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ORCIDGregory M. Provan
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- affiliation: University College Cork, Department of Computer Science
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2020 – today
- 2024
[j23]Gregory M. Provan
:
Formal Methods for Autonomous Vehicles. IT Prof. 26(1): 50-56 (2024)- [c93]Killian Nolan, Darijo Raca, Gregory M. Provan, Ahmed H. Zahran:
MATURE: Multistage Throughput Prediction for Adaptive Video Streaming in Cellular Networks. NOSSDAV 2024: 15-21 - 2023
- [j22]Gregory M. Provan:
Toward Explainable AutoEncoder-Based Diagnosis of Dynamical Systems. Algorithms 16(4): 178 (2023) - [j21]Mazen Azzam, Liliana Pasquale, Gregory M. Provan, Bashar Nuseibeh:
Forensic readiness of industrial control systems under stealthy attacks. Comput. Secur. 125: 103010 (2023) - [j20]Mazen Azzam, Liliana Pasquale, Gregory M. Provan, Bashar Nuseibeh:
Efficient Predictive Monitoring of Linear Time-Invariant Systems Under Stealthy Attacks. IEEE Trans. Control. Syst. Technol. 31(2): 735-747 (2023) - [c92]Gregory M. Provan, Yves Sohege:
Robust Embedded Control using Randomized Switching Algorithms. ECC 2023: 1-6 - [c91]Ruth Helen Bergin, Marco Dalla, Andrea Visentin, Barry O'Sullivan, Gregory M. Provan:
Using Machine Learning Classifiers in SAT Branching [Extended Abstract]. SOCS 2023: 169-170 - 2022
- [j19]Mazen Azzam, Liliana Pasquale, Gregory M. Provan, Bashar Nuseibeh:
Grounds for Suspicion: Physics-Based Early Warnings for Stealthy Attacks on Industrial Control Systems. IEEE Trans. Dependable Secur. Comput. 19(6): 3955-3970 (2022) - [c90]Gregory M. Provan, Marcos Quiñones-Grueiro, Yves Sohege:
Generating Minimal Controller Sets for Mixing MMAC. CDC 2022: 3009-3014 - [i16]Eleftherios E. Vlahakis, Gregory M. Provan, Gordon Werner, Shanchieh Yang, Nikolaos Athanasopoulos:
Quantifying impact on safety from cyber-attacks on cyber-physical systems. CoRR abs/2211.12196 (2022) - 2021
- [c89]Yves Sohege, Marcos Quiñones-Grueiro, Gregory M. Provan:
A Novel Hybrid Approach for Fault-Tolerant Control of UAVs based on Robust Reinforcement Learning. ICRA 2021: 10719-10725 - [i15]Mazen Azzam, Liliana Pasquale, Gregory M. Provan, Bashar Nuseibeh:
Efficient Predictive Monitoring of Linear Time-Invariant Systems Under Stealthy Attacks. CoRR abs/2106.02378 (2021) - [i14]Mazen Azzam, Liliana Pasquale, Gregory M. Provan, Bashar Nuseibeh:
Grounds for Suspicion: Physics-based Early Warnings for Stealthy Attacks on Industrial Control Systems. CoRR abs/2106.07980 (2021) - 2020
- [c88]Riccardo Orizio, Satyanarayana Vuppala, Stylianos Basagiannis, Gregory M. Provan:
Towards an Explainable Approach for Insider Threat Detection: Constraint Network Learning. IDSTA 2020: 42-49
2010 – 2019
- 2019
- [c87]Gregory M. Provan, Yves Sohege:
Fault-Tolerant Control for Unseen Faults using Randomized Methods. SysTol 2019: 159-164 - 2018
- [c86]Yves Sohege, Gregory M. Provan:
On-line Reinforcement Learning for Trajectory Following with Unknown Faults. AICS 2018: 291-302 - [c85]Gregory M. Provan, Yves Sohege:
Comparison of Control and Cooperation Frameworks for Blended Autonomy. ECC 2018: 1-7 - 2017
- [c84]Gregory M. Provan:
An Algebraic Approach for Diagnosing Discrete-Time Hybrid Systems. DX 2017: 37-51 - [c83]Yves Sohege, Gregory M. Provan:
Comparing Switching vs. Mixing MPC for Robust Fault-Tolerant Control. DX 2017: 110-123 - 2016
