contrast to the regular bounded-yet-ambiguous traits seen in Selection Dynamics.

Figure 3: Chaos Theory – three examples. Bounded-yet-ambiguous solution spaces arise in chaos theory. Lorenz ‘strange attractors’ (left), often called a butterfly effect, map a system’s sensitive dependence on initial conditions. A logistics equation (middle), developed to gauge population shifts, yields a bifurcation diagram. Bifurcations hold a self-similar aspect (red boxes: fractal symmetry) typical to chaos theory (Sardanyés, 2017). Mandelbrot sets (right) are perhaps the best known model of fractal symmetry. A generational view (red numbers) shows how further iterations of a Mandelbrot equation ‘reduce’ more fractal detail, toward a bounded limit (Fonseca, 2016). Sensitive dependence, bifurcations, self-similarity, and generational aspects in chaos theory also apply to Selection Dynamics, but in a more-empiric manner for the later.

Closer study of Selection Dynamics and chaos theory reveals a curious fact. Selection Dynamics hold a dualist-triune form, named in Figure 2’s note. This dualist-triune topology implies a type 3

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of fractal symmetry, akin to that seen in chaos theory. This ‘curious fact’ may point to a useful organizing principle for exploring Selection Dynamics in a computable or quasi-predictive role.

A fact based topology for Selection Dynamics, joined to a fact free (but highly appealing) mathematics in chaos theory, suggests a possible hybrid view may arise to allow the practical framing of selection events.

More research is needed to affirm such a ‘topological key’ but enough work is done already to see the approach may have some merit (see Appendix: Table 2; also Abundis, 2009). But to attempt a mathematical model, a firmer base is first needed. Still, as our present focus is adaptive cognition, we return to exploring the emergence of a human cultural ecology as a main environment.

MODEL DEVELOPMENT – Topological Evolution & Dualist-Triune Aesthetics Adaptive informatics are perforce expansive-and-reductive (Figure 1): forcing adaptive options, and selecting certain roles in a functional (non-statistical) manner, with occasional novel results.

Chaos theory has a similar dualist expansive-and-reductive role, as seen in Figure 3. Beyond this expansive-and-reductive link between Selection Dynamics and chaos theory, a dualist-triune topology is noted for Selection Dynamics in Figure 2. Thus, to explore an initial cultural ecology, these two aspects (chaos theory and fractal topology) are emphasized. Further, while this study targets modern humans, due to our evolutionary origins more-primitive facets are also explored.

As such, parts of this study apply to other (lower-order) agents. Lastly, a ‘dualist-triune topology’ returns us to a base style of calculation, namely, that of simple pattern recognition, except that we now target a ‘pattern for all patterns’ or a topological key. For example, biologist Gregory Bateson (1979) similarly asked ‘What is the pattern that connects [the cosmos]?’ in pursuing his work. The hope is that enough pattern regularity appears such that more exact views are later possible.

Following the above factors, a topological continuum as a ‘first degree ➔ fifth degree’ unfolding of adaptive cognition is now explored. This view of an evolving cultural ecology will help to differentiate ‘types of intelligence’ across a range of adaptive roles.

1D Survival – first degree logic To initiate this topological continuum, first degree logic (1D survival) is held by all resilient agents. ‘Failure’ means extinction, where non-resilient agents are ‘dispersed’ (Figure 4). Here, minimal survival also implies minimal sentience, a minimal ‘survival will’, and a limited range of passive-active adjacent behavioral possibilities. For example, within a surging selection force, agents that freeze (are constant or Set) succumb to entropic events and expire. But passive agents (as pliant or flexible roles) are forced into new niches, arriving bruised but secure.

Alternatively, an active flight instinct would drive agents to ‘single-mindedly’ (reflexively) flee hostile environs for adjacent spaces. Lastly, agents that freeze within preserved spaces (coincident flight) remain unmolested, in a passive role. Hence, a ‘will-full’ Fight response is unneeded for basic (1D) survival.

