127 research outputs found
Applicable Mathematics in a Minimal Computational Theory of Sets
In previous papers on this project a general static logical framework for
formalizing and mechanizing set theories of different strength was suggested,
and the power of some predicatively acceptable theories in that framework was
explored. In this work we first improve that framework by enriching it with
means for coherently extending by definitions its theories, without destroying
its static nature or violating any of the principles on which it is based. Then
we turn to investigate within the enriched framework the power of the minimal
(predicatively acceptable) theory in it that proves the existence of infinite
sets. We show that that theory is a computational theory, in the sense that
every element of its minimal transitive model is denoted by some of its closed
terms. (That model happens to be the second universe in Jensen's hierarchy.)
Then we show that already this minimal theory suffices for developing very
large portions (if not all) of scientifically applicable mathematics. This
requires treating the collection of real numbers as a proper class, that is: a
unary predicate which can be introduced in the theory by the static extension
method described in the first part of the paper
Realizing Continuity Using Stateful Computations
The principle of continuity is a seminal property that holds for a number of intuitionistic theories such as System T. Roughly speaking, it states that functions on real numbers only need approximations of these numbers to compute. Generally, continuity principles have been justified using semantical arguments, but it is known that the modulus of continuity of functions can be computed using effectful computations such as exceptions or reference cells. This paper presents a class of intuitionistic theories that features stateful computations, such as reference cells, and shows that these theories can be extended with continuity axioms. The modulus of continuity of the functionals on the Baire space is directly computed using the stateful computations enabled in the theory
Towards Automated Reasoning in Herbrand Structures
Herbrand structures have the advantage, computationally speaking, of being guided by the definability of all elements in them. A salient feature of the logics induced by them is that they internally
exhibit the induction scheme, thus providing a congenial, computationally-oriented framework for
formal inductive reasoning. Nonetheless, their enhanced expressivity renders any effective proof
system for them incomplete. Furthermore, the fact that they are not compact poses yet another prooftheoretic challenge. This paper offers several layers for coping with the inherent incompleteness and
non-compactness of these logics. First, two types of infinitary proof system are introduced—one
of infinite width and one of infinite height—which manipulate infinite sequents and are sound and
complete for the intended semantics. The restriction of these systems to finite sequents induces a
completeness result for finite entailments. Then, in search of effectiveness, two finite approximations
of these systems are presented and explored. Interestingly, the approximation of the infinite-width
system via an explicit induction scheme turns out to be weaker than the effective cyclic fragment of the
infinite-height system
The FastMap Algorithm for Shortest Path Computations
We present a new preprocessing algorithm for embedding the nodes of a given
edge-weighted undirected graph into a Euclidean space. The Euclidean distance
between any two nodes in this space approximates the length of the shortest
path between them in the given graph. Later, at runtime, a shortest path
between any two nodes can be computed with A* search using the Euclidean
distances as heuristic. Our preprocessing algorithm, called FastMap, is
inspired by the data mining algorithm of the same name and runs in near-linear
time. Hence, FastMap is orders of magnitude faster than competing approaches
that produce a Euclidean embedding using Semidefinite Programming. FastMap also
produces admissible and consistent heuristics and therefore guarantees the
generation of shortest paths. Moreover, FastMap applies to general undirected
graphs for which many traditional heuristics, such as the Manhattan Distance
heuristic, are not well defined. Empirically, we demonstrate that A* search
using the FastMap heuristic is competitive with A* search using other
state-of-the-art heuristics, such as the Differential heuristic
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