Relevant bibliographies by topics / Algebaic Decision Diagram

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Algebaic Decision Diagram'

Author: Grafiati
Published: 9 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Algebaic Decision Diagram"

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Rauzy, Antoine, and Yang. "Decision Diagram Algorithms to Extract Minimal Cutsets of Finite Degradation Models." Information 10, no. 12 (2019): 368. http://dx.doi.org/10.3390/info10120368.

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In this article, we propose decision diagram algorithms to extract minimal cutsets of finite degradation models. Finite degradation models generalize and unify combinatorial models used to support probabilistic risk, reliability and safety analyses (fault trees, attack trees, reliability block diagrams…). They formalize a key idea underlying all risk assessment methods: states of the models represent levels of degradation of the system under study. Although these states cannot be totally ordered, they have a rich algebraic structure that can be exploited to extract minimal cutsets of models, w
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DJIDJEV, HRISTO N., and ANDRZEJ LINGAS. "ON COMPUTING VORONOI DIAGRAMS FOR SORTED POINT SETS." International Journal of Computational Geometry & Applications 05, no. 03 (1995): 327–37. http://dx.doi.org/10.1142/s0218195995000192.

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We show that the Voronoi diagram of a finite sequence of points in the plane which gives sorted order of the points with respect to two perpendicular directions can be computed in linear time. In contrast, we observe that the problem of computing the Voronoi diagram of a finite sequence of points in the plane which gives the sorted order of the points with respect to a single direction requires Ω(n log n) operations in the algebraic decision tree model. As a corollary from the first result, we show that the bounded Voronoi diagrams of simple n-vertex polygons which can be efficiently cut into
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Dudek, Jeffrey, Vu Phan, and Moshe Vardi. "ADDMC: Weighted Model Counting with Algebraic Decision Diagrams." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 02 (2020): 1468–76. http://dx.doi.org/10.1609/aaai.v34i02.5505.

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We present an algorithm to compute exact literal-weighted model counts of Boolean formulas in Conjunctive Normal Form. Our algorithm employs dynamic programming and uses Algebraic Decision Diagrams as the main data structure. We implement this technique in ADDMC, a new model counter. We empirically evaluate various heuristics that can be used with ADDMC. We then compare ADDMC to four state-of-the-art weighted model counters (Cachet, c2d, d4, and miniC2D) on 1914 standard model counting benchmarks and show that ADDMC significantly improves the virtual best solver.
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Bibilo, P. N., and V. I. Romanov. "Experimental Study of Algorithms for Minimization of Binary Decision Diagrams using Algebraic Representations of Cofactors." Programmnaya Ingeneria 13, no. 2 (2022): 51–67. http://dx.doi.org/10.17587/prin.13.51-67.

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BDD (Binary Decision Diagram) is used for technology-independent optimization, performed as the first stage in the synthesis of logic circuits in the design of ASIC (application-specific integrated circuit). BDD is an acyclic graph defining a Boolean function or a system of Boolean functions. Each vertex of this graph is associated with the complete or reduced Shannon expansion formula. Binary decision diagrams with mutually inverse subfunctions (cofac-tors) are considered. We have developed algorithms for finding algebraic representations of cofactors of the same BDD level in the form of a di
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Pralet, C., G. Verfaillie, and T. Schiex. "An Algebraic Graphical Model for Decision with Uncertainties, Feasibilities, and Utilities." Journal of Artificial Intelligence Research 29 (August 23, 2007): 421–89. http://dx.doi.org/10.1613/jair.2151.

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Numerous formalisms and dedicated algorithms have been designed in the last decades to model and solve decision making problems. Some formalisms, such as constraint networks, can express "simple" decision problems, while others are designed to take into account uncertainties, unfeasible decisions, and utilities. Even in a single formalism, several variants are often proposed to model different types of uncertainty (probability, possibility...) or utility (additive or not). In this article, we introduce an algebraic graphical model that encompasses a large number of such formalisms: (1) we firs
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Bibilo, P. N. "Disjunctive and conjunctive decompositions of incompletely defined Boolean functions in a Binary Decision Diagram." Informatics 22, no. 1 (2025): 40–65. https://doi.org/10.37661/1816-0301-2025-22-1-40-65.

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Objectives. The problems of minimizing the number of cofactors (subfunctions) of the Shannon expansions located at the same level of the BDD, representing a system of incompletely defined (partial) Boolean functions, are considered. To reduce the number of functions, it is proposed to find a subset of such functions that can be expressed as algebraic decompositions of disjunctions or conjunctions of other predefined partial functions, while the directed graph of function occurrences in decompositions should not contain contours.Methods. Finding disjunctive and conjunctive decompositions requir
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Joshi, S., and R. Khardon. "Probabilistic Relational Planning with First Order Decision Diagrams." Journal of Artificial Intelligence Research 41 (June 21, 2011): 231–66. http://dx.doi.org/10.1613/jair.3205.