Figure 4: 1D Logic – minimal survival. Here, directional selection is expansive-and-reductive with agent freeze and flight roles mapped as ‘basic survival’. Freeze (left) yields extinction, freeze (middle) shows co-incident survival.

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Lastly, flight can be effectively passive or active, depending on the degree of agent ‘survival will’. Freeze and flight thus map a constant-passive-active continuum (a 3-2 form), that is expansive-and-reductive, as a minimal 1D case.

Constant, passive, and active roles thus define survival as ‘1D niche formation’. Also, as earthly environs can often shift, those minimal roles grow via increasingly diverse environs. This niche proliferation adds an expansive exaptive latency to 1D survival. The later passive-active-latent parsing of variable environs sets ab initio traits that drive a natural ‘branching’ in species (re Darwin’s Dilemma [Mayr, 1982], see also Figure 1’s noted divisive example).

As such, Earthly entropic forces drive all 1D shifts, while agents hold genetically set phenotypic traits (i.e., limited behavioral variability). Still, genomic variation ensures that some adaptivity occurs (via parental contribution, epigenetic activation, and gene mutation [a 3-2 form]). Also, even limited behavioral roles (freeze and flight) hold enough flex-ability (e.g., passive versus constant) such that adaptive behaviors can seem evident. But nothing here truly signals a ‘directed’ autonomous will with agents driving resource shifts. Instead, DNA meets all need for an ‘adaptive working memory’, as it re-productively expands across diverse environs in a functionally bounded-yet-ambiguous role.

2D Polemics – second degree ‘Fight’ Conversely, polemic logic signals an autonomous will, beyond 1D survival. ‘Willfulness’ arises as a directed 1D ‘fLight’ that later becomes 2D Fight (Figure 5). To Fight against Earthly entropy marks a type of entropic mimicry in agents, where behavioral (entropic) gains drive a ‘directed will’. Fighting shows in the literature variously as B. F. Skinner’s operant conditioning (a ‘drive to survive’), and Nietzsche’s will to power and power in adversity. This ‘Enhanced fLight’ contrasts with 1D’s more-submissive aspect, seen by Skinner as reflexive classic conditioning. Lastly, Fight opens a path to the advent of practical subject-object (S-O) modeling, as an early cognitive trait.

Figure 5: 2D Logic. ‘Fight’ to survive is shown as an agent’s ‘eventually directed’ niche expansion. 2D Fight starts as a reflexive (weak) 1D fLight, refined via more-gainful directions (upward ‘chalk’ arrow). A ‘gain’ may first appear as gap in otherwise overwhelming entropic forces. That ‘gainful gap’ then becomes an preferred/learned direction in fleeing survivors, in turn, inciting a ‘will-full survival behavior’ or directed cognition.

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As a fLight ➔ Fight example, many directions exist for fleeing a threat. A fLight’s direction is thus tied to certain outcomes, where ‘better directions’ offer survival. In a crude way, fleeing agents are therefore ‘forced to learn’ better directions, that frame a cognitive survival will. Any lapses in this ‘learned gainful behavior’ lead to eventual extinction. Further, more variety in the threats a survivor confronts, drives an equally greater cognitive will (Nietzsche’s power of adversity). This growing ‘variable willful-ness’ can be viewed as a type of proven survival skill (behavior), where richer survival experience ≈ more intelligence.

Polemic logic implies basic dia-metric (S-O) sentience, with a phenomenal or episodic ‘working memory’ as a derived record (meta-physics) of S-O (entropic) events. That ‘continuous narrative memory’ surpasses the more-discrete (coded) functioning of DNA as working memory. Later, the ensuing dia-metric (S-O) parsing and probing of environs grows to where predator-prey roles arise, as an evolutionary arms race – Van Valen’s (1973) Red Queen’s Race, ‘where it takes all the running you can do, just to keep in the same place’.

