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Classic Works of the Dempster-Shafer Theory of Belief Functions
This is a collection of classic research papers on the Dempster-Shafer theory of belief functions. The book is the authoritative reference in the field of evidential reasoning and an important archival reference in a wide range of areas including uncertainty reasoning in artificial intelligence and decision making in economics, engineering, and management. The book includes a foreword reflecting the development of the theory in the last forty years.
An Improved Dempster-Shafer Algorithm Using a Partial Conflict Measurement
Multiple evidences based decision making is an important functionality for computers and robots. To combine multiple evidences, mathematical theory of evidence has been developed, and it involves the most vital part called Dempster’s rule of combination. The rule is used for combining multiple evidences.
Information Fusion on Belief Networks
This paper will focus on the process of “fusing” several observations or models of uncertainty into a single resultant model. Many existing approaches to fusion use subjective quantities such as “strengths of belief” and process these quantities with heuristic algorithms. This paper argues in favor of quantities that can be objectively measured, as opposed to the subjective “strength of belief” values. This paper will focus on probability distributions, and more importantly, structures that denote sets of probability distributions known as “credal sets”. The novel aspect of this paper will be a taxonomy of models of fusion that use specific types of credal sets, namely probability interval distributions and Dempster-Shafer models.
Counter-examples to Dempster’s rule of combination
This chapter presents several classes of fusion problems which cannot be directly approached by the classical mathematical theory of evidence, also known as Dempster-Shafer Theory (DST), either because Shafer’s model for the frame of discernment is impossible to obtain, or just because Dempster’s rule of combination fails to provide coherent results (or no result at all). We present and discuss the potentiality of the DSmT combined with its classical (or hybrid) rule of combination to attack these infinite classes of fusion problems.
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Information Processing and Management of Uncertainty
These three volumes (CCIS 442, 443, 444) constitute the proceedings of the 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2014, held in Montpellier, France, July 15-19, 2014. The 180 revised full papers presented together with five invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on uncertainty and imprecision on the web of data; decision support and uncertainty management in agri-environment; fuzzy implications; clustering; fuzzy measures and integrals; non-classical logics; data analysis; real-world applications; aggregation; probabilistic networ...
Artificial Intelligence
AI is an emerging discipline of computer science. It deals with the concepts and methodologies required for computer to perform an intelligent activity. The spectrum of computer science is very wide and it enables the computer to handle almost every activity, which human beings could. It deals with defining the basic problem from viewpoint of solving it through computer, finding out the total possibilities of solution, representing the problem from computational orientation, selecting data structures, finding the solution through searching the goal in search space dealing the real world uncertain situations etc. It also develops the techniques for learning and understanding, which make the c...
Evolving Ambient Intelligence
This book constitutes the refereed proceedings of the workshops co-located with the 4th International Joint Conference on Ambient Intelligence, AmI 2013, held in Dublin, Ireland, in December 2013. The 33 revised full papers presented were carefully reviewed and selected from numerous submissions to the following workshops: 5th International Workshop on Intelligent Environments Supporting Healthcare and Well-being (WISHWell’13) 3d International workshop on Pervasive and Context-Aware Middleware (PerCAM’13), 2nd International Workshop on Adaptive Robotic Ecologies (ARE'13), International Workshop on Aesthetic Intelligence (AxI'13), First International Workshop on Uncertainty in Ambient Intelligence (UAmI13). The papers are organized in topical sections on intelligent environments supporting healthcare and well-being; adaptive robotic ecologies; uncertainty in ambient intelligence; aesthetic intelligence; pervasive and context-aware middleware.
