Algebras and Base Change¶
The choice of algebra \(\mathcal{V}\) in an algebra declaration determines the truth-value semantics of every \(\mathcal{V}\)-relation in the program. A QVR algebra is the structure \((V, \le, \otimes, \oplus, \mathbf{1})\) that assigns weights to V-relations; not every built-in algebra is a strict quantale in Kelly's sense, as classified in §2. This page records the formal definition of each built-in algebra and the base-change functors that mediate between them.
1. The eleven algebras¶
Each algebra is determined by its underlying lattice and its monoidal product. Joins are taken pointwise on \(V\); the unit \(\mathbf{1}\) is the maximum element with respect to the order.
1.1 Product fuzzy algebra¶
The join is noisy-OR. This is the QVR default.
1.2 Boolean algebra¶
The classical two-element lattice; \(\mathcal{V}_{\mathbb{B}}\text{-}\mathbf{Rel}\) is the category of ordinary binary relations on finite sets.
1.3 Łukasiewicz algebra¶
1.4 Gödel algebra¶
1.5 Tropical algebra¶
The order is reversed: smaller is "truer". The unit is \(0\) (the additive identity), and the bottom of the lattice (the largest element) is \(+\infty\). Composition is the min-plus matrix product, suitable for shortest-path semantics.
1.6 Max-plus (Viterbi) algebra¶
The max-plus / Viterbi semiring used in best-path scoring; the bottom \(\bot = -\infty\) is the additive zero, the unit \(\mathbf{1} = 0\), and joins are pointwise max. Programs over log-probabilities live in the sub-poset \((-\infty, 0]\).
1.7 Log-prob algebra¶
The log-space analogue of the product-fuzzy / probability algebra. Carrier, unit, and bottom coincide with \(\mathcal{V}_{\mathrm{MP}}\); the algebra differs by replacing \(\max\) with \(\operatorname{logsumexp}\), the smooth aggregation. Composition is numerically stable log-domain matrix multiplication. Programs over log-probabilities live in the sub-poset \((-\infty, 0]\).
1.8 Markov algebra¶
The sum-product semiring underlying stochastic-kernel composition: a \(\mathcal{V}_{\mathrm{M}}\)-relation is the per-entry tabulation of a row-stochastic matrix, and matrix multiplication under this algebra is Kleisli composition in \(\mathbf{Stoch}\). Like \(\mathcal{V}_{\mathbb{R}}\) this is a semiring rather than a bounded lattice; the row-stochasticity constraint lives in the morphism layer, not in the algebra itself.
1.9 Real algebra¶
The sum-product semiring on the reals. No bottom/top: this is a semiring, not a bounded algebra, and is used for expectation-style aggregation where negative weights and unbounded magnitudes are required.
1.10 Probability algebra¶
Sum-product on \([0, 1]\) with explicit saturation at \(1\) on aggregation. Distinguishes from \(\mathcal{V}_{\mathrm{pf}}\) in its choice of join (saturated-sum rather than noisy-OR).
1.11 Counting algebra¶
Sum-product on the non-negative integers. Used for derivation-counting and unweighted multiplicity tracking. Negation is undefined.
2. Order- and structure-preservation¶
For each algebra we record which elementary properties hold; these determine which categorical constructions transport across base change.
| Algebra | Idempotent? | Integral? | Cancellative? |
|---|---|---|---|
| \(\mathcal{V}_{\mathrm{pf}}\) | No | Yes (\(\mathbf{1} = 1\)) | No |
| \(\mathcal{V}_{\mathbb{B}}\) | Yes | Yes | No |
| \(\mathcal{V}_{\mathrm{L}}\) | No | Yes | No |
| \(\mathcal{V}_{\mathrm{G}}\) | Yes | Yes | No |
| \(\mathcal{V}_{\mathrm{T}}\) | Yes (join) | Yes (\(\mathbf{1} = 0\)) | Yes |
| \(\mathcal{V}_{\mathrm{MP}}\) | Yes (join) | Yes (\(\mathbf{1} = 0\)) | Yes |
| \(\mathcal{V}_{\mathrm{LP}}\) | No | Yes (\(\mathbf{1} = 0\)) | Yes |
| \(\mathcal{V}_{\mathrm{M}}\) | No | Yes (\(\mathbf{1} = \delta\)) | No |
| \(\mathcal{V}_{\mathbb{R}}\) | No | Yes (\(\mathbf{1} = 1\)) | Yes |
| \(\mathcal{V}_{[0,1]}\) | No | Yes (\(\mathbf{1} = 1\)) | No |
| \(\mathcal{V}_{\mathbb{N}}\) | No | Yes (\(\mathbf{1} = 1\)) | Yes |
An algebra is integral if \(\mathbf{1}\) is the top element and idempotent if \(a \otimes a = a\) for all \(a\). Cancellativity means \(a \otimes b = a \otimes c \Rightarrow b = c\) whenever \(a \neq \bot\). Idempotent integral algebras are precisely frames (locales), and the strict-quantale subclass (in Kelly's sense) is exactly the idempotent integral case together with its non-idempotent extensions on which the join distributes exactly over the monoidal product.
