What the source specifies
A twelve-panel visual synthesis places consciousness, recursive repair, unified learning, value-directed evolution, federation, harmonic knowledge, plasticity, action scoring, projection and applied ranking together.
Equations and variants
Every visible complete mathematical relation has a linked record, including parameter definitions, constraints, decorative corner equations and repeated formula variants. The original images and full reading copies are available through the source links.
Source findings and limits
Twelve numbered panels plus a supporting-formulas strip were inspected. This generated poster is a synthesis artifact, not an exhaustive proof that every historical project equation is present.
Several tiny symbols are degraded or internally inconsistent. They are recorded as unclear instead of repaired from expectation.
The consciousness, AGI and performance captions describe intended interpretations. The graphic itself contains no runtime, training or benchmark evidence.
Equations in this build
49 linked mathematical records. Each opens its notation, interpretation and source.
Atlas consciousness integral with ambiguous Φ grouping
The panel combines an agency coupling, coherence, an information-related factor and a saturating knowledge-gradient magnitude inside a time integral. The printed numerator…
Agency–experience–substrate coupling
The source defines a coupling term as a function of agency, an experiential lattice and substrate scale. It specifies which quantities are intended to matter, but leaves the…
Rhiannon constrained repair objective
Select a candidate program that minimizes residual bug loss plus a weighted cost of changing the original program. The displayed compile, type, test and safety predicates restrict…
Rhiannon Compile acceptance condition
The poster uses a binary acceptance predicate requiring that the candidate compiles. It is one of four conditions restricting the repair search.
Rhiannon TypeSafe acceptance condition
The poster uses a binary acceptance predicate requiring that the candidate passes the chosen type check. It is one of four conditions restricting the repair search.
Rhiannon Tests acceptance condition
The poster uses a binary acceptance predicate requiring that the candidate passes the specified diagnostics and tests. It is one of four conditions restricting the repair search.
Rhiannon Safety acceptance condition
The poster uses a binary acceptance predicate requiring that the candidate passes the specified safety check. It is one of four conditions restricting the repair search.
Rhiannon repeated program repair
Apply the repair operator R to the current program and current diagnostics to obtain the next program. Repeating this interface describes an iterative repair process; it does not…
Atlas self-extension sum with unclear lower index
The panel sums self-composed stage operators, but its small summation lower index is degraded and does not clearly bind the k in the summand. The larger Rhiannon poster prints an…
Rhiannon seventh-stage self-composition
The seventh stage operator is applied twice to the input. This names a repeated transformation; it does not by itself provide the stage function or establish an implemented…
Unified learning state dynamics
The state velocity is decomposed into four operators: diffusion D spreads activation, nonlinear emergence N describes interactions, external force F represents inputs or pressure,…
Epona / Echad discrete loss–value update
The next state combines a step opposite the loss gradient with a step in the direction of the value gradient. The learning rate η_t scales the loss term, while λ independently…
Epona / Echad F-minus-value gradient flow
The velocity follows the negative gradient of a composite potential F − λV. Where F acts as a loss, descending that composite potential trades off loss reduction against value…
Epona / Echad L-minus-value gradient flow
The continuous state moves downhill on L − λV. Expanding the gradient gives −∇L + λ∇V when λ is independent of state. This is the continuous counterpart of the poster’s goal of…
Reshit surprise–uncertainty–value objective
The chosen state or action is intended to minimize surprise plus uncertainty minus value. Increasing the value term can lower the objective, while larger surprise or uncertainty…
Habrit seven-family binding interface
The source proposes a resolver that binds seven named family representations into a federation state B. Superscript 16 identifies the poster’s family/lattice notation; the image…
Habrit state tuple
The proposed system state groups ten named components into a tuple. This lists the representation’s fields without defining how they are updated or how their meanings align with…
Sixteen-domain family-lattice label
The equality assigns a descriptive name to H^16. It identifies an intended sixteen-domain recursive family organization; it is not a numerical identity or a measurement of AGI.
Habrit illustrative weighted total
The two printed contributions sum to 10.605, which rounds to 10.6 at one decimal place. The poster does not identify the unit or empirical origin of either contribution.
