docs: the 12 duplicates deleted; README rewritten to the system as it is
Captain Bob's rulings, 2026-10-14: "delete" -- the duplicates listed in DELETE-CANDIDATES.md are removed (the list stays as the record; the formal tier's provenance comments repointed at the maintained copies) -- and "rewrite" the README: v2.1.0, the Tripod as Hera/Artemis/Hestia, kernel-Hermes, identities on thumbdrives, the corrected ACL overhead, 1052-test POST and the current parity line, keyboards and storage, board images carrying both systems and how to switch, and docs/README.md as the way in. The book is left as it is, to be reworked later. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This commit is contained in:
rajames
co-authored by
Claude Opus 5.5
Claude Opus 5.5
parent
776c89457e
commit
f8fbc37698
@@ -1,528 +0,0 @@
|
||||
<!-- Moved from docs/reference/ONTOLOGY.md to docs/working/papers/ONTOLOGY.md on 2026-06-16 (docs reorg Phase 2) -->
|
||||
# StarForth Ontology, Taxonomy, and Lexicon
|
||||
|
||||
**Version**: 1.0
|
||||
**Date**: 2025-12-13
|
||||
**Purpose**: Formal conceptual framework for precise academic discourse
|
||||
|
||||
---
|
||||
|
||||
## I. ONTOLOGY (Conceptual Framework)
|
||||
|
||||
### 1.1 Core Concepts
|
||||
|
||||
```
|
||||
StarForth Adaptive Runtime System
|
||||
├── Execution Metrics
|
||||
│ ├── Execution Frequency (primary measurable)
|
||||
│ ├── Temporal Decay (derived quantity)
|
||||
│ └── Transition Probability (derived quantity)
|
||||
├── Adaptive Mechanisms
|
||||
│ ├── Frequency-Based Caching
|
||||
│ ├── Window-Based Inference
|
||||
│ └── Decay-Based Pruning
|
||||
├── Convergence Properties
|
||||
│ ├── Deterministic Behavior
|
||||
│ ├── Steady-State Equilibrium
|
||||
│ └── Variance Reduction
|
||||
└── Analysis Frameworks
|
||||
├── Dynamical Systems View
|
||||
├── Statistical Inference View
|
||||
└── Control Theory View
|
||||
```
|
||||
|
||||
### 1.2 Conceptual Relationships
|
||||
|
||||
```
|
||||
METAPHORICAL MAPPING (Thermodynamics → Execution):
|
||||
Thermal Energy ≈ Execution Frequency (measurable count)
|
||||
Heat Dissipation ≈ Exponential Decay (time-based reduction)
|
||||
Thermal Equilibrium ≈ Steady-State Convergence (stable metrics)
|
||||
Temperature ≈ Normalized Frequency Rank
|
||||
Cooling Rate ≈ Decay Coefficient (λ)
|
||||
|
||||
LITERAL IMPLEMENTATIONS (No Metaphor):
|
||||
Frequency Counter → Integer increment on execution
|
||||
Decay Function → f(t) = f₀ * e^(-λt)
|
||||
Hot-Words Cache → Top-K frequency-sorted entries
|
||||
Rolling Window → Circular buffer of execution records
|
||||
ANOVA Test → Statistical variance analysis (Levene's test)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## II. TAXONOMY (Hierarchical Classification)
|
||||
|
||||
### 2.1 Adaptive Runtime Components
|
||||
|
||||
```
|
||||
1. Measurement Layer
|
||||
1.1 Execution Frequency Tracking
|
||||
└── Dictionary Entry Counter (per-word increment)
|
||||
1.2 Temporal Recording
|
||||
└── Rolling Window of Truth (circular buffer)
|
||||
1.3 Transition Tracking
|
||||
└── Word-to-Word Transition Matrix
|
||||
|
||||
2. Transformation Layer
|
||||
2.1 Decay Models
|
||||
2.1.1 Linear Decay (Loop #3)
|
||||
└── Δf = -k * Δt
|
||||
2.1.2 Exponential Decay (Loop #6 Inference)
|
||||
└── f(t) = f₀ * e^(-λt)
|
||||
2.2 Normalization
|
||||
2.2.1 Frequency Ranking
|
||||
2.2.2 Probability Calculation
|
||||
