7087864
Formal description of the cognitive process of decision making
Decision making is one of the basic cognitive processes of human behaviors by which a preferred option or a course of actions is chosen from among a set of alternatives based on certain criteria. Decision theories are widely applied in a number of disciplines encompassing cognitive science, computer science, management science, economics, sociology, psychology, political science, and statistics. The studies on decision making can be categorized into two classes: descriptive and normative theories. A number of decision strategies have been proposed from different angles and application domains such as the maximum expected utility and Bayesian method. However, there is still a lack of a fundamental and mathematical decision model and a rigorous cognitive process for decision making. This paper presents a decision making process on the basis of the layered reference model of the brain (LRMB). The cognitive process of decision making is modeled as a sequence of Cartesian-product based selections. A rigorous description of the decision process in real-time process algebra (RTPA) is presented. Different decision making strategies are comparatively analyzed. The result shows these strategies can be well fit in the formally described decision process. The cognitive process of decision making may be applied in a wide range of decision-based systems, such as cognitive informatics, software agent systems, expert systems, and decision support systems.
44372041
Software Engineering Process Benchmarking
This paper proposes a Software Engineering Process (SEP) benchmarking methodology and a benchmark-gap analysis technique to assist industrial practitioners in quantitative software engineering. This work adopts the comprehensive SEP Assessment model (SEPRM), as a foundation to SEP benchmarking. In this approach, a number of conventional benchmarking challenges may be overcome. Case studies are presented to demonstrate the usage of the benchmarking technologies and supporting tools.
27410689
On cognitive informatics
Information is the third essence in modeling the natural world. This paper attempts to explore an emerging discipline know as cognitive informatics. Cognitive Informatics is a profound interdisciplinary research area that tackles the common root problems of modern informatics, computation, software engineering, artificial intelligence (AI), neural psychology, and cognitive science. Cognitive informatics studies the internal information processing mechanisms and natural intelligence of the brain. This paper describes historical development of informatics from the classical information theory, contemporary informatics, to cognitive informatics. The domain of cognitive informatics and its interdisciplinary nature are explored. Foundations of cognitive informatics, particularly the brain vs. the mind, the acquired life functions vs. the inherited ones, and generic relationships between information, matter and energy are investigated. The potential engineering applications of cognitive informatics and perspectives on future research are discussed. It is expected that the investigation into cognitive informatics will result in fundamental findings towards the development of next generation IT and software technologies, such as neural computers, bioinformatics, quantum information processing, new software development approaches, and new architectures of information systems.
12841371
Implementing the Real-Time Processes of RTPA using Real-Time Java
This paper discusses the implementation of the real-time processes of real-time process algebra (RTPA) using real-time Java. The difficulty in implementing real-time software from formal specifications comes from the fact that some realtime features expressed using a formal specification language cannot be easily transformed into a programming language. The paper shows how a combination of a real-time support library for RTPA (RTPASupportLib) and the recently developed extensions to real-time Java can overcome some of these difficulties. The strategies and techniques employed in implementing RTPA real-time features such as concurrency, interleaving, and interrupt/event/time-driven dispatching of real-time processes are presented. A number of case studies on the implementation of RTPA real-time features show that the approach is a feasible one
21557809
Formal description of the cognitive process of problem solving
One of the fundamental human cognitive processes is problem solving. Most of the decisions we make relate to some kind of problems we try to solve no matter how trivial and critical the problem may be. The problem solving process entails performing in a new situation with information acquired and knowledge learned from past situations. As a higher level cognitive process, problem solving involves the correlation process effort to connect newly encounter problem object(s) with the object-attribute-relation (OAR) model representation of knowledge in the brain. The goal of problem solving is to search along various solution paths within the problem solver's knowledge base in the memory. When a problem object is identified, problem solving can be perceived as a search process in the memory space for finding a relationship between a set of problem-solving goals and a set of alternative paths. This paper presents a mathematical and cognitive model that describes problem solving as a cognitive process. The cognitive structures of the brain and the mechanisms of internal knowledge representation behind the cognitive process of problem solving are explained. The cognitive process is then formally and rigorously described using real-time process algebra (RTPA) base on the aforementioned models. Extended discussions are presented on applications of the cognitive process model of problem solving in software engineering and psychology.