Atlas golden-ratio basis with equal-frequency branches
Add sine and cosine waves at the same frequency scaled by φ^k and σ_i. The image uses a k-indexed basis function and an i-indexed scale; no relation between those indices is…
Atlas harmonic knowledge reconstruction
Map a query through h, evaluate harmonic basis functions at that representation, then form a coefficient-weighted sum. The displayed sum omits an explicit range; the coefficients…
Poster timing- and coherence-weighted plasticity
A connection-weight change is scaled by a learning rate, a coherence-related factor, a signed difference between pre- and post-synaptic times, and an exponential timing factor.…
Federation objective component summary
The objective rewards utility, semantic progress, goal progress and novelty, then subtracts penalties, risk and resource use. This is a scoring design whose behavior depends on…
Federation action objective
Score action a in state s using four benefits and five penalties or costs. Repetition depends on the action, while stall and fallback terms are written as state-dependent. The…
Semantic progress weighted score
Combine state change, produced artifacts, information gain and goal progress with four weights. The terms indicate what counts as progress, but neither the image nor this formula…
Logarithmic action repetition penalty
Penalize repeated use of an action using the logarithm of one plus its count. The penalty is zero at count zero and grows sublinearly for nonnegative counts when λ_rep is…
Linear stall-cycle penalty
Multiply the number of stalled cycles by a per-cycle penalty. The result increases linearly if λ_stall is positive.
Linear fallback penalty
Multiply fallback count by a weight to discourage repeated reliance on fallback behavior.
Substrate-to-experience mapping interface
A mapping Π takes substrate state S to a reduced experiential state X. The arrow names the intended direction of representation transfer without specifying an algorithm.
Atlas 23-million to 5,000 projection signature
The source labels a transformation from a twenty-three-million-scale substrate representation to a five-thousand-component experience representation. The symbols S and X here…
Atlas regional mean with unclear summation index
The visible denominator and membership condition indicate a regional average of substrate entries. The small summation index itself cannot be read reliably, so the transcript…
Atlas adaptive marketing-weight update
Add a performance-driven adjustment to the logarithms of current weights and normalize the result with softmax. For positive weights this has the multiplicative form of…
Marketing performance-change vector
Collect seven changes into a signal vector. Click-through rate, conversion rate, revenue per click and engagement enter positively; cost per click, cost per acquisition and bounce…
Click-through rate
The share of impressions that receive clicks; it requires a nonzero impression count. Defines the named performance ratio used or referenced in the framework.
Cost per click
Average spend per click over a common reporting window; it requires nonzero clicks. Defines the named performance ratio used or referenced in the framework.
Cost per thousand impressions
Spend scaled to one thousand impressions; it requires nonzero impressions. Defines the named performance ratio used or referenced in the framework.
Cost per acquisition
Average spend per recorded acquisition; acquisition criteria and attribution window must be specified. Defines the named performance ratio used or referenced in the framework.
Conversion rate
The ratio of conversions to visitors in the selected population. The poster uses visitors rather than sessions or clicks. Defines the named performance ratio used or referenced…
Revenue per click
Revenue divided by clicks over a consistent attribution interval; zero-click periods require a handling rule. Defines the named performance ratio used or referenced in the…
Missionmatch candidate weighted score
Rank candidates with six feature weights summing to one. Clearance and skills each receive a quarter of the total weight, certifications and customer experience each receive…
Exponentially decaying learning rate
Multiply the current learning rate by an exponential factor determined by loss. If β and L_t are nonnegative, the learning rate cannot increase under this rule, and larger losses…
Atlas memory-gradient update with unclear subscript
The printed memory state receives an additive gradient-dependent increment. The variable with respect to which the gradient is taken is not reliably legible in the small source…
Domain recurrent state through Φ
Combine a domain-specific transformation of the current state with a scaled previous domain state, then apply Φ. This is a recurrent update whose memory strength is influenced by…
Unity-centered proximity score
Assign a score of one at z=1 and decrease it as the absolute distance from one increases. For finite real z the score lies in (0,1]. It is a simple proximity function rather than…
Hub-and-six-domain coherence average
Average one hub score and six domain scores with equal weight. The adjacent Unified AGI diagram explicitly labels six domains plus a hub, which explains the denominator seven.
Saturating knowledge-gradient magnitude
Map a nonnegative gradient magnitude r to r/(1+r). It is zero at r=0, increases monotonically, and approaches one for large r, limiting the influence of very large gradients.
Softmax action policy
Convert action values into a distribution over actions by applying softmax across the available action set. Actions with larger values receive larger probability, while finite…
One-step Q-learning update
Move the current action-value estimate toward the observed reward plus the discounted best next-state value. The bracket is the temporal-difference error, and α controls how much…
G-family order label
The source pairs a G-family superscript with x=256. No expansion, operational definition or relationship to the nearby G^16 notation is given, so the expression is preserved as a…