Search results for " logic"
showing 10 items of 1720 documents
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.
Modello fuzzy di calcolo della distanza di visibilità per il sorpasso su strade extraurbane ad unica carreggiata bidirezionale
2002
Lo studio di modelli teorici che ben rappresentino, nella loro articolazione, le manovre di guida in sede stradale è da sempre un esercizio tanto praticato quanto complesso. La difficoltà di delineare compiutamente tali manovre, di definirne l’interazione cinematica dei veicoli coinvolti è comprovata dalla varietà di modelli presenti in letteratura. Con il presente lavoro ci si propone di pervenire alla formulazione di un modello originale di calcolo della distanza di visibilità per il sorpasso su strade bidirezionali ad unica carreggiata, il quale tenga debitamente conto del coacervo delle variabili cinematiche, meccaniche, geometriche, ambientali e di traffico, così come del comportamento…
Collaborative Assessment of Information Provider's Reliability and Expertise Using Subjective Logic
2011
QA each user can individually estimate the expertise and the reliability of her peers using her direct interactions with them and our framework. The online SN (OSN), which can be considered as a distributed database, performs continuous data aggregation for users expertise and reliability assessment in order to reach a consensus. We emulate a Q&A SN to examine various performance aspects of our algorithm (e.g., convergence time, responsiveness etc.). Our evaluations indicate that it can accurately assess the reliability and the expertise of a user with a small number of samples and can successfully react to the latter's behavior change, provided that the cognitive traits hold in practice.
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…
On Fuzzy Stochastic Integral Equations—A Martingale Problem Approach
2011
In the paper we consider fuzzy stochastic integral equations using the methods of stochastic inclusions. The idea is to consider an associated martingale problem and its solutions in order to obtain a solution to the fuzzy stochastic equation.
Realizing Undelayed N-step TD prediction with neural networks
2010
There exist various techniques to extend reinforcement learning algorithms, e.g., eligibility traces and planning. In this paper, an approach is proposed, which combines several extension techniques, such as using eligibility-like traces, using approximators as value functions and exploiting the model of the environment. The obtained method, ‘Undelayed n-step TD prediction’ (TD-P), has produced competitive results when put in conditions of not fully observable environment.
Optimal Control Under Fuzzy Conditions for Dynamical Systems Associated with the Second Order Linear Differential Equations
2020
This paper is devoted to an optimal trajectory planning problem with uncertainty in location conditions considered as a problem of constrained optimal control for dynamical systems. Fuzzy numbers are used to incorporate uncertainty of constraints into the classical setting of the problem under consideration. The proposed approach applied to dynamical systems associated with the second order linear differential equations allows to find an optimal control law at each \(\alpha \)-level using spline-based methods developed in the framework of the theory of splines in convex sets. The solution technique is illustrated by numerical examples.
A multicriteria extension of the efficient market hypothesis
2021
Challenging the Efficient Market Hypothesis (EMH) has been a recurrent topic for researchers and practitioners since its formulation. Hundreds of empirical studies claim to either prove or disprove the EMH by means of a number of heterogeneous methods. Even though the EMH is usually adjusted to a measure of risk, there is a lack of a formal analysis within a multiple-criteria context. In this paper, we propose a extension of the EMH that accommodates the foundations of multiple-criteria decision analysis. To this end, we rely on a family of parametric signed dissimilarity measures to assess multidimensional performance differences. Since normalization is a critical step in our approach to a…
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 …