The cultural import of ‘logically diametric sentience’ varies. To start, fLight has little cultural weight as 1D agents are mostly pushed about, along with all other resources. Any agent differentiation and selection that occurs here is due to interacting ‘geographic and genomic variation’. But later diametric (2D) aspects vary widely. A reflexive diametric role may seem ‘emotional’, culturally reactive and paranoid (active fLight). A more-analytic diametric role seems opportunistic, cunning or predator-like (directed Fight). The key difference here is each agent’s skill in the use of working memory, as a central psycho-logical/cultural aspect. Lastly, polemic logic typifies many simple conceptual views still used by modern humans (e.g., good versus bad) as part of an ongoing cultural ecology.

Due to the innate ‘psycho-logical (analytic) separation’ of polemic logic, I label it an archetypal Sacred Wound – with (Mother) nature often urging an agent’s demise, contrasted with endless recreative deeds or Eden-like plenty (paradoxic creative destruction). This Sacred Wound psychologically reframes all demands innate to biological homeostasis, as Fight, while also instigating an early cultural ecology.

Polemic logic thus drives shifts to ‘new’ agent horizons, beyond what Earthly entropy alone allows. But nothing truly new (as with a ‘ballpoint pen’) arises here. Polemic logic only maps oppositions (i.e., differentiation of base cognitive artifacts) in an extant cosmos, including any cosmic ‘order for free’. It cannot explain how richer adaptive or evolutionary shifts occur.

‘Knowing a cosmos’ is vital to affording future agent innovation, but otherwise, purely polemic logic is creatively impotent – it is merely descriptive, and not explanatory.

3D Dialectic – creative reasoning Thus far – agent responses in relation to selection pressure (Selection Dynamics) convey a basic map of ‘adaptive cognition’. Even if this joint view is atypical, nothing posited so far should stir much debate. But missing in this analysis is the advent of ‘cognitive creativity’, where creativity is a controversial topic.

In contrast to 1D and 2D logic, 3D logic signals adaptive creativity as an ‘Enhanced Fight’ role (versus Fight as ‘Enhanced fLight’). But views beyond 1D and 2D logic can seem ‘non6

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scientific’, as they build on a psycho-logical role just named. Dialectic logic surpasses banal 1D and 2D flight, freeze, and fight. For example, science often targets what is ‘consistently measurable and repeatable’ as basic S-O parsing and probing. Anything beyond that 2D landscape is ‘too fuzzy’ for hard science. But a gap arises – as science is deeply creative – where a logically-consistent (2D) narrative cannot explain scientific creativity. Thus, we must look to dialectic 3D narratives to explain scientific and other agent creativity.

General creativity was long-ago seen as innately recombinant Hegelian dialectics: thesis + antithesis = synthesis (generative 3-2 conflicts). Nature similarly ‘re-creates’ via regular evolving recombination (1D logic). We might then ask ‘Are agents consciously or sub-consciously (re)creative?’ in realizing de facto recombinant syntheses; with creativity often seen as arising from sub-conscious roles (McCarthy, 2017). Thus, we might also say science is unconsciously creative in psycho-logically imagining a hypotheses, prior to empiric S-O tests. Lastly, recombinant adaptivity is needed to just remain upon an evolutionary landscape. As such, the need to model recombinant creativity (as re-creation) in Selection Dynamics is inescapable if we are to typify ‘general (survival) intelligence’.

Dialectic roles (beyond 1D ‘force-and-consequence’ and 2D ‘stimulus-and-response’) point to a 3D ‘stimulus + process = response’ shift. A 3D process is thus ‘key’ to differentiating creativity (adaptive Fight-ing styles). For example, genomic recombination entails parental contribution, gene activation, and gene mutation to produce adaptive novelty. Prior to that, sexual selection (a variable ‘base behavior’) between genetic parents further defines the nature of one’s offspring.

Later, breeding groups (variable pro-social behavior) also set a type of recombinant cultural ecology for all parents, in the competitive/co-ordinated nurturing of offspring. The specific Fight ‘process’ in each case differs, but each case still holds an innately recombinant vari-able process (re-creation). That process variability can be simplified to a generally variable ‘thesis + antithesis = synthesis’ of basic survival, or the equivalent of ‘life + threat = survival or extinction’.

