Probabilistic Reasoning in Expert Systems

Background: probabilistic considerations; graph theoretic considerations; rule based expert systems: subjective Bayesian method; the odds method; causal networks: the use of causal networks in expert systems; fusion, propagation and structuring in causal networks; "marrying" and "filling in" in causal networks; maximum entropy methods in causal networks; abductive inference - the set covering method; the probabilistic causal model; the odds method applied to set covering; higher order probabilities - the use of intervals instead of point values; the use of causal networks to express uncertainty in point values.