text_combined: jonathan lawry asuwexbristolacuk modelling reasoning vague concepts jonathan lawry published springer overview vagueness central flexibility robustness natural language descriptions vague concepts robust imprecision perceptions still allowing us convey useful sometimes vital information study vagueness artificial intelligence ai therefore motivated desire incorporate robustness flexibility intelligent computer systems goal however requires formal model vague concepts allow us quantify manipulate uncertainty resulting use means passing information autonomous agents volume outlines formal representation framework modelling reasoning vague concepts artificial intelligence new calculus many applications especially automated reasoning learning data analysis information fusion book gives rigorous introduction label semantics theory illustrated many examples suggests clear operational interpretations proposed measures also provides detailed description theory applied data analysis information fusion based range benchmark problems contents foreword didier dubois chapter 1introduction chapter 2 vague concepts fuzzy sets chapter 3 label semantics chapter 4 multidimensional multiinstance label semantics chapter 5 information vague concepts chapter 6 learning linguistic models data chapter 7 fusing knowledge data chapter 8 nonadditive appropriateness measures book ordered springer website httpwwwspringercomsgwcdafrontpage01185541752286707466details page253dppmmedia257ctoc257ctoc00html wed 06 aug 2008 224906 0000 uai book announcement modelling reasoning vague concepts j lawry