|
||||
3. Inference Layer
|
||||
3.1 Window Width Inference (Loop #5)
|
||||
3.1.1 Variance Analysis (Levene's Test)
|
||||
3.1.2 Binary Search (Variance Inflection Point)
|
||||
3.2 Decay Slope Inference (Loop #6)
|
||||
3.2.1 Exponential Regression
|
||||
3.2.2 Least Squares Fitting
|
||||
|
||||
4. Actuation Layer
|
||||
4.1 Hot-Words Cache (Loop #1)
|
||||
4.1.1 Frequency-Based Sorting
|
||||
4.1.2 Top-K Selection
|
||||
4.1.3 Fast-Path Dictionary Lookup
|
||||
4.2 Speculative Execution (Loop #4)
|
||||
4.2.1 Transition Probability Calculation
|
||||
4.2.2 Prefetch Decision
|
||||
|
||||
5. Coordination Layer
|
||||
5.1 Heartbeat System (Loop #7)
|
||||
5.1.1 Time-Driven Tick Generation
|
||||
5.1.2 Loop Orchestration
|
||||
5.1.3 Adaptive Tick Rate
|
||||
```
|
||||
|
||||
### 2.2 Feedback Loop Taxonomy
|
||||
|
||||
```
|
||||
Feedback Loops (7 Total)
|
||||
├── Positive Loops (Amplifying)
|
||||
│ ├── Loop #1: Execution Heat Tracking
|
||||
│ │ └── More executions → Higher rank → More cache hits → More executions
|
||||
│ └── Loop #4: Pipelining Metrics
|
||||
│ └── More transitions → Better prediction → More prefetch hits
|
||||
├── Negative Loops (Stabilizing)
|
||||
│ ├── Loop #3: Linear Decay
|
||||
│ │ └── High frequency → Faster decay → Lower frequency → Slower decay
|
||||
│ ├── Loop #5: Window Width Inference
|
||||
│ │ └── High variance → Smaller window → Lower variance
|
||||
│ └── Loop #6: Decay Slope Inference
|
||||
│ └── Unstable metrics → Steeper decay → Faster stabilization
|
||||
├── Neutral Loops (Monitoring)
|
||||
│ └── Loop #2: Rolling Window History
|
||||
│ └── Execution occurs → Record in window → Historical data available
|
||||
└── Meta-Loop (Adaptive Coordination)
|
||||
└── Loop #7: Adaptive Heartbeat
|
||||
└── Stable system → Slower ticks → Less overhead
|
||||
```
|
||||
|
||||
### 2.3 Convergence Taxonomy
|
||||
|
||||
```
|
||||
Convergence Properties
|
||||
├── Determinism
|
||||
│ ├── Algorithmic Determinism (same inputs → same outputs)
|
||||
│ ├── Temporal Determinism (time-invariant steady state)
|
||||
│ └── Statistical Determinism (0% variance)
|
||||
├── Steady-State Characteristics
|
||||
│ ├── Fixed Point (attractors in phase space)
|
||||
│ ├── Periodic Behavior (limit cycles)
|
||||
│ └── Chaotic Behavior (sensitive dependence - avoided)
|
||||
└── Variance Metrics
|
||||
├── Inter-Run Variance (across multiple executions)
|
||||
├── Intra-Run Variance (within single execution)
|
||||
└── Temporal Variance (across time windows)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## III. LEXICON (Precise Definitions)
|
||||
|
||||
### 3.1 Core Terms (Alphabetical)
|
||||
|
||||
**Adaptive Heartbeat**
|
||||
*Definition*: Time-driven coordination mechanism that orchestrates feedback loop execution at dynamically-adjusted intervals.
|
||||
*Formal*: Thread T executing `vm_tick()` at frequency f_tick, where f_tick ∈ [f_min, f_max] adapts based on system stability.
|
||||
*Measurement*: Tick period in nanoseconds (configurable: HEARTBEAT_TICK_NS).
|
||||
*Category*: Coordination mechanism.
|
||||
|
||||
**Attractor**
|
||||
*Definition*: Stable equilibrium point or region in phase space toward which execution trajectories converge.
|
||||
*Formal*: Fixed point x* where F(x*) = x* for dynamical system x_{t+1} = F(x_t).
|
||||
*Measurement*: Coordinates in (window_size, decay_slope, variance) space.
