Model Averaging for Prediction with Discrete Bayesian Networks
The Journal of Machine Learning Research
U-director: a decision-theoretic narrative planning architecture for storytelling environments
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Bayesian networks for imputation in classification problems
Journal of Intelligent Information Systems
International Journal of Hybrid Intelligent Systems - HIS 2007
Implementing tutoring strategies into a patient simulator for clinical reasoning learning
Artificial Intelligence in Medicine
Efficient computation of jointree bounds for systematic MAP search
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Equipping robot control programs with first-order probabilistic reasoning capabilities
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Adding diagnostics to intelligent robot systems
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Design and implementation of a Bayesian network speech recognizer
TSD'10 Proceedings of the 13th international conference on Text, speech and dialogue
Modeling narrative-centered tutorial decision making in guided discovery learning
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Robust independence testing for constraint-based learning of causal structure
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Clinical reasoning learning with simulated patients
AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine
Director agent intervention strategies for interactive narrative environments
ICIDS'11 Proceedings of the 4th international conference on Interactive Digital Storytelling
AdNext: a visit-pattern-aware mobile advertising system for urban commercial complexes
Proceedings of the 12th Workshop on Mobile Computing Systems and Applications
Bayesian network structure learning from limited datasets through graph evolution
EuroGP'12 Proceedings of the 15th European conference on Genetic Programming
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
A memetic approach to bayesian network structure learning
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
Impact of precision of Bayesian network parameters on accuracy of medical diagnostic systems
Artificial Intelligence in Medicine
Bayesian network modeling of Port State Control inspection findings and ship accident involvement
Expert Systems with Applications: An International Journal
Transgenic: An evolutionary algorithm operator
Neurocomputing
| Hi-index | 0.00 |
SMILE (Structural Modeling, Inference, and Learning Engine) is a fully portable library of C++ classes implementing graphical decision-theoretic methods, such as Bayesian networks and influence diagrams, directly amenable to inclusion in intelligent systems. Its Windows user interface, GeNIe is a versatile and user-friendly development environment for graphical decision-theoretic models. Both modules, developed at the Decision Systems Laboratory, University of Pittsburgh, have been made available to the community in July 1998 at http://www2.sis.pitt.edu/~genie and have over 1,200 users worldwide (as of April 1999). This document summarizes the basic features of GeNIe and SMILE