Finally, a 2D ➔ 3D shift also marks a shift in memory type, from 2D episodic (S-O) memory to 3D ‘procedural (process) memory’. Again, a key difference here is an agent’s skill in the use of working memory. More recombinant flex-ability later affords tool invention (hand axes, etc.), which then underlies a ‘human revolt’ (Upper Paleolithic Revolution), as a species-wide cultural march that continues to this date (Abundis, 2017).

INTERIM ANALYSIS – A Fractal Evolutionary Landscape This study of a 1D ➔ 5D adaptive continuum next explores 4D and 5D logic. The psycho-logical role named as 2D polemics is extended further. But before entering these ‘fuzzier realms’, I synopsize what is covered thus far.

• General: Selection Dynamics (as force contra agency) present a map needed to model precognitive and cognitive adaptation – a vital reframing of ‘evolution by natural selection’.

• Creative: The map entails diverse re-creative roles as: forced happenstance, genomic variability, and phenotypic (behavior) flexibility. The map is thus innately dynamic, or entropic and ‘noisy’.

• Discrete: The above creativity is selectively differentiated in a discrete functional manner, and is both expansive and reductive (novelty ≈ ‘evolution by natural selection’).

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• Structure: A dualist-triune fractal trait seems to pervade the map. This recurrent ‘pattern of patterns’ (as a meta-meta-perspective) implies a computational approach may be possible. This innate 3D logic is shown as a 3-2 form or a 2-3 form, where . . . 3-2-3. . . conveys a continuum.

• Continuous: No true ‘material breaks’ exist in the map. Logical degrees seem evident more as a way of cognitively differentiating an increasingly (or continuously) diverse landscape.

• Culture: An agent’s active observing (conscious), passive observing (sub-conscious), or ‘blind’ engagement with shifting landscapes frames that agent’s general adaptive cognition. This all ‘sums’ to a cultural ecology for each agent and its peers. More-resilient agents can be said to ‘think most like nature’, evident as survival. Extinct agents can be said to have ‘thought less like nature’ (Figure 6).

These points only partially detail Selection Dynamics. For example, the model’s topological trait requires further geometric analysis (Figure 7). Still, as our focus is adaptive cognition, we return to exploring the emergence of a human cultural ecology as a main environment, and now study 4D and 5D logic.

Figure 6: Selection (survival/extinction) Dynamics. Following Figure 2, a cartoon tree shows evolutionary paths of surviving agents across time as a ‘positive space’. Blank (‘negative’) space then marks unfeasible or short-lived (i.e., no record) agent roles. Comparative analysis of this image, with images in Figure 3 for chaos theory, offers a cursory view of the core challenge in attempting a computational Selection Dynamics. It is unclear if these two vistas can be reconciled in a cohesive computational model.

Figure 7: Geometric Analysis. In geometry a point (far left, 1D) has ‘no dimensionality’ and a line (mid left, 2D) has one dimension of ‘length’. Conversely, 1D points are logically dualist, as an extant-or-extinct ‘existential meaning’.

‘One dimension’ 2D lines mark a dualist-triune as: 2 ends + 1 middle, or 1 line bisecting 2 spaces. ‘Two dimension’ 3D planes (width and length: middle) have a 2 face + 3 edge minimal dualist-triune form. ‘Three dimension’ 4D solids (right) add interiority/exteriority, for a dualist-triune logical network. This last shift marks a four-fold leap in representational space, from 2 to 8 faces (3D ➔ 4D), by adding one node. That ‘leap’ roughly mirrors the cultural import of the human ‘discovery of information’.

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4D Relational – discovery of ‘information’ Relational logic extends prior psycho-logical/cultural roles. Firm existential (1D), psychological (2D), and creative (3D) gains drive a growing sense of agent autonomy. Willful agency is set, not just in ‘more survival’, but in meeting other agents with varied aims (more 2D predator-prey/S-O testing). This ‘meeting of wills’ affords a new re-creative 3D process as 4D social-ability. Thus, a 3D ‘recombinant conflict’ is enlarged via ‘co-operation’ (Enhanced Dialectic). In allied agents, 4D co-ordination/co-operation incites a cultural surge as a recombinant marshaling of resources and agency. Such 4D gains then encourage agents to further explore shared adaptive cognition as ‘theory of mind’, ‘theory of self’, and ‘theory of theories’ types of differentiated thinking. This more advanced meta-physics pro-socially enlarges what is seen as ‘logically possible’ for allied agents.

