2060430
A Defect in Dempster-Shafer Theory
By analyzing the relationships among chance, weight of evidence and degree of belief, we show that the assertion "probability functions are special cases of belief functions" and the assertion "Dempster's rule can be used to combine belief functions based on distinct bodies of evidence" together lead to an inconsistency in Dempster-Shafer theory. To solve this problem, we must reject some fundamental postulates of the theory. We introduce a new approach for uncertainty management that shares many intuitive ideas with D-S theory, while avoiding this problem.
5826256
Confidence as Higher-Order Uncertainty
With conflicting evidence, a reasoning system derives uncertain conclusions. If the system is open to new evidence, it faces additionally a higher-order uncertainty, because the first-order uncertainty evaluations are uncertain themselves — they can be changed by future evidence. A new measurement, confidence, is introduced for this higher-order uncertainty. It is defined in terms of the amount of available evidence, and interpreted and processed as the relative stability of the first-order uncertainty evaluation. Its relation with other approaches of “reasoning with uncertainty” is also discussed.
28879338
Reasoning in Practical Situations
An automatic reasoning system usually consists of the following major components: (1) a formal language that represents knowledge, (2) a semantics that defines meaning and truth value in the language, (3) a set of inference rules that derives new knowledge from existing knowledge, (4) a memory that stores knowledge, and (5) a control mechanism that chooses premises and rules in each inference step. The first three components are usually referred to as a logic, or the logical part of the reasoning system, and the last two as an implementation of, or the control part of the system.
34131767
Problem Solving With Insufficient Resources
A new approach, "controlled concurrency," is introduced for inference control in an adaptive reasoning system working with insufficient knowledge and resources. With this method, a problem-solving process is constructed from atomic steps in run time, according to the system's past experience and the current context. The system carries out many such processes in parallel by distributing its resources among them, and dynamically adjusting the distribution according to feedback. A data structure, "bag," is designed to support this dynamic time-space allocation, and is a kind of probabilistic priority queue. This approach provides a flexible, efficient, and adaptive control mechanism for real-time systems working with uncertain knowledge. To analyze problem solving in such a system, the traditional computability theory and computational complexity theory become inappropriate, because the system no longer follows problem-specific algorithms in problem solving.
26841509
From inheritance relation to nonaxiomatic logic
Abstract A nonaxiomatic reasoning system is an adaptive system that works with insufficient knowledge and resources. At the beginning of the paper, three binary term logics are defined. The first is based only on an inheritance relation. The second and the third suggest a novel way to process extension and intension, and they also have interesting relations with Aristotle's syllogistic logic. Based on the three simple systems, a nonaxiomatic logic is defined. It has a term-oriented language and an experience-grounded semantics. It can uniformly represent and process randomness, fuzziness, and ignorance. It can also uniformly carry out deduction, abduction, induction, and revision.
13349953
Heuristics and normative models of judgment under uncertainty
Abstract Psychological evidence shows that probability theory is not a proper descriptive model of intuitive human judgment. Instead, some heuristics have been proposed as such a descriptive model. This paper argues that probability theory has limitations even as a normative model. A new normative model of judgment under undertainty is designed under the assumption that the system's knowledge and resources are insufficient with respect to the questions that the system needs to answer. The proposed heuristics in human reasoning can also be observed in this new model, and can be justified according to the assumption.
40949007
Pluggability Issues in the Multi Protocol
There are several advantages to providing communication links between independent scientific applications. Important problems to solve include data and control integration. Solving these problems separately is an essential aspect of the design and implementation of a protocol for mathematics. The Multi Protocol (MP) specification addresses the exchange of mathematical data by focusing only on the data encoding issues. In this way, MP can be plugged into various existing data transport mechanisms addressing control integration, or augmented by a higher control-related protocol layer. Our implementation of MP is independent of the data transport mechanism and can work with several devices. An application puts/gets data to/from MP buffers which communicate with the transport device through an abstract device interface. This paper describes the general design of the interface between MP and a transport device and the lessons we have learned during its implementation.
25531643
Multicomponent chirp signals analysis using product cubic phase function
This paper presents an algorithm for estimating the parameters of multicomponent chirp signals. The estimator is based on the cubic phase function (CPF), which is efficient to estimate the parameters of monocomponent first-, second-, and third-order polynomial phase signal. When the CPF is dealing with multicomponent chirp signals, the spurious peaks arise and hence the identifiability problem exists. A new approach based on the product cubic phase function (PCPF) is proposed to remove the identifiability problem. The occurrence probability of spurious peak, and the effect of noise to the estimator are statistically studied. The simulation examples are provided for validating the theoretical analysis.
12790595
Optimally scheduling N customer arrival times for a single-server system
Abstract In this paper, we investigate the problem of scheduling a finite number of customer arrivals for a single-server system. Under the assumptions that the customers arrive at the system by scheduled appointments and they request random amount of times for service, the question is: what are the ‘best’ arrival times so that the total operating cost is minimized? This type of queueing problem has important applications in production systems as well as in service systems. Using phase-type distribution functions and matrix algebraic manipulation, we are able to obtain recursive expressions for the customer flow-time distributions, from which the mean and variance, or higher moments, can be easily computed. A computational procedure is developed that efficiently evaluates the mean flow-times for large number of customers that need to be scheduled. This procedure is integrated with a nonlinear program that determines the optimal customer arrival times.
31996759
Analysis and Design of Parallel Thinning Algorithms - A Generic Approach
In this paper, a generic approach for the analysis and design of parallel thinning algorithms is presented. The procedures for designing 4-subcycle/iteration, 2-subcycle/iteration, and 1-subcycle/iteration thinning algorithms are developed. The experimental results show that these thinning algorithms designed by proposed approach preserve image connectivity, produce thinner results, and obtain faster speed than many existing key thinning algorithms. As an example, a 1-subcycle/iteration algorithm and its experimental results were illustrated, which is in general about two times faster than others in the literature.
28206858
Tennis Video Analysis Based on Transformed Motion Vectors
Motion Vectors (MV) indicate the motion characteristics between two video frames, and has been widely used in the content-based sports video analysis. Previous works on sports video analysis have proved the effectiveness and efficiency of the MV-based methods. However, in the tennis video, the MV-based methods are seldom applied because the motion represented by MV is greatly deformed relative to the player’s true movement due to the camera’s diagonal shooting. In this paper, an algorithm of MV transformation is proposed to revise the deformed MV using a pinhole camera model. With the transformed MVs, we generate the temporal feature curves and employ Hidden Markov Models to classify two types of player’s basic actions. Evaluation on four hours live tennis videos shows very encouraging results.