3,876 research outputs found
Why Philosophers Should Care About Computational Complexity
One might think that, once we know something is computable, how efficiently
it can be computed is a practical question with little further philosophical
importance. In this essay, I offer a detailed case that one would be wrong. In
particular, I argue that computational complexity theory---the field that
studies the resources (such as time, space, and randomness) needed to solve
computational problems---leads to new perspectives on the nature of
mathematical knowledge, the strong AI debate, computationalism, the problem of
logical omniscience, Hume's problem of induction, Goodman's grue riddle, the
foundations of quantum mechanics, economic rationality, closed timelike curves,
and several other topics of philosophical interest. I end by discussing aspects
of complexity theory itself that could benefit from philosophical analysis.Comment: 58 pages, to appear in "Computability: G\"odel, Turing, Church, and
beyond," MIT Press, 2012. Some minor clarifications and corrections; new
references adde
Effective Choice and Boundedness Principles in Computable Analysis
In this paper we study a new approach to classify mathematical theorems
according to their computational content. Basically, we are asking the question
which theorems can be continuously or computably transferred into each other?
For this purpose theorems are considered via their realizers which are
operations with certain input and output data. The technical tool to express
continuous or computable relations between such operations is Weihrauch
reducibility and the partially ordered degree structure induced by it. We have
identified certain choice principles which are cornerstones among Weihrauch
degrees and it turns out that certain core theorems in analysis can be
classified naturally in this structure. In particular, we study theorems such
as the Intermediate Value Theorem, the Baire Category Theorem, the Banach
Inverse Mapping Theorem and others. We also explore how existing
classifications of the Hahn-Banach Theorem and Weak K"onig's Lemma fit into
this picture. We compare the results of our classification with existing
classifications in constructive and reverse mathematics and we claim that in a
certain sense our classification is finer and sheds some new light on the
computational content of the respective theorems. We develop a number of
separation techniques based on a new parallelization principle, on certain
invariance properties of Weihrauch reducibility, on the Low Basis Theorem of
Jockusch and Soare and based on the Baire Category Theorem. Finally, we present
a number of metatheorems that allow to derive upper bounds for the
classification of the Weihrauch degree of many theorems and we discuss the
Brouwer Fixed Point Theorem as an example
Compressed Secret Key Agreement: Maximizing Multivariate Mutual Information Per Bit
The multiterminal secret key agreement problem by public discussion is
formulated with an additional source compression step where, prior to the
public discussion phase, users independently compress their private sources to
filter out strongly correlated components for generating a common secret key.
The objective is to maximize the achievable key rate as a function of the joint
entropy of the compressed sources. Since the maximum achievable key rate
captures the total amount of information mutual to the compressed sources, an
optimal compression scheme essentially maximizes the multivariate mutual
information per bit of randomness of the private sources, and can therefore be
viewed more generally as a dimension reduction technique. Single-letter lower
and upper bounds on the maximum achievable key rate are derived for the general
source model, and an explicit polynomial-time computable formula is obtained
for the pairwise independent network model. In particular, the converse results
and the upper bounds are obtained from those of the related secret key
agreement problem with rate-limited discussion. A precise duality is shown for
the two-user case with one-way discussion, and such duality is extended to
obtain the desired converse results in the multi-user case. In addition to
posing new challenges in information processing and dimension reduction, the
compressed secret key agreement problem helps shed new light on resolving the
difficult problem of secret key agreement with rate-limited discussion, by
offering a more structured achieving scheme and some simpler conjectures to
prove
Knowability Relative to Information
We present a formal semantics for epistemic logic, capturing the notion of knowability relative to information (KRI). Like Dretske, we move from the platitude that what an agent can know depends on her (empirical) information. We treat operators of the form K_AB (āB is knowable on the basis of information Aā) as variably strict quantifiers over worlds with a topic- or aboutness- preservation constraint. Variable strictness models the non-monotonicity of knowledge acquisition while allowing knowledge to be intrinsically stable. Aboutness-preservation models the topic-sensitivity of information, allowing us to invalidate controversial forms of epistemic closure while validating less controversial ones. Thus, unlike the standard modal framework for epistemic logic, KRI accommodates plausible approaches to the Kripke-Harman dogmatism paradox, which bear on non-monotonicity, or on topic-sensitivity. KRI also strikes a better balance between agent idealization and a non-trivial logic of knowledge ascriptions
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