Conditional Logic in Expert Systems

This volume is a collection of invited papers on all basic aspects of conditional logic, inference and reasoning in expert systems. Specifically, theoretical results and applications centered around the main task in automated reasoning, namely conditional inference, in the three main approaches to reasoning under uncertainty (Bayesian, Fuzzy sets and Belief functions) including: - Measure-free conditioning, conditioning operators for non-monotonic reasoning; - General approach using logic to conditional inference; - Conditioning reasoning with fuzzy sets; - Random set as a formalism for evidential reasoning; - New results in the theory of Belief functions; - Some aspects of applications to various fields of AI.
 
This volume is a collection of invited papers on all basic aspects of conditional logic, inference and reasoning in expert systems. Specifically, theoretical results and applications centered around the main task in automated reasoning, namely conditional inference, in the three main approaches to reasoning under uncertainty (Bayesian, Fuzzy sets and Belief functions) including: - Measure-free conditioning, conditioning operators for non-monotonic reasoning; - General approach using logic to conditional inference; - Conditioning reasoning with fuzzy sets; - Random set as a formalism for evidential reasoning; - New results in the theory of Belief functions; - Some aspects of applications to various fields of AI.