Generic Inference: A Unifying Theory for Automated Reasoning

List of Instances and Applications

1.1 Indicator Functions, Boolean Functions and Crisp Constraints

1.2 Relational Algebra

1.3 Arithmetic Potentials

1.4 Set Potentials

1.5 Density Functions

1.6 Gaussian Densities and Gaussian Potentials

A.7 Set Potentials on Partition Lattices

A.8 Quotients of Density Functions

2.1 Bayesian Networks

2.2 Query Answering in Relational Databases

2.3 Dempster-Shafer Theory of Evidence

2.4 Satisfiability of Constraints and Propositional Logic

2.5 Hadamard Transform

2.6 Discrete Fourier and Cosine Transforms

B.4 Filtering, Prediction and Smoothing in hidden Markov chains

4.4 Probability Potentials

4.5 Probability Density Functions

D.9 Scaling of Belief Functions

5.1 Weighted Constraints, Spohn Potentials and GAI Preferences

5.2 Possibility Potentials, Probabilistic Constraints and Fuzzy Sets

5.3 Set-based Constraints and Assumption-based Reasoning

5.3 Possibility Measures

5.3 Disbelief Functions

E.15 Quasi-Spohn Potentials

E.18 Bottleneck Constraints

6.1 Connectivity Path Problem

6.2 Shortest and Longest Distance Problem

6.3 Maximum Capacity Problem

6.4 Maximum Reliability Problem

6.5 Regular Languages

6.6 Path Counting Problem

6.7 Markov Chains

6.8 Numeric Partial Differentiation

6.9 Matrix Multiplication

F.1 Path Listing Problems

F.2 Testing whether Graphs are Bipartite

F.3 Identifying Cut Nodes in Graphs

F.6 Network Compilation

F.6 Symbolic Partial Differentiation

7.1 Satisfiability in Propositional Logic

7.2 Theorem Proving in Propositional Logic ...