The cultural surges start as co-ordinated energy-matter collection and trade (organized gathering/ hunting, agri-culture, transport, etc.), and then – wars (resource contests), written/printed text, wired/wireless messages, computers, the Internet, etc. The sharing of thoughts and energy-matter across space-time (concerted networking) expands one’s power of observation (sensorium) and engagement (behavior) beyond that of willful 2D agency, and well beyond what Earthly entropy alone allows. It also drives/requires a leap in an agent’s effective representational space, often seen as commerce and ‘distributed working memory’ (Figure 7, 4D, right).

Sharing of thoughts fortifies psychological-cultural roles by normalizing thoughts as objective (shared) knowledge. The allure of shared informational strategies comes to prevail as a cultural fundament, variously framed as science, education, religion, trade, etc. Also, study of a human psycho-logical fundament becomes more formal. A goal of ‘making conscious what is unconscious’ is stressed by Janet, Freud, Jung and others. This also marks a new memory type as 4D semantic memory (‘meaning’ attribution), beyond 2D episodic memory and 3D process memory. Thus, 4D informatics hold some information as innately more-meaningful than other information, which then affords a differentiation of innately social/re-creative archetypal ‘memes’ (Dawkins, 2006). Memes present a ‘device’ for faith-based systems of exchange that now typify much of our modern informational society.

Despite the cultural import of 4D logic, creativity is still perforce born of 3D individuals. Thus, an Enhanced (2D) Polemic also arises as ‘man against society’ – an enduring struggle to innovate in the face of growing cultural demands from an impressed ‘reality’. Our Sacred Wound dons a new mask, with humanity competing, not just against environs and other agents, but against itself. This signals a preemptive gain in human selective behavior, beyond natural selection, potentially fortifying the rate and robustness of human cultural evolution. It also increases the variety of existential angst (adversity) that humans experience, thus fracturing the possibility of peaceful or ‘complacent behavior’.

5D Full Sentience – the logic of ‘Play’ From the ‘practical paranoia’ of 2D, 3D, and 4D logic full sentience emerges. Full sentient 5D logic considers all entropic possibilities (1D ➔ 5D), but stresses the context of observed events.

Thus, a 5D context or ‘re-creative space’ is now the key differentiator – a new 3D process arises as an Enhanced (4D) Relational. 5D logic infers a pattern-of-patterns or meta-meta-perspectives 9

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needed for optimal adaptation. It actively explores agent pattern sense-ability (breadth and depth of memory), with an aim to discern further pattern details in S-O (and other) roles. This new relational focus variably (‘play-fully’) emphasizes ‘What is most effective-and-efficient’ for each situation, dispassionately exploring various options, which is then seen as driving innate wisdom.

A play-full 5D process (or acute re-creation) exhibits new memory flex-ability, and thus, is the most adaptive of all agent roles. For example, if an entropic event seems confusing, a simple logic is first tried as part of an agent’s en-cultured trail-and-error conduct (Abundis, 2017).

Successively more-complex views are then attempted until a subjectively good (for that agent) ‘descriptive-and-explanatory’ model arises, where more effective-ness and efficiency have survival value. Lastly, this ‘memory-intensive recombination’ – in advance of realized entropic/ behavioral events – implicates intensified cerebration and thus suggests a ‘more-intelligent’ agency.