|
||||
*Category*: Dynamical systems concept.
|
||||
|
||||
**Decay Coefficient (λ)**
|
||||
*Definition*: Rate parameter controlling exponential reduction in execution frequency over time.
|
||||
*Formal*: λ in f(t) = f₀ * e^(-λt), units of [1/time].
|
||||
*Measurement*: Derived via exponential regression; stored as Q48.16 fixed-point.
|
||||
*Category*: Transformation parameter.
|
||||
|
||||
**Deterministic Convergence**
|
||||
*Definition*: Property whereby repeated executions of identical workloads produce statistically indistinguishable steady-state metrics.
|
||||
*Formal*: ∀ executions i,j: |metric_i - metric_j| / σ < ε, where ε → 0 as t → ∞.
|
||||
*Measurement*: Coefficient of variation CV = σ/μ → 0%.
|
||||
*Category*: Convergence property.
|
||||
|
||||
**Execution Frequency**
|
||||
*Definition*: Count of times a dictionary entry has been executed since VM initialization, optionally adjusted by decay.
|
||||
*Formal*: f = Σ executions - ∫ decay(t) dt.
|
||||
*Measurement*: Unsigned 64-bit integer (`uint64_t execution_heat`).
|
||||
*Category*: Primary measurable quantity.
|
||||
*Note*: "Heat" is metaphorical naming; actual quantity is frequency.
|
||||
|
||||
**Exponential Decay**
|
||||
*Definition*: Mathematical function modeling reduction in execution frequency proportional to current value.
|
||||
*Formal*: f(t) = f₀ * e^(-λt), where f₀ is initial frequency.
|
||||
*Measurement*: Applied periodically by heartbeat system.
|
||||
*Category*: Transformation function.
|
||||
*Metaphor*: Analogous to radioactive decay or thermal dissipation.
|
||||
|
||||
**Hot-Words Cache**
|
||||
*Definition*: Fixed-size array storing pointers to the K most frequently executed dictionary entries for O(1) lookup acceleration.
|
||||
*Formal*: Cache C = {e_1, e_2, ..., e_K} where f(e_i) ≥ f(e_{i+1}) ∀ i.
|
||||
*Measurement*: Cache size K (configurable: HOTWORDS_CACHE_SIZE).
|
||||
*Category*: Frequency-based optimization.
|
||||
|
||||
**Levene's Test**
|
||||
*Definition*: Non-parametric statistical test for homogeneity of variance across groups.
|
||||
*Formal*: H₀: σ₁² = σ₂² = ... = σ_k² (variances equal).
|
||||
*Measurement*: F-statistic with p-value threshold (typically 0.05).
|
||||
*Category*: Statistical inference method.
|
||||
*Application*: Used to detect variance changes when adjusting window size.
|
||||
|
||||
**Phase Space**
|
||||
*Definition*: Multi-dimensional coordinate system where each axis represents a system state variable.
|
||||
*Formal*: Space S = {(w, λ, σ²) | w ∈ ℕ, λ ∈ ℝ⁺, σ² ∈ ℝ⁺}.
|
||||
*Measurement*: Coordinates: (window_size, decay_slope_Q48, variance_Q48).
|
||||
*Category*: Dynamical systems representation.
|
||||
|
||||
**Rolling Window of Truth**
|
||||
*Definition*: Circular buffer recording recent execution history for deterministic metric seeding.
|
||||
*Formal*: Buffer B[i] = word_id at execution event i mod |B|.
|
||||
*Measurement*: Buffer size (configurable: ROLLING_WINDOW_SIZE = 4096).
|
||||
*Category*: Temporal recording mechanism.
|
||||
*Purpose*: Ensures identical initial conditions for reproducibility.
|
||||
|
||||
**Steady-State Equilibrium**
|
||||
*Definition*: Condition where adaptive system metrics stabilize within bounded oscillation.
|
||||
*Formal*: ∃ t_0: ∀ t > t_0, |x(t) - x*| < δ for small δ.
|
||||
*Measurement*: Variance CV < 0.1% over 1000-tick window.
|
||||
*Category*: Convergence property.
|
||||
*Metaphor*: Analogous to thermodynamic equilibrium.
|
||||
|
||||
**Thermodynamic Metaphor**
|
||||
*Definition*: Conceptual mapping between thermodynamic quantities and execution metrics.