- [c82]Gregory M. Provan:
Learning Dynamical Models Using System Motifs. AICS 2016: 161-172 - [c81]Weipéng Huáng, Gregory M. Provan:
An Improved State Filter Algorithm for SIR Epidemic Forecasting. ECAI 2016: 524-532 - [c80]Gregory M. Provan:
A General Characterization of Model-Based Diagnosis. ECAI 2016: 1565-1566 - 2015
- [j18]Séamus Ó Buadhacháin, Gregory M. Provan:
An efficient decentralized clustering algorithm for aggregation of noisy multi-mean data. J. Heuristics 21(2): 301-328 (2015) - [c79]Gregory M. Provan:
Bayesian Model Selection for Diagnostics. MEDI 2015: 248-256 - [c78]Gregory M. Provan, Alexander Feldman:
A Framework For Assessing Diagnostics Model Fidelity. DX 2015: 127-134 - 2014
- [j17]Ji Ma, David P. Murphy, Gregory M. Provan, S. Cian O'Mathuna, Michael Hayes:
The Evaluation of Direct Volume Rendering-Based Uncertainty Visualization Techniques for 3D Scalar Data. Int. J. Image Graph. 14(4) (2014) - [c77]Alexander Feldman, Gregory M. Provan:
Diagnosing Analogue Linear Systems Using Dynamic Topological Reconfiguration. AAAI 2014: 2644-2651 - [c76]Gregory M. Provan:
A Contracts-Based Framework for Systems Modeling and Embedded Diagnostics. SEFM Workshops 2014: 131-143 - [i13]Alexander Feldman, Gregory M. Provan, Arjan J. C. van Gemund:
Approximate Model-Based Diagnosis Using Greedy Stochastic Search. CoRR abs/1401.3848 (2014) - [i12]Alexander Feldman, Gregory M. Provan, Arjan J. C. van Gemund:
A Model-Based Active Testing Approach to Sequential Diagnosis. CoRR abs/1401.3850 (2014) - [i11]Adnan Darwiche, Gregory M. Provan:
Query DAGs: A Practical Paradigm for Implementing Belief Network Inference. CoRR abs/1408.1480 (2014) - 2013
- [c75]Séamus Ó Buadhacháin, Gregory M. Provan:
A model-based control method for decentralized calibration of wireless sensor networks. ACC 2013: 6571-6576 - [c74]Alexander Feldman, Gregory M. Provan:
Toward an Equation-Oriented Framework for Diagnosis of Complex Systems. EOOLT 2013: 65-74 - [c73]Lior Rokach, Meir Kalech, Gregory M. Provan, Alexander Feldman:
Machine-Learning-Based Circuit Synthesis. IJCAI 2013: 1635-1641 - [c72]Ji Ma, David P. Murphy, Gregory M. Provan, S. Cian O'Mathuna, Michael Hayes:
The Evaluation of Perceptual Effectiveness of Isosurface Rendering-based Uncertainty Visualization Techniques for Volumetric Scalar Data. TPCG 2013: 25-32 - [i10]Adnan Darwiche, Gregory M. Provan:
A Standard Approach for Optimizing Belief Network Inference using Query DAGs. CoRR abs/1302.1532 (2013) - [i9]Max Henrion, Malcolm Pradhan, Brendan Del Favero, Kurt Huang, Gregory M. Provan, Paul O'Rorke:
Why Is Diagnosis Using Belief Networks Insensitive to Imprecision In Probabilities? CoRR abs/1302.3582 (2013) - [i8]Gregory M. Provan:
Abstraction in Belief Networks: The Role of Intermediate States in Diagnostic Reasoning. CoRR abs/1302.4979 (2013) - [i7]Max Henrion, Gregory M. Provan, Brendan Del Favero, Gillian Sanders:
An Experimental Comparison of Numerical and Qualitative Probabilistic Reasoning. CoRR abs/1302.6818 (2013) - [i6]Malcolm Pradhan, Gregory M. Provan, Blackford Middleton, Max Henrion:
Knowledge Engineering for Large Belief Networks. CoRR abs/1302.6839 (2013) - [i5]Gregory M. Provan:
Tradeoffs in Constructing and Evaluating Temporal Influence Diagrams. CoRR abs/1303.1458 (2013) - [i4]Gregory M. Provan:
Dynamic Network Updating Techniques For Diagnostic Reasoning. CoRR abs/1303.5739 (2013) - [i3]David L. Poole, Gregory M. Provan:
What is an Optimal Diagnosis? CoRR abs/1304.1087 (2013) - [i2]Gregory M. Provan:
A Logical Interpretation of Dempster-Shafer Theory, with Application to Visual Recognition. CoRR abs/1304.1523 (2013) - 2012
- [j16]Virag Sharma, David P. Murphy, Gregory M. Provan, Pavel V. Baranov:
CodonLogo: a sequence logo-based viewer for codon patterns. Bioinform. 28(14): 1935-1936 (2012) - [c71]Roni Tzvi Stern, Meir Kalech, Alexander Feldman, Gregory M. Provan:
Exploring the Duality in Conflict-Directed Model-Based Diagnosis. AAAI 2012: 828-834 - [c70]Ji Ma, David P. Murphy, S. Cian O'Mathuna, Michael Hayes, Gregory M. Provan:
Visualizing uncertainty in multi-resolution volumetric data using marching cubes. AVI 2012: 489-496 - [c69]Ji Ma, David P. Murphy, S. Cian O'Mathuna, Michael Hayes, Gregory M. Provan:
Iso-Surface Rendering based Uncertainty Visualization for Multi-resolution Volume Data with Regular Grids. GRAPP/IVAPP 2012: 751-754 - [c68]Alie El-Din Mady, Gregory M. Provan, Ning Wei:
Designing cost-efficient wireless sensor/actuator networks for building control systems. BuildSys@SenSys 2012: 138-144 - [c67]Ji Ma, David P. Murphy, S. Cian O'Mathuna, Michael Hayes, Gregory M. Provan:
Analyzing and Visualizing Multivariate Volumetric Scalar Data and Their Uncertainties. TPCG 2012: 61-68 - 2011
- [c66]Alie El-Din Mady, Gregory M. Provan, Conor Ryan, Kenneth N. Brown:
Stochastic Model Predictive Controller for the Integration of Building Use and Temperature Regulation. AAAI 2011: 1371-1376 - [c65]Alie El-Din Mady, Gregory M. Provan:
Co-design of Wireless Sensor-Actuator Networks for building controls. CDC/ECC 2011: 5266-5273 - [c64]Gregory M. Provan:
Using Equation-Based Languages for Generating Embedded Code for Smart Building Applications. EOOLT 2011: 87-96 - [c63]Ji Ma, David P. Murphy, S. Cian O'Mathuna, Michael Hayes, Gregory M. Provan:
Model and Visualise the Relationship between Energy Consumption and Temperature Distribution in Cold Rooms. TPCG 2011: 71-72 - 2010
- [j15]David W. Aha, Mark S. Boddy, Vadim Bulitko, Artur S. d'Avila Garcez, Prashant Doshi, Stefan Edelkamp, Christopher W. Geib, Piotr J. Gmytrasiewicz, Robert P. Goldman, Pascal Hitzler, Charles L. Isbell Jr., Darsana P. Josyula, Leslie Pack Kaelbling, Kristian Kersting, Maithilee Kunda, Luís C. Lamb, Bhaskara Marthi, Keith McGreggor, Vivi Nastase, Gregory M. Provan, Anita Raja, Ashwin Ram, Mark O. Riedl, Stuart Russell, Ashish Sabharwal, Jan-Georg Smaus, Gita Sukthankar, Karl Tuyls, Ron van der Meyden, Alon Y. Halevy, Lilyana Mihalkova, Sriraam Natarajan:
Reports of the AAAI 2010 Conference Workshops. AI Mag. 31(4): 95-108 (2010) - [j14]Alexander Feldman, Gregory M. Provan, Arjan J. C. van Gemund:
Approximate Model-Based Diagnosis Using Greedy Stochastic Search. J. Artif. Intell. Res. 38: 371-413 (2010) - [j13]Alexander Feldman, Gregory M. Provan, Arjan J. C. van Gemund:
A Model-Based Active Testing Approach to Sequential Diagnosis. J. Artif. Intell. Res. 39: 301-334 (2010) - [j12]Peter Struss, Gregory M. Provan, Johan de Kleer, Gautam Biswas:
Special Issue on Model-Based Diagnostics. IEEE Trans. Syst. Man Cybern. Part A 40(5): 870-873 (2010) - [j11]Jun Wang, Gregory M. Provan:
A Benchmark Diagnostic Model Generation System. IEEE Trans. Syst. Man Cybern. Part A 40(5): 959-981 (2010) - [c62]Gregory M. Provan, Ashish Sabharwal:
Preface. Abstraction, Reformulation, and Approximation 2010 - [c61]Marion Behrens, Gregory M. Provan:
Temporal Model-Based Diagnostics Generation for HVAC Control Systems. ICMT@TOOLS 2010: 31-44 - [c60]Alie El-Din Mady, Menouer Boubekeur, Gregory M. Provan:
WSAN QoS Driven Control Model for Building Operations. SOCO 2010: 237-247 - [c59]Alie El-Din Mady, Menouer Boubekeur, Gregory M. Provan, Conor Ryan, Kenneth N. Brown:
Intelligent Hybrid Control Model for Lighting Systems Using Constraint-Based Optimisation. SOCO 2010: 249-259
2000 – 2009
- 2009
- [j10]Jun Wang, Gregory M. Provan:
Topological Analysis of Specific Spatial Complex Networks. Adv. Complex Syst. 12(1): 45-71 (2009) - [c58]Jun Wang, Gregory M. Provan:
Characterizing the Structural Complexity of Real-World Complex Networks. Complex (1) 2009: 1178-1189 - [c57]Jun Wang, Gregory M. Provan:
A Comparative Analysis of Specific Spatial Network Topological Models. Complex (2) 2009: 1514-1525 - [c56]Alexander Feldman, Gregory M. Provan, Arjan J. C. van Gemund:
FRACTAL: Efficient Fault Isolation Using Active Testing. IJCAI 2009: 778-784 - [c55]Alexander Feldman, Gregory M. Provan, Arjan J. C. van Gemund:
Solving Strong-Fault Diagnostic Models by Model Relaxation. IJCAI 2009: 785-790 - [c54]A. Mady, Menouer Boubekeur, Gregory M. Provan:
Compositional model-driven design of embedded code for energy-efficient buildings. INDIN 2009: 250-255 - [c53]Marion Behrens, Gregory M. Provan, Menouer Boubekeur, A. Mady:
Model-driven diagnostics generation for industrial automation. INDIN 2009: 708-714 - [c52]Alexander Feldman, Gregory M. Provan, Johan de Kleer, Lukas D. Kuhn, Arjan J. C. van Gemund:
Automated Redesign with the General Redesign Engine. SARA 2009 - 2008
- [c51]Jun Wang, Gregory M. Provan:
Generating Application-Specific Benchmark Models for Complex Systems. AAAI 2008: 566-571 - [c50]Alexander Feldman, Gregory M. Provan, Arjan J. C. van Gemund:
Computing Minimal Diagnoses by Greedy Stochastic Search. AAAI 2008: 911-918 - [c49]Alexander Feldman, Gregory M. Provan, Arjan J. C. van Gemund:
Computing Observation Vectors for Max-Fault Min-Cardinality Diagnoses. AAAI 2008: 919-924 - [c48]Alberto Venturini, Gregory M. Provan:
Incremental Algorithms for Approximate Compilation. AAAI 2008: 1495-1498 - [c47]Gregory M. Provan:
Test Generation for Model-Based Diagnosis. ECAI 2008: 199-203 - [c46]Adamo Santana, Gregory M. Provan:
An Analysis of Bayesian Network Model-Approximation Techniques. ECAI 2008: 851-852 - [c45]Margarita Razgon, Gregory M. Provan:
Adding Flexibility to Russian Doll Search. ICTAI (1) 2008: 163-171 - [c44]Gregory M. Provan:
Approximation Techniques for Space-Efficient Compilation in Abductive Inference. ISAIM 2008 - 2007
- [c43]Igor Razgon, Barry O'Sullivan, Gregory M. Provan:
Generalizing Global Constraints Based on Network Flows. CSCLP 2007: 127-141 - [c42]Margarita Razgon, Barry O'Sullivan, Gregory M. Provan:
Search Ordering Heuristics for Restarts-Based Constraint Solving. FLAIRS 2007: 182-183 - [c41]Olga Heling-Tveretina, Gregory M. Provan:
On Approximate Knowledge Compilation with Weighted Decision Diagrams. IC-AI 2007: 470-475 - [c40]Gregory M. Provan, Jun Wang:
Automated Benchmark Model Generators for Model-Based Diagnostic Inference. IJCAI 2007: 513-518 - [c39]Alexander Feldman, Gregory M. Provan, Arjan J. C. van Gemund:
Approximate Model-Based Diagnosis Using Greedy Stochastic Search. SARA 2007: 139-154 - 2006