Logic or Reasoning Modality

Memory/Cognitive Traits

1D Freeze (extinction, or co-incident Flight)

narrow materialist role (direct: specialist, Set)

1D Passive Flight

broadly materialist (embodied: generalist, flexible)

1D Active Flight

narrow behavioral will (instinctual, rigid)

1D pseudo Fight (directed-ish Flight)

broadening behavioral role (initial ideation)

2D Fight (polemic logic, S-O modeling)

narrow material & behavioral ideation (flexible)

3D early Play or pseudo Fight (dialectic logic)

recombinant ideation (more generative)

4D Relational Logic (personal and social)

generative complexity via sensual ideation

5D Full Sentience (contextual aesthetic)

maximum flexibility, complex and ambiguous

Table 1: Adaptive Continuum. A map of 1D ➔ 5D logic, with 1D shown in four granular steps to stress a natural continuum, where a similar granular view is likely at each level. While 1D implies minimal adaptivity and an initial narrow focus, and minimal energy demands, 5D logic implies maximal/general adaptivity, and maximal cerebration with high energy needs. This difference in ‘energy overhead’ (between 1D and 5D) may explain the evident cost of maintaining a human brain (uses 20% of caloric input, 15% of cardiac output, but entails only 2% of human body mass) in support of more-flexible/general adaptivity.

5D’s simultaneous inter-operation of 1D, 2D, 3D, and 4D traits can have a mystical air and seem chaotic, essentially mirroring nature’s happenstance. Synchronous recombination as ‘engineered serendipity’, or natural multi-state computing, marks a new cultural aspect. 5D ‘logic’ embraces logical in-constance, ambiguity, and plasticity (i.e., maximal curiosity) in search of optimal adaptivity. It thus has no consistent narrative, akin to a Zen koan, and is thus unlike prior logical levels. Further, not all 5D agents are equal as each agent is still innately (uniquely) informed by the breadth and depth of 2D S-O memories and 3D creativity (re ‘the individual’) that ultimately inform every agent’s action.

Neurologically, 5D logic implies growing neural plasticity, leading to cognitive plasticity, thus driving informational and behavioral plasticity. It conveys another shift in neural order to what I 10

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call supra-semantic memory, implying maximal neural interconnections. High-functioning full sentience appears as ‘being in the zone’, an intuitive animal-like think-feeling, seen in elite athletes, artists, politicians, researchers, and the like. The essence of this role is that an agent is selflessly (psychologically) given over, wholly, to a ‘becoming-ness’ before them, and is thus maximally engaged with a given context.

As a human mythos, we reference notable models as Ulysses, Jesus, a championship team, Bach, Picasso, Einstein, and on. Joseph Campbell’s Hero’s Journey is the standard universal archetype in 5D logic. This memetic mythos also shows as the Uroboros, or a paradoxical sage/savant, a master-student-servant of Nature, the Tao, Nietzsche’s Übermensch, and The Dancing Wu Li Masters (Zukav, 1982).

CONCLUSION This 1D ➔ 5D analysis asserts that Earth’s entropic unfolding affords, and thus compels, more entropic/re-creative processes and processing in agents. Agents may ‘adaptively match’ that Earthly entropy, or fail. The recombinant vari-ability innate to this shifting landscape does not argue one role surpasses another. It argues only that agents fluidly embracing flex-ability within dynamic or complex environs will prevail, and that stable/simple environs will reward specialist or Set roles. But between those two roles a wide continuum of adaptive or intelligent possibilities exist – shown here as a 1D ➔ 5D adaptive/entropic continuum – experienced as ‘adaptive cognition’ or an evolving ‘cultural ecology’.

Within this study, three key points arise: 1) The naming of a base structural psychology (memory processing) for differentiating ‘types of intelligence’ across a range of adaptive roles. 2) A continuous dualist-triune fractal trait in those psychological, and other behavioral and material, roles – therein implying universality or generalizability. 3) A scientific core (information theory, evolutionary theory, and chaos theory) underlies the model’s framing. Consequently: A) In a backward-looking way, if this study’s approach is formalized into a model, that model can be gauged against an historic scientific view. B) In a forward-looking way, if that model is proven valid, it could be used in a further-extensible or ‘super intelligent’ adaptive manner.

Much work remains to be done before such a model ultimately arises. But, at the least, this study maps one likely path toward realizing such a model of ‘adaptive cognition’.