|
||||
*Mapping*:
|
||||
- Heat ↔ Execution Frequency
|
||||
- Temperature ↔ Normalized Rank
|
||||
- Cooling ↔ Exponential Decay
|
||||
- Equilibrium ↔ Steady State
|
||||
*Category*: Conceptual framework (not literal physics).
|
||||
*Warning*: Must qualify as metaphor in academic writing.
|
||||
|
||||
**Transition Probability**
|
||||
*Definition*: Conditional probability that word B is executed immediately after word A.
|
||||
*Formal*: P(B|A) = count(A→B) / count(A).
|
||||
*Measurement*: Stored as Q48.16 fixed-point in transition matrix.
|
||||
*Category*: Derived metric for speculative execution.
|
||||
|
||||
**Variance Inflection Point**
|
||||
*Definition*: Window size w* where variance begins to increase when window shrinks below w*.
|
||||
*Formal*: w* = arg min_w { Var(w) | w < w_current }.
|
||||
*Measurement*: Found via binary search with Levene's test.
|
||||
*Category*: Inference target.
|
||||
*Purpose*: Optimal window size for stable metrics.
|
||||
|
||||
**Word Transition**
|
||||
*Definition*: Sequential execution of word B immediately following word A in threaded code.
|
||||
*Formal*: Event (A, B, t) where A executes at time t and B at time t+ε.
|
||||
*Measurement*: Recorded in transition_metrics.history[] circular buffer.
|
||||
*Category*: Execution event.
|
||||
|
||||
---
|
||||
|
||||
### 3.2 Avoid/Deprecated Terms
|
||||
|
||||
| ❌ Avoid | ✅ Use Instead | Reason |
|
||||
|---------|---------------|--------|
|
||||
| "Physics-based" | "Thermodynamically-inspired metaphor" | Not literal physics |
|
||||
| "Execution heat" (in formal writing) | "Execution frequency with decay" | "Heat" is metaphorical |
|
||||
| "Temperature" | "Normalized frequency rank" | No actual thermal quantity |
|
||||
| "Quantum-inspired" | N/A | No quantum mechanics involved |
|
||||
| "AI-driven" | "Statistically-inferred" | No neural networks or ML |
|
||||
| "Learning" | "Adaptive inference" | Not machine learning |
|
||||
| "Training" | "Convergence to steady state" | Not supervised learning |
|
||||
|
||||
---
|
||||
|
||||
## IV. MATHEMATICAL FORMALISM
|
||||
|
||||
### 4.1 Execution Frequency Evolution
|
||||
|
||||
**Discrete-time update**:
|
||||
```
|
||||
f[t+1] = f[t] + Δexec[t] - Δdecay[t]
|
||||
|
||||
where:
|
||||
Δexec[t] = 1 if word executed at tick t, else 0
|
||||
Δdecay[t] = λ * f[t] * Δt (exponential decay approximation)
|
||||
```
|
||||
|
||||
**Continuous-time model**:
|
||||
```
|
||||
df/dt = r(t) - λf(t)
|
||||
|
||||
where:
|
||||
r(t) = execution rate [executions/second]
|
||||
λ = decay coefficient [1/second]
|
||||
|
||||
Solution:
|
||||
f(t) = e^(-λt) * [f₀ + ∫₀ᵗ r(τ)e^(λτ) dτ]
|
||||
```
|
||||
|
||||
### 4.2 Hot-Words Cache Selection
|
||||
|
||||
**Cache membership criterion**:
|
||||
```
|
||||
e ∈ Cache ⟺ rank(e) ≤ K
|
||||
|
||||
where:
|
||||
rank(e) = |{e' ∈ Dictionary : f(e') > f(e)}| + 1
|
||||
K = cache size (constant)
|
||||
```
|
||||
|
||||
### 4.3 Window Width Inference
|
||||
|
||||
**Objective function**:
|
||||
```
|
||||
w* = arg min { Var(w) : w ∈ [w_min, w_current] }
|
||||
|
||||
Subject to:
|
||||
Levene(w, w_current) → F-statistic
|
||||
p-value(F) < α (typically α = 0.05)
|
||||
```
|
||||
|
||||
### 4.4 Decay Slope Inference
|
||||
|
||||
**Exponential regression**:
|
||||
```
|
||||
