Belief networks with decision graphs

Data processing: artificial intelligence – Knowledge processing system – Creation or modification

Patent

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

706 45, G06N 500, G06N 502

Patent

active

061547360

ABSTRACT:
An improved belief network is provided for assisting users in making decisions. The improved belief network utilizes a decision graph in each of its nodes to store the probabilities for that node. A decision graph is a much more flexible and efficient data structure for storing probabilities than either a tree or a table, because a decision graph can reflect any equivalence relationships between the probabilities and because leaf nodes having equivalent probabilities need not be duplicated. Additionally, by being able to reflect an equivalency relationship, multiple paths (or combinations of the parent values) refer to the same probability, which yields a more accurate probability.

REFERENCES:
patent: 5696884 (1997-12-01), Heckerman et al.
patent: 5704017 (1997-12-01), Heckerman et al.
patent: 5704018 (1997-12-01), Heckerman et al.
patent: 5715374 (1998-02-01), Heckerman et al.
patent: 5802256 (1998-09-01), Heckerman et al.
Boutilier, Craig et al., "Context-Specific Independence in Bayesian Networks," Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence (UAI-96), Portland, Oregon, Aug. 1997, pp. 115-123.
Chickering, David Maxwell et al., "A Bayesian Approach to Learning Bayesian Networks with Local Structure," Technical Report MSR-TR-97-06, Microsoft Research, Redmond, Washington, Mar. 1997, pp. 1-22.
Friedman, Nir and Goldszmidt, Moises, "Discretizing Continuous Attributes While Learning Bayesian Networks," pp. 157-165.
Friedman, Nir and Goldszmidt, "Building Classifiers Using Bayesian Networks," pp. 1277-1284.
Friedman, Nir and Goldszmidt, "Learning Bayesian Networks with Local Structure," pp. 252-262.
Tukey, John W., Exploratory Data Analysis, Addison-Wesley Publishing Company, Inc., Redding, Massachusetts, 1977, preface and table of contents.
Zhaoyu Li; D'Ambrosio, B., A framework for ordering composite beliefs in belief networks, Systems, Man and Cybernetics, IEEE Transactions on, vol.: 25 2, Feb. 1995, pp: 243-255.
Dagum, P.; Chavez, R.M., Approximating probabilistic inference in Bayesian belief networks, Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.: 15 3, Mar. 1993 , pp.: 246-255.
Sarkar, S., Modeling uncertainty using enhanced tree structures in expert systems, Systems, Man and Cybernetics, IEEE Transactions on, vol.: 25 4, Apr. 1995 , pp.: 592-604.
Yiqun Gu; Peiris, D.R.; Crawford, J.W.; NcNicol, J.W.; Marshall, B.; Jefferies, R.A., An application of belief networks to future crop production, Artificial Intelligence for Applications, Jan. 1994., Proceedings of the Tenth Conference on , Jan. 1994, pp.: 3.
Abdelbar, A.M.; Hedetniemi, S.M., A parallel hybrid genetic algorithm simulated annealing approach to finding most probable explanations on Bayesian belief networks, Neural Networks, Jan. 1997., International Conference on, vol: 1 , 1997 , pp: 450-455, Jan. 1997.
Shang-Hua Wang; Hung-Tat Tsui, Dynamic structuring of belief networks in a hierarchical perceptual organization, Speech, Image Processing and Neural Networks, 1994. Proceedings, ISSIPNN '94., 1994 International Symposium on, 1994 , pp.: 519-522 vol. 2, Jan. 1997.
Sarkar, S.; Murthy, I., Constructing efficient belief network structures with expert provided information, Knowledge and Data Engineering, IEEE Transactions on, vol.: 8 1 , Feb. 1996, pp.: 134-143.
Deleu, J.; Beuscart, R.; Becquart, E.; Duhamel, A.; Comyn, G., Comparison of a probabilistic network and an expert system, Engineering in Medicine and Biology Society, Jan. 1988., Proceedings of the Annual International Conference of the IEEE , 1988 , pp:.
Abramson, B.; Ng, K.-C., Toward an art and science of knowledge engineering: a case for belief networks, Knowledge and Data Engineering, IEEE Transactions on, vol.: 5 4 , Aug. 1993, pp.: 705-.
Low, B.T., Neural-Logic Belief Networks-A tool for knowledge representation and reasoning, Tools with Artificial Intelligence, Jan. 1993. TAI '93. Proceedings., Fifth Interntional Conference on , Jan. 1993 , pp.: 34-37.
Saxena, N.; Sarkar, S.; Ranganathan, N., Mapping and parallel implementation of Bayesian belief networks Parallel and Distributed Processing, 1996., Eighth IEEE Symposium on , Jan. 1996 , pp.: 608-611.
Suzuki, J., An extension on learning Bayesian belief networks based on MDL principle, Information Theory, 1995. Proceedings., 1995 IEEE International Symposium on, Jan. 1995, p.: 232.
Bellazzi, R.; Quaglini, S.; Berzuini, C., GAMEES II: an environment for building probabilistic expert systems based on arrays of Bayesian belief networks, Computer-Based Medical Systems, 1992. Proceedings., Fifth Annual IEEE Symposium on, Jan. 1992, p.: 5.
Gebhardt, J; Kruse, R., Learning possibilistic networks from data, Fuzzy Systems, Feb. 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of, Jan. 1995.
Wang, Shang-Hua et al., Dynamic Structuring of Belief Networks in a Heirarchical Perceptual Organization., ISSIPNN '94. 1994 International Symposium on Speech, Image Processing, and Neural Networks Proceedings (Cat. No. 94TH0638-7) New York, NY, IEEE, 199, Apr. 1994.
Breese, J.S.; Heckerman, D., Decision-theoretic case-based reasoning, Systems, Man and Cybernetics, Part A, IEEE Transactions on, vol.: 26 6 , Nov. 1996 , pp.: 838-842.
Heckerman, D.; Breese, J.S., Causal independence for probability assessment and inference using Bayesian networks, Systems, Man and Cybernetics, Part A, IEEE Transactions on, vol.: 26 6 , Nov. 1996 , pp.: 838-842.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Belief networks with decision graphs does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Belief networks with decision graphs, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Belief networks with decision graphs will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-1735092

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.