Symbolic Inference and Optimization
Papers from the 2017 AAAI Workshop
Scott Sanner, Chair
AAAI Technical Report WS-17-14
This technical report was published as part of The Workshops of the Thirty-First AAAI Conference on Artificial Intelligence: Technical Reports WS-17-01 – WS-17-15 by The AAAI Press, Palo Alto, California
Contents
Open-Universe Weighted Model Counting: Extended Abstract
Vaishak Belle
Expressing Probabilistic Graphical Models in RCC
Cristina Cornelio, Vijay Saraswat
Trusted Machine Learning: Model Repair and Data Repair for Probabilistic Models
Shalini Ghosh, Patrick Lincoln, Ashis Tiwari, Xiaojin Zhu
Nonlinear Optimization and Symbolic Dynamic Programming for Parameterized Hybrid Markov Decision Processes
Shamin Kinathil, Harold Soh, Scott Sanner
Conditional Term Equivalent Symmetry Breaking for SAT
Timothy Kopp, Parag Singla, Henry Kautz
PDDL+ Planning with Temporal Pattern Databases
Wiktor Mateusz Piotrowski, Maria Fox, Derek Long, Daniele Magazzeni, Fabio Mercorio
Embedding Tarskian Semantics in Vector Spaces
Taisuke Sato
BDD-Constrained A* Search: A Fast Method for Solving Constrained DAG Shortest-Path Problems
Fumito Takeuchi, Masaaki Nishino, Norihito Yasuda, Takuya Akiba, Shin-ichi Minato, Masaaki Nagata
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