7,975 research outputs found
Implicit complexity for coinductive data: a characterization of corecurrence
We propose a framework for reasoning about programs that manipulate
coinductive data as well as inductive data. Our approach is based on using
equational programs, which support a seamless combination of computation and
reasoning, and using productivity (fairness) as the fundamental assertion,
rather than bi-simulation. The latter is expressible in terms of the former. As
an application to this framework, we give an implicit characterization of
corecurrence: a function is definable using corecurrence iff its productivity
is provable using coinduction for formulas in which data-predicates do not
occur negatively. This is an analog, albeit in weaker form, of a
characterization of recurrence (i.e. primitive recursion) in [Leivant, Unipolar
induction, TCS 318, 2004].Comment: In Proceedings DICE 2011, arXiv:1201.034
Causal inference via algebraic geometry: feasibility tests for functional causal structures with two binary observed variables
We provide a scheme for inferring causal relations from uncontrolled
statistical data based on tools from computational algebraic geometry, in
particular, the computation of Groebner bases. We focus on causal structures
containing just two observed variables, each of which is binary. We consider
the consequences of imposing different restrictions on the number and
cardinality of latent variables and of assuming different functional
dependences of the observed variables on the latent ones (in particular, the
noise need not be additive). We provide an inductive scheme for classifying
functional causal structures into distinct observational equivalence classes.
For each observational equivalence class, we provide a procedure for deriving
constraints on the joint distribution that are necessary and sufficient
conditions for it to arise from a model in that class. We also demonstrate how
this sort of approach provides a means of determining which causal parameters
are identifiable and how to solve for these. Prospects for expanding the scope
of our scheme, in particular to the problem of quantum causal inference, are
also discussed.Comment: Accepted for publication in Journal of Causal Inference. Revised and
updated in response to referee feedback. 16+5 pages, 26+2 figures. Comments
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Elaboration in Dependent Type Theory
To be usable in practice, interactive theorem provers need to provide
convenient and efficient means of writing expressions, definitions, and proofs.
This involves inferring information that is often left implicit in an ordinary
mathematical text, and resolving ambiguities in mathematical expressions. We
refer to the process of passing from a quasi-formal and partially-specified
expression to a completely precise formal one as elaboration. We describe an
elaboration algorithm for dependent type theory that has been implemented in
the Lean theorem prover. Lean's elaborator supports higher-order unification,
type class inference, ad hoc overloading, insertion of coercions, the use of
tactics, and the computational reduction of terms. The interactions between
these components are subtle and complex, and the elaboration algorithm has been
carefully designed to balance efficiency and usability. We describe the central
design goals, and the means by which they are achieved
On the mathematical synthesis of equational logics
We provide a mathematical theory and methodology for synthesising equational
logics from algebraic metatheories. We illustrate our methodology by means of
two applications: a rational reconstruction of Birkhoff's Equational Logic and
a new equational logic for reasoning about algebraic structure with
name-binding operators.Comment: Final version for publication in Logical Methods in Computer Scienc
Structural Resolution with Co-inductive Loop Detection
A way to combine co-SLD style loop detection with structural resolution was
found and is introduced in this work, to extend structural resolution with
co-induction. In particular, we present the operational semantics, called
co-inductive structural resolution, of this novel combination and prove its
soundness with respect to the greatest complete Herbrand model.Comment: In Proceedings CoALP-Ty'16, arXiv:1709.0419
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