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Dynamic programming algorithms have been successfully applied to propositional stochastic planning problems by using compact representations, in particular algebraic decision diagrams, to capture domain dynamics and value functions. Work on symbolic dynamic programming lifted these ideas to first order logic using several representation schemes. Recent work introduced a first order variant of decision diagrams (FODD) and developed a value iteration algorithm for this representation. This paper develops several improvements to the FODD algorithm that make the approach practical. These include,
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Falkowski, B. J., and Chip-Hong Chang. "Efficient calculation of Gray code-ordered Walsh spectra through algebraic decision diagrams." Electronics Letters 34, no. 9 (1998): 848. http://dx.doi.org/10.1049/el:19980606.

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Speck, David, Florian Geißer, and Robert Mattmüller. "Symbolic Planning with Edge-Valued Multi-Valued Decision Diagrams." Proceedings of the International Conference on Automated Planning and Scheduling 28 (June 15, 2018): 250–58. http://dx.doi.org/10.1609/icaps.v28i1.13890.

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Symbolic representations have attracted significant attention in optimal planning. Binary Decision Diagrams (BDDs) form the basis for symbolic search algorithms. Closely related are Algebraic Decision Diagrams (ADDs), used to represent heuristic functions. Also, progress was made in dealing with models that take state-dependent action costs into account. Here, costs are represented as Edge-valued Multi-valued Decision Diagrams (EVMDDs), which can be exponentially more compact than the corresponding ADD representation. However, they were not yet considered for symbolic planning. In this work, w
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Van den Broeck, Guy, Ingo Thon, Martijn Van Otterlo, and Luc De Raedt. "DTProbLog: A Decision-Theoretic Probabilistic Prolog." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (2010): 1217–22. http://dx.doi.org/10.1609/aaai.v24i1.7755.

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We introduce DTProbLog, a decision-theoretic extension of Prolog and its probabilistic variant ProbLog. DTProbLog is a simple but expressive probabilistic programming language that allows the modeling of a wide variety of domains, such as viral marketing. In DTProbLog, the utility of a strategy (a particular choice of actions) is defined as the expected reward for its execution in the presence of probabilistic effects. The key contribution of this paper is the introduction of exact, as well as approximate, solvers to compute the optimal strategy for a DTProbLog program and the decision problem
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Dissertations / Theses on the topic "Algebaic Decision Diagram"

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MOLTENI, MARIA CHIARA. "ON THE SECURITY OF CRYPTOGRAPHIC CIRCUITS:PROTECTION AGAINST PROBING ATTACKS AND PERFORMANCE IMPROVEMENT OF GARBLED CIRCUITS." Doctoral thesis, Università degli Studi di Milano, 2022. http://hdl.handle.net/2434/920426.

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Dealing with secure computation and communication in hardware devices, an attacker that threatens to security of the systems can be of two different types. The first type of attacker is external to the exchange of secret messages and tries to steal some sensitive information. Probing a circuit is a useful technique through which an attacker can derive information correlated with the secret manipulated by a cryptographic circuit. Probing security is the branch of research that tries to devise models, tools and countermeasures against this type of attacks. We define a new methodology that al
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Ng, David. "Modeling circuit-level leakage current using algebraic decision diagrams." 2005. http://link.library.utoronto.ca/eir/EIRdetail.cfm?Resources__ID=370239&T=F.

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Books on the topic "Algebaic Decision Diagram"

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Ng, David. Modeling circuit-level leakage current using algebraic decision diagrams. 2005.

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Book chapters on the topic "Algebaic Decision Diagram"

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Raddum, Håvard, and Oleksandr Kazymyrov. "Algebraic Attacks Using Binary Decision Diagrams." In Cryptography and Information Security in the Balkans. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21356-9_4.

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Atampore, Francis, and Michael Winter. "Relation Algebras, Matrices, and Multi-valued Decision Diagrams." In Relational and Algebraic Methods in Computer Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33314-9_17.

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Kim, Kee-Eung, and Thomas Dean. "Solving Factored MDPs with Large Action Space Using Algebraic Decision Diagrams." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45683-x_11.

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Murtovi, Alnis, Alexander Bainczyk, and Bernhard Steffen. "Forest GUMP: A Tool for Explanation." In Tools and Algorithms for the Construction and Analysis of Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99527-0_17.

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AbstractIn this paper, we present Forest GUMP (for Generalized, Unifying Merge Process) a tool for providing tangible experience with three concepts of explanation. Besides the well-known model explanation and outcome explanation, Forest GUMP also supports class characterization, i.e., the precise characterization of all samples with the same classification. Key technology to achieve these results is algebraic aggregation, i.e., the transformation of a Random Forest into a semantically equivalent, concise white-box representation in terms of Algebraic Decision Diagrams (ADDs). The paper sketch
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Lazreg, Sami, Maxime Cordy, and Axel Legay. "Verification of Variability-Intensive Stochastic Systems with Statistical Model Checking." In Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19759-8_27.