APPENDIX Dualist-triune fractal fundaments are explored further in two complementary papers.

A General Theory of Meaning (Abundis, 2016) details the nature of meaning-full information as: 1) direct functional meaning, and as 2) discrete and temporal adaptive meaning.

Next, Natural Multi-State Computing (Abundis, 2017) shows various dualist-triune roles as: A) functional levers with a: i) fixed Fulcrum, and a ii) variable Effort and Load; B) entropic landscapes entailing: i) non-adaptive happenstance and signal entropy; and ii) adaptive interpretive entropy; C) where interpretive entropy has: i) innate value and order entropy; and ii) disruptive element entropy.

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Beyond these examples, and the examples detailed earlier, additional general examples are shown in various videos posted online (Abundis, 2009). Lastly, Table 2 gives a detailed account of the Standard Model in Physics and space-time as dualist-triune forms.

Table 1: The Standard Model in Physics – further dualist-triune examples.

REFERENCES 1. Abundis, M. (2009). This note refers to any of several videos available at: < https:// vimeo.com/evolv/>.

2. Abundis, M. (2016). A general theory of meaning. Issuu.com [Online]. Available at: <https:// issuu.com/mabundis/docs/lgcn.fin.4.15> [Accessed 1 December 2016].

3. Abundis, M. (2017). Natural multi-state computing – engineering evolution: simple machines and beyond. Issuu.com [Online]. Available at: <https://issuu.com/mabundis/docs/ multistate> [Accessed 1 February 2017].

4. Bateson, G. (1979). Mind and nature: A necessary unity. New York, NY: Dutton.

5. Dawkins, R. (2006). The selfish gene (3rd ed.). New York, NY: Oxford University Press.

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6. Fonseca, R. (2017). Random Themes, The Mandelbrot Set [Online]. Available at: <http:// renatofonseca.net/mandelbrotset.php> [Accessed on 2 May 2017].

7. Kauffman, S. A. (2000). Investigations. Oxford, UK: Oxford University Press.

8. Kauffman, S. A. (2016). Stuart Kaufmann | Full lecture | KLI, 16 June 2016. Konrad Lorenz Institute (KLI), Klosterneuburg, Austria [online]. Available at <https://www.youtube.com/ watch?v=EWo7-azGHic> [Accessed 1 January 2017].

9. Mayr, Ernst (1982). The Growth of Biological Thought: Diversity, Evolution, and Inheritance. Cambridge, MA: Belknap Press of Harvard University Press.

10. McCarthy, C. (2017). The Kekulé Problem, Nautilus, issue 047. [Online]. Available at <http://nautil.us/issue/47/consciousness/the-kekul-problem> [Accessed on 25 April 2017].

11. Sardanyés, J. (2017). Chaos, Complex Systems Lab, Universitat Pompeu Fabra, Barcelona SPAIN [Online]. Available at: <http://complex.upf.es/~josep/Chaos.html> [Accessed on 2 May 2017].

12. Shannon, C. (1948). ‘A mathematical theory of communication’, Bell System Technical Journal, 27, pp. 379-423 & 623-656, July & October, 1948.

13. Smith, J. M. (1995). Life at the edge of chaos?, The New York Review of Books, 42(2), 28-30.

14. Sprott, J. C. (2009) Nonlinear Dynamics, Psychology, and Life Sciences 13, 271-278. http:// sprott.physics.wisc.edu/pubs/paper327.htm 15. Tomasello, M. (2014). ‘What Makes Humans Different Than Any Other Species’, Scientific American Volume 311, Issue 3. [online] Available at: <http://www.scientificamerican.com/ article/what-makes-humans-different-than-any-other-species> [Accessed 5 May 2015].

16. Van Valen, L. (1973). ‘A new evolutionary law’. Evolutionary Theory 1: 1-30, Dept. of Ecology & Evolution, University of Chicago. Chicago, IL: University of Chicago, etc.

17. Zukav, G. (1982). The dancing Wu Li masters: An overview of the new physics. Flamingo.

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