PCE (Probabilistic Consistency Engine)


Notes:

PCE stands for Probabilistic Consistency Engine. It is used for probabilistic inference with Markov Logic as a formal framework. PCE can infer the marginal probabilities of formulas based on facts and rules. PCE is used as a tool for MLN inference. Semantic information is extracted by applying probabilistic inference to the syntactic information, using an MLN capturing the domain-specific rules. As a MAX-SMT solver, Yices is the main component of the probabilistic consistency engine used in SRI’s CALO system.

  • Dynamic Markov logic network

Resources:

  • cvc4.cs.nyu.edu .. open-source automatic theorem prover
  • yices.csl.sri.com .. decides the satisfiability of formulas containing uninterpreted function symbols

Wikipedia:

See also:

PCFG (Probabilistic Context Free Grammar) & Dialog Systems | PLSA (Probabilistic Latent Semantic Analysis) & Dialog Systems | Probabilistic Consistency Engine (PCE) | Probabilistic Graphical Models & Dialog Systems | Probabilistic Parser & Dialog Systems


The yices smt solver B Dutertre, L De Moura – Tool paper at http://yices. csl. sri. com/tool- …, 2006 – yices.csl.sri.com … Yices is the main decision procedure used by the SAL model checking environment, and it is be- ing integrated to the PVS theorem prover. As a MAX-SMT solver, Yices is the main component of the probabilistic consistency engine used in SRI’s CALO system. 1 Introduction … Cited by 552 Related articles All 6 versions

System Description: Yices 1.0 B Dutertre, L de Moura – Proc. on 2nd SMT competition, SMT …, 2006 – smtcomp.cs.uiowa.edu Page 1. System Description: Yices 1.0 Bruno Dutertre and Leonardo de Moura Computer Science Laboratory, SRI International 333 Ravenswood Avenue, Menlo Park, CA 94025 – USA {bruno, demoura}@csl.sri.com 1 Introduction … Cited by 25 Related articles

Machine reading using markov logic networks for collective probabilistic inference S Ghosh, N Shankar, S Owre – In Proceedings of ECML-CoLISD, 2011 – csl.sri.com … Semantic information is then extracted from Page 3. the system by applying probabilistic inference to the syntactic information, using an MLN capturing the domain-specific rules. We use SRI’s Probabilistic Consistency Engine (PCE) for probabilistic inference in MLNs [14]. … Cited by 10 Related articles All 3 versions

Probabilistic Modeling of Failure Dependencies Using Markov Logic Networks S Ghosh, W Steiner, G Denker… – … (PRDC), 2013 IEEE …, 2013 – ieeexplore.ieee.org … machine learning. We illustrate this modeling methodology on example system architectures, and show how the the Probabilistic Consistency Engine (PCE) tool can create and analyze failure-dependency models. We compare … Cited by 1 Related articles All 6 versions

Integrating Multiple Learning Components through Markov Logic. TG Dietterich, X Bao – AAAI, 2008 – aaai.org … w = log P(Class|Object) 1 ? P(Class|Object) , (2) The MPE Architecture Figure 3 shows our first architecture, called the MPE Ar- chitecture. The box labeled PCE denotes the Probabilistic Consistency Engine. This is the inference engine for the Markov Logic system. … Cited by 6 Related articles All 11 versions

Anomaly Detection and Diagnosis for Automatic Radio Network Verification GF Ciocarlie, C Connolly, CC Cheng… – Mobile Networks and …, 2015 – Springer … observed conditions. We use the Probabilistic Consistency Engine (PCE) [ 1 ], a very efficient MLN solver under continuous improvement. We apply … their contributions. References. 1. Probabilistic Consistency Engine. https://?pal … Cited by 1 Related articles All 2 versions

Markov logic networks in health informatics S Ghosh, N Shankar, S Owre, S David… – In Proceedings of ICML …, 2011 – csl.sri.com … person smokes or has cancer. We use the Probabilistic Consistency Engine (PCE) (Owre & Shankar, 2009) tool for MLN inference, in which the specification of this MLN would look like: # Declarations. sort Person; const A, B … Cited by 2 Related articles All 2 versions

