Provides an implementation of McCarthy's `amb` operator with
binding forms and acceptance test operator.

Constraints solving functions that operate on a Constraint Description
which is a map describing a constraint description containing the mappings:
- :variables -> seq of LVars
- :formula -> list describing a predicate expression composed of a mix of
  the LVars in :variables and Clojure functions.

Most functions in rv work off of one or more of the following core
concepts:

Entity: a hashmap with a :kb/id key mapped to a unique value and namespaced keys.

{:kb/id       :person/john-doe
 :person/name "John Doe"
 :person/age  42}

Table: a set of hashmaps or Entities. Tables represent unstructured or
semi-structured collections of data.

#{{:kb/id :city/blt :city/name "Baltimore"}
  {:kb/id :city/atl  :city/name "Atlanta"}}

Fact: a vector triple in the form [entity-id attribute value] that describe that
a given entity has an attribute with a specific value. You can tie facts together
by referencing their :kb/ids.

[:person/john-doe :person/age 42]
[:city/blt :city/name "Baltimore"]

Relation: a set of Facts pertaining to a particular Entity. You can tie facts
together by referencing :kb/ids in value positions.

#{[:person/john-doe :person/age 42]
  [:city/blt :city/name "Baltimore"]
  [:person/john-doe :address/city :city/blt]}

LVar: a logic variable that can unify with any value in its :range

(map->LVar {:domain 'x :range (range 0 5)})

Ground: a concrete value, like a keyword, number, string, etc.

42, "John Doe", :city/blt

Query: a set of Facts containing a mix of LVars and Grounds used  to find
bindings for the LVars that satisfy a set of Facts.

Rules: a set of Facts describing derived or synthetic relations in terms of
existing ones.

Production: a map containing :antecedent -> query and :consequent -> Facts
to be asserted if the query fires.

KB: a set of Relations about many Entities and possibly containing Productions. It
represents all the knowledge currently known or derivable.

Constraint Description: a set of LVars and a Formula describing the domain
of their values.

Formula: a list describing a predicate expression of mixed LVars and clojure functions.

A minimal implementation of Datalog.

I came across the Soundex algorithm when researching the retro KAMAS outlining application.
Soundex is a phonetic algorithm for indexing words by sound.

Provides internal unification functions.
DO NOT USE THIS NS.
There is no guarantee that it will remain stable or at all.

Common learning-related functions and protocols.

Version spaces are a binary classification, empirical learning algorithm.
The approach, as described in 'Version spaces: a candidate elimination approach
to rule learning' by Tom Mitchel (1977) takes training examples (currently
Tuples of a like-arity) and manages a 'version space'. A version space is a
map containing two 'boundaries' `:S` and `:G`. The `:G` boundary contains 'hypotheses'
corresponding to the most general versions of the training data that are consistent
and `:S` is the most specific versions. When a version space is presented with a new
example it runs a 'candidate elimination' algorithm to modify the boundaries `:S`
and `:G` accordingly. Examples can be marked as 'positive' examples, meaning
that they are preferred instances. Anything not marked as 'positive' are taken as
negative examples. Once trained, a version space can  classify new examples as
`::positive` or `::negative`. If new examples are not covered by the existing hypotheses
in either boundary then they are classified as `::ambiguous` instead.

The simplest possible production rules system that uses a set
of EAV tuples as its knowledge base.

Common search-related functions and protocols.

A* search implementation.