2.1 A note on the product-fuzzy and Łukasiewicz pairs¶
The product-fuzzy and Łukasiewicz \((\otimes, \oplus)\) pairs are t-norm / t-conorm pairs on \([0, 1]\), equipping the unit interval with the structure of a commutative residuated lattice (an MV-algebra in the Łukasiewicz case). They are not strict quantales: the full quantale-distributivity law
fails in general for these two pairs.
For example, in the product-fuzzy pair with \(a = b_1 = b_2 = 1/2\):
Strict distributivity of \(\otimes\) over \(\bigoplus\) holds in the idempotent (\(\mathcal{V}_{\mathbb{B}}\), \(\mathcal{V}_{\mathrm{G}}\)), tropical (\(\mathcal{V}_{\mathrm{T}}\), \(\mathcal{V}_{\mathrm{MP}}\)), log-additive (\(\mathcal{V}_{\mathrm{LP}}\)), and sum-product (\(\mathcal{V}_{\mathrm{M}}\), \(\mathcal{V}_{\mathbb{R}}\), \(\mathcal{V}_{\mathbb{N}}\)) cases. The idempotent integral ones (\(\mathcal{V}_{\mathbb{B}}\), \(\mathcal{V}_{\mathrm{G}}\)) are strict quantales in Kelly's sense; the others satisfy the distributive law as semirings, with the saturated probability algebra \(\mathcal{V}_{[0,1]}\) failing strictness only at the saturation boundary. For \(\mathcal{V}_{\mathrm{pf}}\) and \(\mathcal{V}_{\mathrm{L}}\), the categorical apparatus of \(\mathcal{V}\text{-}\mathbf{Rel}\) should be read as describing the Bayesian noisy-OR (resp. Łukasiewicz-bounded-sum) aggregation under the multiplicative (resp. Łukasiewicz) t-norm, rather than as a strict \(\mathcal{V}\)-enriched category. Composition, tensor, and the equational laws of Expressions §5 hold up to this standard caveat: equations involving \(\bigoplus\)-distribution over \(\otimes\) are exact in the strict cases and approximate in the t-norm cases.
3. Base change¶
A algebra homomorphism \(h : \mathcal{V} \to \mathcal{W}\) is a join-preserving monoid map: \(h(a \otimes_{\mathcal{V}} b) = h(a) \otimes_{\mathcal{W}} h(b)\), \(h(\mathbf{1}_{\mathcal{V}}) = \mathbf{1}_{\mathcal{W}}\), and \(h\) commutes with arbitrary joins.
Each homomorphism induces a base-change functor
which acts as the identity on objects and pointwise on \(\mathcal{V}\)-relations. Functoriality is a direct consequence of \(h\) preserving \(\otimes\) and \(\bigoplus\).
The implementation ships a registry of named homomorphisms, including:
- \(\beta : \mathcal{V}_{\mathbb{B}} \to \mathcal{V}_{\mathrm{pf}}\), the inclusion \(\{0, 1\} \hookrightarrow [0, 1]\) (
Embedding); - \(\theta : \mathcal{V}_{\mathrm{pf}} \to \mathcal{V}_{\mathbb{B}}\), thresholding at \(\tau \in (0, 1]\) (
Threshold); - \(\mathcal{V}_{\mathrm{pf}} \to \mathcal{V}_{\mathrm{G}}\) via the material conditional \(a \mapsto \min(1, 1 - a + b)\) (
MaterialImplication); - \(\mathcal{V}_{\mathrm{M}} \to \mathcal{V}_{\mathrm{pf}}\) (
Expectation); - \(\mathcal{V}_{\mathrm{pf}} \to \mathcal{V}_{\mathrm{LP}}\) via \(a \mapsto \log a\) (
LogProb); - \(\mathcal{V}_{\mathrm{pf}} \to \mathcal{V}_{\mathrm{MP}}\) via \(a \mapsto \log a\) (
MaxPlus); the per-entry map matchesLogProbbut the target join is \(\max\) rather than \(\operatorname{logsumexp}\), realizing Viterbi-MAP aggregation; - \(\mathcal{V}_{\mathbb{R}} \rightleftarrows \mathcal{V}_{[0, 1]}\) (
ProbabilityClamp/ProbabilityToReal); - \(\mathcal{V}_{\mathbb{R}} \rightleftarrows \mathcal{V}_{\mathbb{N}}\) (
CountingFromReal/CountingToReal).
lookup_homomorphism(src, tgt) retrieves a registered map; programs select one via the change-of-base block. Only \(\beta \circ \theta = \mathrm{id}_{\mathcal{V}_\mathbb{B}}\) and the sub-algebra inclusions are sections; the rest are lossy lax monoidal poset functors.
4. Functoriality of the language¶
The QVR language is parametric in \(\mathcal{V}\): every syntactic construct interprets uniformly over all eleven algebras modulo the existence of joins, products, and units. Concretely, for any algebra \(\mathcal{V}\) and base-change homomorphism \(h : \mathcal{V} \to \mathcal{W}\), the diagram
commutes for every well-typed phrase whose type does not involve a kernel ... ~ Family declaration (the parametric Markov-kernel form). The stochastic and continuous strata are tied to the additive structure of \([0,1]\) as a \(\sigma\)-algebra of probabilities, not to the algebra; they ignore the algebra declaration.
This commutation is the formal content of base-change invariance: changing the underlying truth-value algebra distributes over composition, tensor, marginalization, and every other expression-level combinator.