21184887
The cognitive processes of abstraction and formal inferences
Theoretical research is predominately an inductive process; while applied research is mainly a deductive process. Both inference processes are based on the cognitive process and means of abstraction. This paper describes the cognitive processes of abstraction and formal inferences such as deduction, induction, abduction, and analogy. The hierarchy of abstraction and the descriptivity of abstract means at different levels are analyzed. A set of mathematical models of formal inference methodologies are developed. Formal descriptions of the five cognitive processes of abstraction and inferences are presented using real-time process algebra (RTPA). Applications of abstraction and formal inferences in dealing with complicated problems in large-scale software system development in software engineering are discussed.
44707452
Diagnosis of clustered faults for identical degree topologies
Huang et al, [1998] studied the diagnosis of clustered faults and wafer testing. They proposed a diagnosis algorithm for a probabilistic fault model in simple rectangular grid structures. In this paper, we extend their results and study the diagnosis algorithm for arbitrary identical degree topologies. Our results are useful and valid for a large class of topologies. We investigate the local and global performance of the algorithm under several important fault distributions: Bernoulli failure distribution, Gamma failure distribution, and exponential failure distribution. We demonstrate that the diagnosis scheme can identify almost all nodes successfully even if the percentage of fault-free units is low (much lower than 50%) while almost all units are guaranteed to be correctly identified. In addition, we show that the performance of the algorithm is insensitive to the changes of the percentage.
19562173
Web-service-agents-based family wealth management system
The roiling financial markets, constantly changing tax law and increasing complexity of planning transaction increase the demand of aggregated family wealth management (FWM) services. However, current trend of developing such advisory systems is mainly focusing on financial or investment side. In addition, these existing systems lack of flexibility and are hard to be integrated with other organizational information systems, such as CRM systems. In this paper, a novel architecture of Web-service-agents-based FWM systems has been proposed. Multiple intelligent agents are wrapped as Web services and can communicate with each other via Web service protocols. On the one hand, these agents can collaborate with each other and provide comprehensive FWM advices. On the other hand, each service can work independently to achieve its own tasks. A prototype system for supporting financial advice is also presented to demonstrate the advances of the proposed Webservice- agents-based FWM system architecture.
6142906
Multiple attribute decision making based on fuzzy preference information on alternatives: Ranking and weighting
This paper investigates the multiple attribute decision making (MADM) problem with fuzzy preference information on alternatives and proposes an eigenvector method to rank them. Three optimization models are introduced to assess the relative importance weights of attributes in a MADM problem, which integrate subjective fuzzy preference relations and objective information in different ways. Since the decisions these models lead to are based on both subjective and objective information, they are more balanced and credible than those that consider only one type of information. An example is provided to illustrate the application of the proposed models.
6236190
Estimation of multiple directional light sources for synthesis of mixed reality images
We present a new method for the detection and estimation of multiple directional illuminants, using a single image of any object with known geometry and Lambertian reflectance. We use the resulting highly accurate estimates to modify virtually the illumination and geometry of a real scene and produce correctly illuminated mixed reality images. Our method obviates the need to modify the imaged scene by inserting calibration objects of any particular geometry, relying instead on partial knowledge of the geometry of the scene. Thus, the recovered multiple illuminants can be used both for image-based rendering and for shape reconstruction. Our method combines information both from the shading of the object and from shadows cast on the scene by the object. Initially we use a method based on shadows and a method based on shading independently. The shadow based method utilizes brightness variation inside the shadows cast by the object, whereas the shading based method utilizes brightness variation on the directly illuminated portions of the object. We demonstrate how the two sources of information complement each other in a number of occasions. We then describe an approach that integrates the two methods, with results superior to those obtained if the two methods are used separately. The resulting illumination information can be used (i) to render synthetic objects in a real photograph with correct illumination effects, and (ii) to virtually re-light the scene.
19364030
The evidential reasoning approach for multiple attribute decision analysis using interval belief degrees
Abstract Multiple attribute decision analysis (MADA) problems having both quantitative and qualitative attributes under uncertainty can be modeled using the evidential reasoning (ER) approach. Several types of uncertainties such as ignorance and fuzziness can be modeled in the ER framework. In this paper, the ER approach will be extended to model new types of uncertainties including interval belief degrees and interval data that could be incurred in decision situations such as group decision making. The Dempster–Shafer (D–S) theory of evidence is first extended, which is one of the bases of the ER approach. The analytical ER algorithm is used to combine all evidence simultaneously. Two pairs of nonlinear optimization models are constructed to estimate the upper and lower bounds of the combined belief degrees and to compute the maximum and the minimum expected utilities of each alternative, respectively. Interval data are equivalently transformed to interval belief degrees and are incorporated into the nonlinear optimization models. A cargo ship selection problem is examined to show the implementation process of the proposed approach.