Given: {(t_i, f_i)}_{i=1}^N from rolling window
|
||||
|
||||
Model: f(t) = f₀ * e^(-λt)
|
||||
|
||||
Log-transform: ln(f) = ln(f₀) - λt
|
||||
|
||||
Least squares:
|
||||
λ* = arg min Σ [ln(f_i) - (ln(f₀) - λt_i)]²
|
||||
```
|
||||
|
||||
### 4.5 Transition Probability
|
||||
|
||||
**Maximum likelihood estimate**:
|
||||
```
|
||||
P(B|A) = count(A→B) / count(A)
|
||||
|
||||
where:
|
||||
count(A→B) = # times B executed immediately after A
|
||||
count(A) = # times A executed
|
||||
```
|
||||
|
||||
### 4.6 Convergence Metric
|
||||
|
||||
**Coefficient of Variation**:
|
||||
```
|
||||
CV = σ / μ
|
||||
|
||||
where:
|
||||
σ = √(Var[metric]) = standard deviation
|
||||
μ = E[metric] = mean
|
||||
|
||||
Convergence achieved when: CV → 0
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## V. RELATIONSHIP DIAGRAM
|
||||
|
||||
### 5.1 Component Dependencies
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────────────────────────┐
|
||||
│ Execution Event │
|
||||
│ (word executed) │
|
||||
└──────────────────────┬──────────────────────────────────────┘
|
||||
│
|
||||
┌───────────┴───────────┐
|
||||
│ │
|
||||
▼ ▼
|
||||
┌────────────────┐ ┌──────────────────┐
|
||||
│ Frequency │ │ Rolling Window │
|
||||
│ Increment │ │ Recording │
|
||||
│ (Loop #1) │ │ (Loop #2) │
|
||||
└────────┬───────┘ └─────────┬────────┘
|
||||
│ │
|
||||
│ │
|
||||
▼ ▼
|
||||
┌────────────────┐ ┌──────────────────┐
|
||||
│ Decay │ │ Inference │
|
||||
│ Application │ │ Engine │
|
||||
│ (Loop #3,#6) │ │ (Loop #5,#6) │
|
||||
└────────┬───────┘ └─────────┬────────┘
|
||||
│ │
|
||||
└───────────┬────────────┘
|
||||
│
|
||||
▼
|
||||
┌───────────────────────┐
|
||||
│ Hot-Words Cache │
|
||||
│ Reorganization │
|
||||
└───────────┬───────────┘
|
||||
│
|
||||
▼
|
||||
┌───────────────────────┐
|
||||
│ Optimized Lookup │
|
||||
│ (O(1) cache hit) │
|
||||
└───────────────────────┘
|
||||
```
|
||||
|
||||
### 5.2 Feedback Loop Interactions
|
||||
|
||||
```
|
||||
Execution → Frequency ↑ → Cache Rank ↑ → Lookup Speed ↑ → More Execution
|
||||
▲ │
|
||||
│ │
|
||||
└─────────────── (Positive Feedback) ────────────┘
|
||||
|
||||
Frequency ↑ → Decay ↑ → Frequency ↓ → Decay ↓ → Frequency Stabilizes
|
||||
▲ │
|
||||
│ │
|
||||
└──── (Negative Feedback) ────┘
|
||||
|
||||
Variance ↑ → Window Shrink → Variance ↓ → Window Stable
|
||||
▲ │
|
||||
│ │
|
||||
└──── (Negative Feedback) ──┘
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## VI. ONTOLOGICAL COMMITMENTS
|
||||
|
||||
### 6.1 Foundational Assumptions
|
||||
|
||||
1. **Frequency as Proxy for Importance**
|
||||
- Assumption: Frequently executed code is more important to optimize
|
||||
- Justification: Empirical validation (Zipf's law in execution patterns)
|
||||
|
||||
2. **Decay Models Temporal Relevance**
|
||||
- Assumption: Recent executions are more relevant than distant past
|
||||
- Justification: Locality of reference (temporal locality principle)
|
||||
|
||||
3. **Determinism Through Convergence**
|
||||
- Assumption: Adaptive systems can converge to deterministic steady states
|
||||
- Justification: Fixed-point theorems for contractive mappings
|
||||
|
||||
4. **Statistical Inference Validity**
|
||||
- Assumption: Execution patterns are statistically analyzable
|
||||
- Justification: Central Limit Theorem for large sample sizes
