Special Track on Uncertain Reasoning, proceedings of FLAIRS'14
Abstract
Many problems in AI require an intelligent agent to operate with incomplete or uncertain information, for example, in reasoning, planning, learning, perception and robotics. The objective of this track is to present and discuss a broad and diverse range of current work on uncertain reasoning, including theoretical and applied research based on different paradigms. We hope that the variety and richness of this track will help to promote cross-fertilization among the different approaches for uncertain reasoning, and in this way foster the development of new ideas and paradigms.
Keywords
Bayesian networks
graphical models of uncertainty
multiagent uncertain reasoning and decision making
approximate and qualitative uncertain reasoning
possibility
fuzzy logic
Belief function
granularity
rough sets
Probability logics
modeling and reasoning using imprecise and indeterminate information
comparative orderings
convex sets of measures
Interval-valued probabilities
exact
vagueness
reasoning with probability
calculi and methodologies
uncertain reasoning formalisms
decision-theoretic planning
temporal reasoning and uncertainty
conditional logics
nonmonotonic reasoning
Markov decision process
argumentation
belief change and merging
similarity-based reasoning
data mining and knowledge discovery
construction of models from elicitation
practical applications of uncertain reasoning