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AbstractWe propose a simulation-based approach to verify Variability-Intensive Systems (VISs) with stochastic behaviour. Given an LTL formula and a model of the VIS behaviour, our method estimates the probability for each variant to satisfy the formula. This allows us to learn the products of the VIS for which the probability stands above a certain threshold. To achieve this, our method samples VIS executions from all variants at once and keeps track of the occurrence probability of these executions in any given variant. The efficiency of this algorithm relies on Algebraic Decision Diagram (AD
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Král’, Danie. "Algebraic and Uniqueness Properties of Parity Ordered Binary Decision Diagrams and Their Generalization." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44612-5_43.

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"Algebraic Structures for the Fourier Transform on Finite Groups." In Decision Diagram Techniques for Micro- and Nanoelectronic Design Handbook. CRC Press, 2005. http://dx.doi.org/10.1201/9781420037586.axa.

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Conference papers on the topic "Algebaic Decision Diagram"

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Herrmann, Ricardo G., and Leliane N. de Barros. "Algebraic Sentential Decision Diagrams in Symbolic Probabilistic Planning." In 2013 Brazilian Conference on Intelligent Systems (BRACIS). IEEE, 2013. http://dx.doi.org/10.1109/bracis.2013.37.

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Xiang, Zhimin, Yongwei Chen, Jin Liu, and Xiaoxiao Wo. "Service Routing Analysis in Optical Network with Algebraic Decision Diagram." In 2015 3rd International Conference on Mechatronics and Industrial Informatics. Atlantis Press, 2015. http://dx.doi.org/10.2991/icmii-15.2015.73.

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Jiang, Wei, Siwei Zhou, Luyao Ye, et al. "An Algebraic Binary Decision Diagram for Analysis of Dynamic Fault Tree." In 2018 5th International Conference on Dependable Systems and Their Applications (DSA). IEEE, 2018. http://dx.doi.org/10.1109/dsa.2018.00018.

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Fang, Ying, Tianlong Gu, Liang Chang, and Long Li. "Algebraic Decision Diagram-Based CP-ABE with Constant Secret and Fast Decryption." In 2020 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). IEEE, 2020. http://dx.doi.org/10.1109/cyberc49757.2020.00025.

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Gulati, K., N. Jayakumar, and S. P. Khatri. "An algebraic decision diagram (ADD) based technique to find leakage histograms of combinational designs." In ISLPED '05. Proceedings of the 2005 International Symposium on Low Power Electronics and Design. IEEE, 2005. http://dx.doi.org/10.1109/lpe.2005.195497.

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Gulati, Kanupriya, Nikhil Jayakumar, and Sunil P. Khatri. "An algebraic decision diagram (ADD) based technique to find leakage histograms of combinational designs." In the 2005 international symposium. ACM Press, 2005. http://dx.doi.org/10.1145/1077603.1077633.

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Bobbio, Andrea, and Roberta Terruggia. "Reliability and quality of service in weighted probabilistic networks using Algebraic Decision Diagrams." In 2009 Annual Reliability and Maintainability Symposium (RAMS). IEEE, 2009. http://dx.doi.org/10.1109/rams.2009.4914643.

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Farahmandi, Farimah, Bijan Alizadeh, and Zain Navabi. "Effective Combination of Algebraic Techniques and Decision Diagrams to Formally Verify Large Arithmetic Circuits." In 2014 IEEE Computer Society Annual Symposium on VLSI (ISVLSI). IEEE, 2014. http://dx.doi.org/10.1109/isvlsi.2014.109.

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Long, Wenjia, Kaizhi Wang, and Xuan Wang. "Reliability Analysis of a Computer-Based Interlocking System with a Double 2-out-of-2 Redundancy Structure using Algebraic Binary Decision Diagrams." In 2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C). IEEE, 2022. http://dx.doi.org/10.1109/qrs-c57518.2022.00073.

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Kolb, Samuel, Martin Mladenov, Scott Sanner, Vaishak Belle, and Kristian Kersting. "Efficient Symbolic Integration for Probabilistic Inference." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/698.

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Weighted model integration (WMI) extends weighted model counting (WMC) to the integration of functions over mixed discrete-continuous probability spaces. It has shown tremendous promise for solving inference problems in graphical models and probabilistic programs. Yet, state-of-the-art tools for WMI are generally limited either by the range of amenable theories, or in terms of performance. To address both limitations, we propose the use of extended algebraic decision diagrams (XADDs) as a compilation language for WMI. Aside from tackling typical WMI problems, XADDs also enable partial WMI yiel
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