Probabilistic, Logical and Relational Learning-A Further Synthesis. L De Raedt, TG Dietterich, L Getoor… – … Learning-A Further …, 2007 – drops.dagstuhl.de … than 25 research groups in the US To integrate the various learning components, and to combine hand-written probabilistic rules with factual and learned knowledge, we implemented and deployed a Markov Logic system that we call the Probabilistic Consistency Engine (PCE). … All 6 versions

Probabilistic Inference with PCE1 N Shankar, S Owre, S Ghosh – 2011 – research.microsoft.com … Page 4. What is PCE? PCE stands for Probabilistic Consistency Engine It is used for probabilistic inference with Markov Logic as a formal framework PCE can infer the marginal probabilities of formulas based on facts and rules. … Related articles

Automated reasoning, fast and slow N Shankar – Automated Deduction–CADE-24, 2013 – Springer … We briefly describe the MC- SAT inference algorithm [31] that is implemented in systems such as Alchemy (http://code.google.com/p/alchemy-2/) and the Probabilistic Consistency Engine (PCE; developed jointly with Sam Owre). … Cited by 1 Related articles All 7 versions

META 2f: Probabilistic, Compositional, Multi-dimension Model-Based Verification (PROMISE) G Denker, L Briesemeister, D Elenius, S Ghosh… – 2011 – DTIC Document … 15 4.3 Results and Discussion ….. 16 4.3.1 Probabilistic Consistency Engine ….. 16 4.3.2 PCE Models and Results ….. … Related articles

Slice normalized dynamic markov logic networks T Papai, H Kautz, D Stefankovic – Advances in Neural Information …, 2012 – papers.nips.cc … increasing weight. 5 Experiments For our experiments we extended the Probabilistic Consistency Engine (PCE) [3], a Markov logic implementation that has been used effectively in different problem domains. For training, we … Cited by 2 Related articles All 16 versions

Slice Normalized Dynamic Markov Logic Networks DRAFT T Papai, H Kautz, D Stefankovic – tsi.wfubmc.edu … increasing weight. 5 Experiments For our experiments we extended the Probabilistic Consistency Engine (PCE) [16], a Markov logic im- plementation that has been used effectively in differ- ent problem domains. For training … Related articles All 2 versions

Combining subjective probabilities and data in training markov logic networks T Pápai, S Ghosh, H Kautz – Machine Learning and Knowledge Discovery …, 2012 – Springer Page 1. Combining Subjective Probabilities and Data in Training Markov Logic Networks Tivadar Pápai1, Shalini Ghosh2, and Henry Kautz1 1 Department of Computer Science,University of Rochester, Rochester, NY {papai … Cited by 5 Related articles All 19 versions

Exploiting constraints, sequential structure, and knowledge in Markov logic networks T Papai – 2013 – urresearch.rochester.edu Page 1. Exploiting Constraints, Sequential Structure, and Knowledge in Markov Logic Networks by Tivadar Papai Submitted in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy Supervised by Professor Henry Kautz … Related articles All 3 versions

Applying machine learning for prediction, recommendation, and integration X Bao – 2009 – ir.library.oregonstate.edu Page 1. Page 2. AN ABSTRACT OF THE DISSERTATION OF Xinlong Bao for the degree of Doctor of Philosophy in Computer Science presented on August 24, 2009. Title: Applying Machine Learning for Prediction, Recommendation, and Integration Abstract approved: … Related articles All 3 versions

Fractionated Software for Networked Cyber-Physical Systems: Research Directions and Long-Term Vision. MO Stehr, CL Talcott, JM Rushby, P Lincoln… – Formal Modeling: Actors, …, 2011 – Springer … Other very promising approaches to the integra- tion of logic and sampling-based analysis techniques are Markov Logic Networks [64] as, for instance, implemented in the Probabilistic Consistency Engine [3] (PCE), which can be used to quantify the probability that a property … Cited by 13 Related articles All 8 versions

Faust: Flexible Acquistion and Understanding System for Text LL Voss, DE Wilkins, D Israel, C Manning, D Jurafsky… – 2013 – DTIC Document Page 1. FAUST: FLEXIBLE ACQUISITION AND UNDERSTANDING SYSTEM FOR TEXT JULY 2013 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED STINFO COPY AIR FORCE RESEARCH LABORATORY … Related articles