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Interactive Dynamic Influence Diagrams (I-DIDs) constitute a graphic model for multi-agent decision making under uncertainty, but solving them is provably intractable. Algorithms for solving I-DIDs face the challenge of an exponentially growing space of candidate models ascribed to other agents, over time. Pruning behaviorally equivalent models is one way toward minimizing the model set, but composing...
This paper presents a method to model biological systems decision. This method allows to reason about incomplete, revisable and uncertain information: an operator has partial information about his environment only and must revise his decisions. Our method uses a nonmonotonic logic: the rules of behavior are formalized with default logic, to which we added a consideration of time. Our method uses preferences...
Accurate situational assessment is key to any decision making especially crucial in military command and control, air traffic control, and complex system decision making. Endsley describes three dependent levels of situational awareness, (1) perception, (2) understanding, and (3) projection. This research is focused on Endsley's second-level situational awareness (understanding) as it applies to service-oriented...
This paper applies the theory of information space for a study of dialogue management in major approaches, ranging from the classical approach based upon finite state machine to the most recent approach using partially observable Markov decision process (POMDP). After identifying the problems of current approaches, this paper proposes a modified approach of POMDP-based dialogue management. This new...
In this paper the Dempster-Shafer theory of evidence is utilized in comprehensive assessment of the reliability enhancement testing (RET). The basic concept of the D-S theory and the rule of evidence-combination are introduced. Moreover, the approach to the assessment of the RET utilizing the D-S theory of evidence is presented. Firstly a recognition frame for all possible effects of RET programs...
Diagnostic knowledge derived from dissolved gas analysis (DGA) is complex, imprecise and may lack information about the actual condition of power transformer. To deal with this uncertainty, Dempster-Shafer (DS) Theory is often utilized for the fusion of evidence obtained from various DGA diagnosis. In the Dempster-Shafer theoretic approach, several rules for combining the evidence were proposed, amongst...
In recent years, dealing with uncertainty using interval probabilities, such as combination, marginalization, condition, Bayesian inferences, is receiving considerable attention by researchers. However, how to elicit interval probabilities from subjective judgment is a basic problem for the applications of interval probabilities. In this paper, interval-valued pair-wise comparison of possible outcomes...
Efficiency and accuracy are imperative aspects in the world of medical diagnosis, for this reason, we have developed a medical diagnosis system based onholonic multi agent system. Holonic multi agent medical diagnosis system combines the advantages of the holonic paradigm, multi agent system technology, and swarm intelligence in order to realize a highly reliable, adaptive, scalable, flexible, and...
In this paper we perform the analysis of Dempster-Shafer temporalized structure for the construction of more precise decisions based on the expert knowledge valuations. The relation of information precision is defined on the bodies of evidence. Negative inaccuracy is defined as the stream of rational expert knowledge in Dempster-Shafer temporalized structure. The principle of negative inaccuracy is...
In this paper we propose the combination of accelerated variants of value iteration with improved prioritized sweeping for the solution of stochastic shortest path Markov decision processes. For the fastest solution, asynchronous updates, prioritization and prioritized sweeping have been tested. A topological reordering algorithm was also compared with a static reordering algorithm. Experimental results...
Intuitionistic fuzzy theory is an excellent tool to represent uncertainty and vagueness in fuzzy multi criteria decision making problems. When intuitionistic fuzzy numbers are used to express fuzzy information, they need to compare with each other to indicate the relative importance or priority. This paper reviews an existed method of ranking two intuitionistic fuzzy numbers, and further defines another...
The object of this study is to present a holonic medical diagnosis system, which unifies the advantages of decision theory under uncertainty with the efficiency, reliability, extensibility, and flexibility of the holonic multi agent system holonic paradigm. This paper also handles an important assumption in Baye's theorem. Clustering and discriminating provide method for solving dependence in symptoms...
Considering the problem that it is difficult to quantify the uncertainty problem about risk assessment of power network planning projects, G1 method and F-DS evidential theory are adopted to establish the assessment model of power network planning projects. Put forward the weighted formula of evidence combination with the use of G1 method. Apply information fusion technology of F-DS evidential theory...
For sequential design processes, the min-max strategy minimizes the worst-case performance cost. This is a game against nature, where the agent attempts to minimize a specified cost criterion, while nature attempts to maximize it. In this paper, we formulate the problem of decision making under uncertainty as a game in which the opponent (nature) is “disinterested” and plays at random, while the agent...
How to deal with qualitative and quantitative information with various types of uncertainties in the process of evaluating the operational effectiveness (OE) of weapon system accurately is a key issue for the decision makers. Incompleteness and vagueness are among the most common uncertainties. In this paper, an OE evaluation approach and process for weapon system is proposed based on belief structure...
Decision making under uncertainty is a critical problem in the field of software engineering. Predicting the software quality or the cost/ effort requires high level expertise. AI based predictor models, on the other hand, are useful decision making tools that learn from past projects' data. In this study, we have built an effort estimation model for a multinational bank to predict the effort prior...
Evaluating and selecting alternatives from available alternatives with respect to multiple, often conflicting criteria in a group decision making setting is complex and challenging due to the risk associated with the uncertainty and imprecision existent in the human decision making process. To effectively solve this problem, this paper proposes a risk-oriented group decision making approach for adequately...
Organizations have to be competitive in their market throughout the globalization process. Thus, they need to achieve customer demands in strategic ways focusing on customer satisfaction. At this point, decision makers encounter with uncertainties based on reducing the deviation in the production/service processes. The uncertainty problem of supplier selection for a Turkish Machinery Industry Corporation...
A new decision making approach based on the evidential reasoning method is proposed for multi-attribute decision making problem with incomplete information. The approach first defines the basic probability assignment function (BPA) according to the assessment information, and then the BPA values are integrated into a comprehensive one through D-S rule of combination. In the process of combination,...
Grain security warning is very important for decision making of government. How to present a reasonable warning is still an open issue. Due to the uncertainty in the grain security warning process, it is reasonable to construct prediction model under the framework of fuzzy sets theory and Dempster Shafer evidence theory. In this paper, a fuzzy evidential grain security warning method is proposed....
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