Propositional DAGs: A new graph-based language for representing Boolean functions

Proceedings of the International Conference on Knowledge Representation and Reasoning

Volumn , Issue , 2006, Pages 277-285

  Wachter, Michael ^a   Haenni, Rolf ^a  

^a UNIVERSITY OF BERN   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

BINARY DECISION DIAGRAMS; DIRECTED GRAPHS; GRAPHIC METHODS; KNOWLEDGE REPRESENTATION;

BINARY DECISION DIAGRAMS (BDD); DIRECTED ACYCLIC GRAPH (DAG); GRAPH-BASED LANGUAGES; KNOWLEDGE COMPILATION; NORMAL FORM; PROPOSITIONAL THEORIES; TARGET LANGUAGE;

BOOLEAN FUNCTIONS;

EID: 37249017714     PISSN: 23341025     EISSN: 23341033     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (23)

1. Akers, S. B. 1978. Binary decision diagrams. IEEE Transactions on Computers 27(6):509-516.
2. Andersen, H. R., and Hulgaard, H. 1997. Boolean expression diagrams. In Winskel, G., ed., LICS'97, 12th Annual IEEE Symposim on Logic in Computer Science, 88- 98. Warsaw, Poland: IEEE Computer Society.
3. Blum, M.; Chandra, A. K.; and Wegman, M. N. 1980. Equivalence of free boolean graphs can be decided probabilistically in polynomial time. Information Processing Letters 10(2):80-82.
4. Boole, G. 1854. The Laws of Thought. London: Walton and Maberley.
5. Bryant, R. E. 1986. Graph-based algorithms for Boolean function manipulation. IEEE Transactions on Computers 35(8):677-691.
6. Bryant, R. E. 1992. Symbolic Boolean manipulation with ordered binary decision diagrams. ACM Computing Surveys 24(3):293-318.
7. Cadoli, M., and Donini, F. 1997. A survey on knowledge compilation. AI Communications 10(3-4):137-150.
8. Clote, P., and Kranakis, E. 1998. Boolean Functions and Computation Models. Springer.
9. Darwiche, A., and Huang, J. 2002. Testing equivalence probabilistically. Technical Report D-123, Computer Science Department, UCLA, Los Angeles, USA.
10. Darwiche, A., and Marquis, P. 2002. A knowlege compilation map. Journal of Artificial Intelligence Research 17:229-264.
11. Darwiche, A. 1999. Compiling knowledge into decomposable negation normal form. In IJCAI'99, 16th International Joint Conference on Artificial Intelligence, 284-289.
12. Darwiche, A. 2001a. Decomposable negation normal form. Journal of ACM 48(4):608-647.
13. Darwiche, A. 2001b. On the tractability of counting theory models and its application to belief revision and truth maintenance. Journal of Applied Non-Classical Logics 11(1- 2):11-34.
14. Darwiche, A. 2002. A compiler for deterministic, decomposable negation normal form. In AAAI'02, 18th National Conference on Artificial Intelligence, 627-634. AAAI Press.
15. Gross, J. L., and Yellen, J. 2003. Handbook of Graph Theory. CRC Press.
16. Hill, F. J., and Peterson, G. R. 1974. Introduction to Switching Theory and Logical Design. New York, USA: John Wiley and Sons.
17. Jain, J.; Bitner, J.; Fussell, D. S.; and Abraham, J. A. 1991. Probabilistic design verification. In ICCAD'91, International Conference on Computer-Aided Design, 468-471.
18. Kohlas, J. 2003. Information Algebras: Generic Stuctures for Inference. London: Springer.
19. Papadimitriou, C. 1994. Computational Complexity. Addison-Wesley.
20. Rai, S.; Veeraraghavan, M.; and Trivedi, K. S. 1995. A survey on efficient computation of reliability using disjoint products approach. Networks 25(3):147-163.
21. Rauzy, A.; Cĥatelet, E.; Dutuit, Y.; and Brenguer, C. 2003. A practical comparison of methods to assess sumof- products. Reliability Engineering and System Safety 79(1):33-42.
22. Verma, T. S., and Pearl, J. 1992. An algorithm for deciding if a set of observed independencies has a causal explanation. In Dubois, D., and Wellman, M. P., eds., UAI'92, 8th Conference on Uncertainty in Artificial Intelligence, 323- 330.
23. Wachter, M., and Haenni, R. 2006. Probabilistic equivalence checking with propositional DAGs (submitted). In CAV'06, 18th Conference on Computer-Aided Verification.