- [c38]Barry O'Sullivan, Gregory M. Provan:
Approximate Compilation for Embedded Model-based Reasoning. AAAI 2006: 894-899 - [c37]Gregory M. Provan:
A Bayesian network framework for stochastic discrete-event control. ACC 2006: 1-6 - [c36]Gregory M. Provan:
An Empirical Analysis of the Complexity of Model-Based Diagnosis. ECAI 2006: 783-784 - [c35]Gregory M. Provan:
Multi-Level Modeling and Distributed Agent-Based Inference: the Role of System Structure. ICECCS 2006: 217-226 - 2005
- [c34]Gregory M. Provan:
Approximate Model-Based Diagnosis Using Preference-Based Compilation. SARA 2005: 182-193 - 2004
- [c33]Gregory M. Provan:
Inferential Complexity Control for Model-Based Abduction. KR 2004: 415-426 - 2003
- [c32]Gregory M. Provan:
A Novel Framework for Integrating Discrete Event System Control and Diagnosis. IJCAI 2003: 1341-1342 - 2002
- [c31]Gregory M. Provan:
Distributed diagnosability properties of discrete event systems. ACC 2002: 134-139 - [c30]Gregory M. Provan:
On the diagnosability of decentralized, timed discrete event systems. CDC 2002: 405-410 - [c29]Gregory M. Provan, Yi-Liang Chen:
Agent-Based, Distributed Diagnosis for Shipboard Systems. BASYS 2002: 281-288 - [c28]Gregory M. Provan:
A Model-Based Diagnosis Framework for Distributed Embedded Systems. KR 2002: 341-352 - 2001
- [j9]Gregory M. Provan, Yi-Liang Chen:
Model-Based Fault-tolerant Control Reconfiguration for General Network Topologies. IEEE Micro 21(5): 64-76 (2001) - [c27]Gregory M. Provan:
Stochastic System Monitoring and Control. AISTATS 2001: 243-250 - 2000
- [c26]Gregory M. Provan, Yi-Liang Chen:
Characterizing controllability and observability properties of temporal causal network modeling for discrete event systems. ACC 2000: 3540-3544 - [c25]Gregory M. Provan, Yi-Liang Chen:
On the relationship between finite state machine and causal network representations for discrete event system modeling: initial results. CDC 2000: 29-34
1990 – 1999
- 1999
- [j8]Gregory M. Provan, David Glover:
An Approach for Integrating Multi-Modal, Model-Based Diagnostic Components. AI Commun. 12(1-2): 19-32 (1999) - 1998
- [c24]Amit Misra, Gregory M. Provan, Gabor Karsai, George Bloor, Ethan Scarl:
A generic and symbolic model-based diagnostic reasoner with highly scalable properties. SMC 1998: 3154-3160 - 1997
- [j7]Adnan Darwiche, Gregory M. Provan:
Query DAGs: A Practical Paradigm for Implementing Belief-Network Inference. J. Artif. Intell. Res. 6: 147-176 (1997) - [j6]Pat Langley, Gregory M. Provan, Padhraic Smyth:
Learning with Probabilistic Representations. Mach. Learn. 29(2-3): 91-101 (1997) - [c23]Adnan Darwiche, Gregory M. Provan:
The Effect of Observations on the Complexity of Model-Based Diagnosis. AAAI/IAAI 1997: 94-99 - [c22]Adnan Darwiche, Gregory M. Provan:
A Standard Approach for Optimizing Belief Network Inference Using Query DAGs. UAI 1997: 116-123 - [i1]Adnan Darwiche, Gregory M. Provan:
Query DAGs: A Practical Paradigm for Implementing Belief-Network Inference. CoRR cs.AI/9705101 (1997) - 1996
- [j5]Malcolm Pradhan, Max Henrion, Gregory M. Provan, Brendan Del Favero, Kurt Huang:
The Sensitivity of Belief Networks to Imprecise Probabilities: An Experimental Investigation. Artif. Intell. 85(1-2): 363-397 (1996) - [c21]Moninder Singh, Gregory M. Provan:
Efficient Learning of Selective Bayesian Network Classifiers. ICML 1996: 453-461 - [c20]Gregory M. Provan, Moninder Singh:
