The Independent Choice Logic and Beyond
暂无分享,去创建一个
[1] E. Rowland. Theory of Games and Economic Behavior , 1946, Nature.
[2] L. J. Savage,et al. The Foundation of Statistics , 1956 .
[3] Richard C. T. Lee,et al. Symbolic logic and mechanical theorem proving , 1973, Computer science classics.
[4] John Seely Brown,et al. Diagnostic Models for Procedural Bugs in Basic Mathematical Skills , 1978, Cogn. Sci..
[5] J. Lloyd. Foundations of Logic Programming , 1984, Symbolic Computation.
[6] J. W. Lloyd,et al. Foundations of logic programming; (2nd extended ed.) , 1987 .
[7] V. Lifschitz,et al. The Stable Model Semantics for Logic Programming , 1988, ICLP/SLP.
[8] David Poole,et al. Explanation and prediction: an architecture for default and abductive reasoning , 1989, Comput. Intell..
[9] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[10] Murray Shanahan,et al. Prediction is Deduction but Explanation is Abduction , 1989, IJCAI.
[11] David Poole,et al. A methodology for using a default and abductive reasoning system , 1989, Int. J. Intell. Syst..
[12] David Poole,et al. A Dynamic Approach to Probabilistic Inference using Bayesian Networks , 1990, UAI 1990.
[13] Nils J. Nilsson,et al. Logic and Artificial Intelligence , 1991, Artif. Intell..
[14] David L. Poole,et al. Representing Bayesian Networks Within Probabilistic Horn Abduction , 1991, UAI.
[15] David Poole,et al. Representing Diagnostic Knowledge for Probabilistic Horn Abduction , 1991, IJCAI.
[16] Johann Eder,et al. Logic and Databases , 1992, Advanced Topics in Artificial Intelligence.
[17] David Poole,et al. Probabilistic Horn Abduction and Bayesian Networks , 1993, Artif. Intell..
[18] Fabio Gagliardi Cozman,et al. Truncated Gaussians as tolerance sets , 1994 .
[19] Luc De Raedt,et al. Inductive Logic Programming: Theory and Methods , 1994, J. Log. Program..
[20] Wray L. Buntine. Operations for Learning with Graphical Models , 1994, J. Artif. Intell. Res..
[21] David Poole,et al. Probabilistic Conflicts in a Search Algorithm for Estimating Posterior Probabilities in Bayesian Networks , 1996, Artif. Intell..
[22] S. Muggleton. Stochastic Logic Programs , 1996 .
[23] Nevin Lianwen Zhang,et al. Exploiting Causal Independence in Bayesian Network Inference , 1996, J. Artif. Intell. Res..
[24] Craig Boutilier,et al. Context-Specific Independence in Bayesian Networks , 1996, UAI.
[25] Nir Friedman,et al. Learning Bayesian Networks with Local Structure , 1996, UAI.
[26] De Raedt,et al. Advances in Inductive Logic Programming , 1996 .
[27] David Poole,et al. The Independent Choice Logic for Modelling Multiple Agents Under Uncertainty , 1997, Artif. Intell..
[28] David Maxwell Chickering,et al. A Bayesian Approach to Learning Bayesian Networks with Local Structure , 1997, UAI.
[29] David Poole,et al. Probabilistic Partial Evaluation: Exploiting Rule Structure in Probabilistic Inference , 1997, IJCAI.
[30] Randy Goebel,et al. Computational intelligence - a logical approach , 1998 .
[31] Lise Getoor,et al. Learning Probabilistic Relational Models , 1999, IJCAI.
[32] David Poole,et al. Learning, Bayesian Probability, Graphical Models, and Abduction , 2000 .
[33] J. Pearl. Causality: Models, Reasoning and Inference , 2000 .
[34] David Poole,et al. Abducing through negation as failure: stable models within the independent choice logic , 2000, J. Log. Program..
[35] Peter A. Flach,et al. Abduction and induction: essays on their relation and integration , 2000 .
[36] Sebastian Thrun,et al. Towards programming tools for robots that integrate probabilistic computation and learning , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).
[37] Avi Pfeffer,et al. IBAL: A Probabilistic Rational Programming Language , 2001, IJCAI.
[38] Yoshitaka Kameya,et al. Parameter Learning of Logic Programs for Symbolic-Statistical Modeling , 2001, J. Artif. Intell. Res..
[39] Adnan Darwiche,et al. Recursive conditioning , 2001, Artif. Intell..
[40] David Andre,et al. State abstraction for programmable reinforcement learning agents , 2002, AAAI/IAAI.
[41] Stuart J. Russell,et al. Identity Uncertainty and Citation Matching , 2002, NIPS.
[42] Vladimir Lifschitz,et al. Answer set programming and plan generation , 2002, Artif. Intell..
[43] David Allen,et al. New Advances in Inference by Recursive Conditioning , 2002, UAI.
[44] David Poole,et al. First-order probabilistic inference , 2003, IJCAI.
[45] Francisco Javier Díez,et al. Efficient computation for the noisy MAX , 2003, Int. J. Intell. Syst..
[46] Nevin Lianwen Zhang,et al. Exploiting Contextual Independence In Probabilistic Inference , 2011, J. Artif. Intell. Res..
[47] K. Vind. A foundation for statistics , 2003 .
[48] Adnan Darwiche,et al. Uncertainty in artificial intelligence : proceedings of the nineteenth conference (2003), August 7-10, 2003, Acapulco, Mexico , 2003 .
[49] David Heckerman,et al. Probabilistic Models for Relational Data , 2004 .
[50] Stuart J. Russell,et al. BLOG: Probabilistic Models with Unknown Objects , 2005, IJCAI.
[51] Dan Roth,et al. Lifted First-Order Probabilistic Inference , 2005, IJCAI.
[52] Matthew Richardson,et al. Markov logic networks , 2006, Machine Learning.
[53] Prakash P. Shenoy,et al. Inference in hybrid Bayesian networks with mixtures of truncated exponentials , 2006, Int. J. Approx. Reason..
[54] Manfred Jaeger,et al. Compiling relational Bayesian networks for exact inference , 2006, Int. J. Approx. Reason..
[55] Ben Taskar,et al. Bayesian Logic Programming: Theory and Tool , 2007 .
[56] Luc De Raedt,et al. Bayesian Logic Programming: Theory and Tool , 2007 .
[57] David Poole,et al. Logical Generative Models for Probabilistic Reasoning about Existence, Roles and Identity , 2007, AAAI.
[58] David Heckerman,et al. A Tutorial on Learning with Bayesian Networks , 1999, Innovations in Bayesian Networks.
[59] R. Mike Cameron-Jones,et al. Induction of logic programs: FOIL and related systems , 1995, New Generation Computing.
[60] Stephen Muggleton,et al. Inverse entailment and progol , 1995, New Generation Computing.
[61] Krzysztof R. Apt,et al. Acyclic programs , 2009, New Generation Computing.
[62] David Poole,et al. Logic programming, abduction and probability , 1993, New Generation Computing.
[63] J. Nelson Rushton,et al. Probabilistic reasoning with answer sets , 2004, Theory and Practice of Logic Programming.