Search results for "Probabilistic"
showing 10 items of 380 documents
Minimal nontrivial space complexity of probabilistic one- way turing machines
2005
Languages recognizable in o(log log n) space by probabilistic one — way Turing machines are proved to be regular. This solves an open problem in [4].
Transitive Reasoning with Imprecise Probabilities
2015
We study probabilistically informative (weak) versions of transitivity by using suitable definitions of defaults and negated defaults in the setting of coherence and imprecise probabilities. We represent \(\text{ p-consistent }\) sequences of defaults and/or negated defaults by g-coherent imprecise probability assessments on the respective sequences of conditional events. Finally, we present the coherent probability propagation rules for Weak Transitivity and the validity of selected inference patterns by proving p-entailment of the associated knowledge bases.
Common fixed point theorems for mappings satisfying common property (E.A.) in symmetric spaces
2011
In this paper, common fixed point theorems for mappings satisfying a generalized contractive condition are obtained in symmetric spaces by using the notion of common property (E.A.). In the process, a host of previously known results are improved and generalized. We also derive results on common fixed point in probabilistic symmetric spaces.
Probabilistic Interpretations of Predicates
2016
In classical logic, any m-ary predicate is interpreted as an m-argument two-valued relation defined on a non-empty universe. In probability theory, m-ary predicates are interpreted as probability measures on the mth power of a probability space. m-ary probabilistic predicates are equivalently semantically characterized as m-dimensional cumulative distribution functions defined on \(\mathbb {R}^m\). The paper is mainly concerned with probabilistic interpretations of unary predicates in the algebra of cumulative distribution functions defined on \(\mathbb {R}\). This algebra, enriched with two constants, forms a bounded De Morgan algebra. Two logical systems based on the algebra of cumulative…
Uncountable Realtime Probabilistic Classes
2018
We investigate the minimal cases for realtime probabilistic machines that can define uncountably many languages with bounded error. We show that logarithmic space is enough for realtime PTMs on unary languages. On non-unary case, we obtain the same result for double logarithmic space, which is also tight. When replacing the work tape with a few counters, we can still achieve similar results for unary linear-space two-counter automata, unary sublinear-space three-counter automata, and non-unary sublinear-space two-counter automata. We also show how to slightly improve the sublinear-space constructions by using more counters.
Common fixed point theorems for families of occasionally weakly compatible mappings
2011
We prove some common fixed point theorems in probabilistic semi-metric spaces for families of occasionally weakly compatible mappings. We also give a common fixed point theorem for mappings satisfying an integral-type implicit relation.
A Probabilistic Approach to the Count-To-Infinity Problem in Distance-Vector Routing Algorithms
2013
Count-to-infinity problem is characteristic for routing algorithms based on the distributed implementation of the classical Bellman-Ford algorithm. In this paper a probabilistic solution to this problem is proposed. It is argued that by the use of a Bloom Filter added to the routing message the routing loops will with high probability not form. An experimental analysis of this solution for use in Wireless Sensor Networks in practice is also included.
Means of 2D and 3D Shapes and Their Application in Anatomical Atlas Building
2015
This works deals with the concept of mean when applied to 2D or 3D shapes and with its applicability to the construction of digital atlases to be used in digital anatomy. Unlike numerical data, there are several possible definitions of the mean of a shape distribution and procedures for its estimation from a sample of shapes. Most popular definitions are based in the distance function or in the coverage function, each with its strengths and limitations. Closely related to the concept of mean shape is the concept of atlas, here understood as a probability or membership map that tells how likely is that a point belongs to a shape drawn from the shape distribution at hand. We devise a procedur…
Probabilistic Forecast for Northern New Zealand Seismic Process Based on a Forward Predictive Kernel Estimator
2011
In seismology predictive properties of the estimated intensity function are often pursued. For this purpose, we propose an estimation procedure in time, longitude, latitude and depth domains, based on the subsequent increments of likelihood obtained adding an observation one at a time. On the basis of this estimation approach a forecast of earthquakes of a given area of Northern New Zealand is provided, assuming that future earthquakes activity may be based on the smoothing of past earthquakes.
Belief elicitation with multiple point predictions
2021
Abstract We propose a simple, incentive compatible procedure based on binarized linear scoring rules to elicit beliefs about real-valued outcomes - multiple point predictions. Simultaneously eliciting multiple point predictions with linear incentives reveals the subjective probability distribution without pre-defined intervals or probabilistic statements. We show that the approach is theoretically as robust as existing methods, while adapting flexibly to different beliefs. In a laboratory experiment, we compare our procedure to the standard approach of eliciting discrete probabilities on pre-defined intervals. We find that elicitation with multiple point predictions is faster, perceived as …