Data Mining and Model Simplicity: A Case Study in Diagnosis. KDD 1996: 57-62 - [c19]Adnan Darwiche, Gregory M. Provan:
Query DAGs: A practical paradigm for implementing belief-network inference. UAI 1996: 203-210 - [c18]Max Henrion, Malcolm Pradhan, Brendan Del Favero, Kurt Huang, Gregory M. Provan, Paul O'Rorke:
Why is diagnosis using belief networks insensitive to imprecision in probabilities? UAI 1996: 307-314 - 1995
- [c17]Gregory M. Provan, Moninder Singh:
Learning Bayesian Networks Using Feature Selection. AISTATS 1995: 291-300 - [c16]Moninder Singh, Gregory M. Provan:
A Comparison of Induction Algorithms for Selective and non-Selective Bayesian Classifiers. ICML 1995: 497-505 - [c15]Gregory M. Provan:
Abstraction in Belief Networks: The Role of Intermediate States in Diagnostic Reasoning. UAI 1995: 464-471 - 1994
- [j4]Gregory M. Provan:
Tradeoffs in Knowledge-Based Construction of Probabilistic Models. IEEE Trans. Syst. Man Cybern. Syst. 24(11): 1580-1592 (1994) - [c14]Max Henrion, Gregory M. Provan, Brendan Del Favero, Gillian Sanders:
An Experimental Comparison of Numerical and Qualitative Probabilistic Reasoning. UAI 1994: 319-326 - [c13]Malcolm Pradhan, Gregory M. Provan, Blackford Middleton, Max Henrion:
Knowledge Engineering for Large Belief Networks. UAI 1994: 484-490 - 1993
- [j3]Gregory M. Provan, John R. Clarke:
Dynamic Network Construction and Updating Techniques for the Diagnosis of Acute Abdominal Pain. IEEE Trans. Pattern Anal. Mach. Intell. 15(3): 299-307 (1993) - [c12]Teow-Hin Ngair, Gregory M. Provan:
A Lattice-Theoretic Analysis of ATMS Problem Solving. ECSQARU 1993: 282-289 - [c11]Gregory M. Provan:
Tradeoffs in Constructing and Evaluating Temporal Influence Diagrams. UAI 1993: 40-47 - 1992
- [j2]Gregory M. Provan:
The validity of Dempster-Shafer belief functions. Int. J. Approx. Reason. 6(3): 389-399 (1992) - 1991
- [c10]Colin J. H. McDiarmid, Gregory M. Provan:
An Expected-Cost Analysis of Backtracking and Non-Backtracking Algorithms. IJCAI 1991: 172-177 - [c9]Gregory M. Provan, David L. Poole:
The Utility of Consistency-Based Diagnostic Techniques. KR 1991: 461-472 - [c8]Gregory M. Provan:
Dynamic Network Updating Techniques for Diagnostic Reasoning. UAI 1991: 279-286 - 1990
- [j1]Gregory M. Provan:
A logic-based analysis of Dempster-Shafer theory. Int. J. Approx. Reason. 4(5-6): 451-495 (1990) - [c7]Gregory M. Provan:
The Computational Complexity of Multiple-Context Truth Maintenance Systems. ECAI 1990: 522-527 - [c6]Gregory M. Provan:
An Analysis Of Knowledge Representation Schemes For High Level Vision. ECCV 1990: 537-541 - [c5]David L. Poole, Gregory M. Provan:
What is the most likely diagnosis? UAI 1990: 89-106
1980 – 1989
- 1989
- [c4]Gregory M. Provan:
An Analysis of ATMS-Based Techniques for Computing Dempster-Shafer Belief Functions. IJCAI 1989: 1115-1120 - [c3]Gregory M. Provan:
The Application of Dempster Shafer Theory to a Logic-Based Visual Recognition System. UAI 1989: 389-406 - 1988
- [b1]Gregory M. Provan:
Complexity analysis of truth maintenance systems with application to high level vision. University of Oxford, UK, 1988 - [c2]Gregory M. Provan:
Solving Diagnostic Problems Using Extended Truth Maintenance Systems. ECAI 1988: 547-552 - 1987
- [c1]Gregory M. Provan:
Efficiency Analysis of Multiple-Context TMSs in Scene Representation. AAAI 1987: 173-177
Coauthor Index
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