|
||||
|
||||
### 6.2 Scope Limitations
|
||||
|
||||
**What This Ontology DOES Cover**:
|
||||
- ✓ Execution frequency measurement and decay
|
||||
- ✓ Adaptive caching and inference mechanisms
|
||||
- ✓ Dynamical systems characterization
|
||||
- ✓ Statistical convergence properties
|
||||
|
||||
**What This Ontology DOES NOT Cover**:
|
||||
- ✗ Actual thermodynamic processes (metaphor only)
|
||||
- ✗ Machine learning or neural networks (no training)
|
||||
- ✗ Quantum computing (no quantum effects)
|
||||
- ✗ Biological neural systems (no biomimicry)
|
||||
|
||||
---
|
||||
|
||||
## VII. USAGE GUIDELINES
|
||||
|
||||
### 7.1 Academic Writing
|
||||
|
||||
**In Abstracts/Titles**: Use precise, non-metaphorical terms
|
||||
```
|
||||
✅ "Thermodynamically-Inspired Adaptive Runtime"
|
||||
❌ "Physics-Based Virtual Machine"
|
||||
```
|
||||
|
||||
**In Technical Sections**: Qualify metaphors explicitly
|
||||
```
|
||||
✅ "We employ a thermodynamic metaphor where execution frequency
|
||||
is treated as 'heat' that dissipates over time..."
|
||||
❌ "The physics model applies heat decay..."
|
||||
```
|
||||
|
||||
**In Formalism**: Use mathematical definitions, not analogies
|
||||
```
|
||||
✅ "Frequency evolves as f(t) = f₀ * e^(-λt)"
|
||||
❌ "Heat cools exponentially like in Newton's law"
|
||||
```
|
||||
|
||||
### 7.2 Code Comments
|
||||
|
||||
**In Source Code**: Use concrete terms from lexicon
|
||||
```c
|
||||
// ✅ GOOD: Increment execution frequency counter
|
||||
entry->execution_heat++;
|
||||
|
||||
// ❌ BAD: Increase temperature of word
|
||||
entry->execution_heat++; // heat up!
|
||||
```
|
||||
|
||||
### 7.3 Presentation/Talks
|
||||
|
||||
**Slides**: Use metaphor for intuition, then formalize
|
||||
```
|
||||
Slide 1: "Think of execution frequency like heat..."
|
||||
Slide 2: "Formally: f(t) = f₀ * e^(-λt)"
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## VIII. REFERENCES
|
||||
|
||||
### 8.1 Foundational Concepts
|
||||
|
||||
- **Dynamical Systems**: Strogatz, S. (2015). *Nonlinear Dynamics and Chaos*
|
||||
- **Control Theory**: Åström, K. & Murray, R. (2008). *Feedback Systems*
|
||||
- **Statistical Inference**: Casella, G. & Berger, R. (2002). *Statistical Inference*
|
||||
- **Exponential Decay**: Standard mathematical function (e^(-λt))
|
||||
|
||||
### 8.2 Related Work
|
||||
|
||||
- **Trace-based JIT**: Bolz et al. (2009). "Tracing the Meta-Level: PyPy's Tracing JIT Compiler"
|
||||
- **Adaptive Systems**: Garlan et al. (2004). "Rainbow: Architecture-Based Self-Adaptation"
|
||||
- **Forth Optimization**: Ertl, M.A. (1996). "Stack Caching for Interpreters"
|
||||
|
||||
---
|
||||
|
||||
## IX. VERSION HISTORY
|
||||
|
||||
**v1.0** (2025-12-13):
|
||||
- Initial ontology, taxonomy, and lexicon
|
||||
- Formal mathematical definitions
|
||||
- Relationship diagrams
|
||||
- Usage guidelines
|
||||
|
||||
---
|
||||
|
||||
## X. ACKNOWLEDGMENTS
|
||||
|
||||
This ontology provides the formal conceptual framework for the StarForth project.
|
||||
It aims to eliminate ambiguity and enable precise academic discourse while
|
||||
acknowledging the metaphorical nature of certain conceptual mappings.
|
||||
|
||||
**License**: CC0 / Public Domain
|
||||
Reference in New Issue
Block a user