Notes:

Probabilistic Consistency Engine (PCE) is a tool for probabilistic inference based on Markov Logic, which is a formal framework for representing and reasoning about probabilistic knowledge. PCE is used to infer the marginal probabilities of formulas based on facts and rules, and it can be used as a tool for Markov Logic Network (MLN) inference.

PCE is often used to extract semantic information from syntactic information by applying probabilistic inference to an MLN that captures domain-specific rules. Yices, a MAX-SMT solver, is a main component of PCE that is used in SRI’s CALO (Cognitive Assistant that Learns and Organizes) system.

A dynamic Markov logic network (D-MLN) is a probabilistic graphical model that is used to represent and reason about dynamic systems and processes. It is a type of Markov logic network (MLN) that is specifically designed to handle temporal or sequential data, and to model the evolution of a system over time.

D-MLN combines the principles of Markov networks, which are used to represent probabilistic dependencies between variables, with the principles of logic programming, which are used to represent logical rules and constraints. This allows D-MLN to represent complex, probabilistic relationships between variables and to reason about these relationships in a flexible and expressive way.

Probabilistic Consistency Engine (PCE) is a tool for probabilistic inference that can be used with D-MLN to perform probabilistic reasoning and make predictions about dynamic systems. PCE is designed to work with MLN as a formal framework, and it can be used to infer the marginal probabilities of formulas based on facts and rules.

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

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**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