First-order mixed integer linear programming

Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009

Volumn , Issue , 2009, Pages 213-222

  Gordon, Geoffrey J ^a   Hong, Sue Ann ^a   Dudík, Miroslav ^a  

^a Carnegie Mellon University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER CIRCUITS; DECISION MAKING; FORMAL LOGIC; FORMAL METHODS;

DECISION-MAKING PROBLEM; FIRST ORDER; FIRST ORDER LOGIC; MIXED-INTEGER LINEAR PROGRAMMING; PROPOSITIONAL LOGIC; SOUND AND COMPLETE;

INTEGER PROGRAMMING;

EID: 80053138449     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. M. Alighanbari and J. P. How. Cooperative task assignment of unmanned aerial vehicles in adversarial environments. In Proc. IEEE American Control Conference (ACC), 2005.
2. V. Borkar, V. Chandru, and S. Mitter. Mathematical programming embeddings of logic. Journal of Automatic Reasoning, 2002.
3. R. Braz, E. Amir, and D. Roth. Lifted first-order probabilistic inference. In IJCAI-05, 2005.
4. Vijay Chandru and John Hooker. Optimization methods for logical inference. Wiley, New York, 1999.
5. B. C. Eaves and U. G. Rothblum. Formulation of linear problems and solution by a universal machine. Mathematical Programming, 65(1-3), 1994.
6. R. Fourer, D. M. Gay, and B. W. Kernighan. AMPL: A Modeling Language for Mathematical Programming. Duxbury Press, 2002. http://ampl.com.
7. R. E. Gomory. Outline of an algorithm for integer solutions to linear programs. Bull. Amer. Math. Soc., 64(5):275-278, 1958.
8. G. Gordon, S. A. Hong, and M. Dudík. First-order mixed integer linear programming. Technical Report CMU-ML-09-108, 2009.
9. D. Heckerman, C. Meek, and D. Koller. Probabilistic entityrelationship models, PRMs, and plate models. In Lise Getoor and Ben Taskar, editors, Introduction to statistical relational learning, chapter 7. MIT Press, 2007.
10. J. N. Hooker and M. A. Osrio. Mixed logical/linear programming. Discrete Applied Mathematics, 96-97:395-442, 1999.
11. B. Milch, B. Marthi, D. Sontag, S. Russell, and D. L. Ong. BLOG: Probabilistic models with unknown objects. In IJCAI-05, 2005.
12. A. Pfeffer. IBAL: A probabilistic rational programming language. In IJCAI-01, 2001.
13. D. Poole. The independent choice logic and beyond. Probabilistic Inductive Logic Programming: Theory and Application, LNAI, 2008.
14. W. B. Powell. A stochastic formulation of the dynamic assignment problem, with an application to truckload motor carriers. Transportation Sci., 30(3):195-219, 1996. (Pubitemid 126605104)
15. M. Richardson and P. Domingos. Markov logic networks. Machine Learning, 62:107-136, 2006. (Pubitemid 43202307)
16. D. Roth and W. Yih. Integer linear programming inference for conditional random fields. In ICML-05, 2005.
17. S. Russell and P. Norvig. Artificial Intelligence: A modern Approach. Pearson Education, Inc., 2003.
18. T. Sandholm, A. Gilpin, and V. Conitzer. Mixed-integer programming methods for finding Nash equilibria. In AAAI-05, 2005.
19. P. Singla and P. Domingos. Markov logic in infinite domains. In UAI-07, 2007.
20. P. Singla and P. Domingos. Lifted first-order belief propagation. In AAAI-08, 2008.
21. T. Vossen, M. Ball, and R. H. Smith. On the use of integer programming models in AI planning. In IJCAI-99, 1999.
22. L. Wolsey and G. L. Nemhauser. Integer and Combinatorial Optimization. John Wiley & Sons, Inc., New York, 1988.