Mapping and Combining Combinatorial Problems into Energy Landscapes via Pseudo-Boolean Constraints

Lima, Priscila M. V.; Pereira, Geraldo; Morveli-Espinoza, Mariela; França, Felipe M. G.

doi:10.1007/11565123_30

Cited by 7 publications

(2 citation statements)

References 7 publications

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“…Other constraint specification languages, such as Z notation [11] and MathSAT [2], differ from this work on (i) the use of a neural engine and on (ii) the possibility of combining different sets of constraints, representing different problems, in order to specify a new target problem, as recently demonstrated [9]. Moreover, our approach profits from the intermediate definition of an energy function, which can be minimized by any available solver, not only higher-order Hopfield networks of stochastic neurons, as considered in this work.…”

Section: Resultsmentioning

confidence: 99%

SATyrus: a SAT-based neuro-symbolic architecture for constraint processing

Lima¹,

Morveli-Espinoza

Pereira

et al. 2005

Fifth International Conference on Hybrid Intelligent Systems (HIS'05)

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This paper introduces SATyrus, a neuro-symbolic architecture oriented to optimization problem solving via mapping problems specification into sets of pseudo-Boolean constraints. SATyrus provides a logical declarative language used to specify and compile a target problem into a particular energy function representing its space state of solutions. The resulting energy function is then mapped into a Higher-order Hopfield network of stochastic neurons in order to find its global minima. The application of SATyrus over three illustrative problems are given: (i) graph coloring, (ii) Traveling Salesperson Problem (TSP), and (iii) calculus of the difference between observed and hypothesized distances of two atoms, a sub-problem of the determination of a molecular structure.

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Section: Resultsmentioning

confidence: 99%

SATyrus: a SAT-based neuro-symbolic architecture for constraint processing

Lima¹,

Morveli-Espinoza

Pereira

et al. 2005

Fifth International Conference on Hybrid Intelligent Systems (HIS'05)

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show abstract

“…Maculan et al [26] provided insight on other considerations such as the similarities and differences between float time and flow problems. Lima et al [24] provided a method for expressing problems as satisfiability whereby the set of so-called "primitives" can be expressed as a problem specification language and problems specification as path to-float time problems as sentences in that language.…”

Section: Introductionmentioning

confidence: 99%

Theory and application of reciprocal transformation of “path problem” and “time float problem”

Wei

2016

RAIRO-Oper. Res.

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The concept of analytic geometry, i.e., the reciprocal transformation of geometry and algebra, hints a prospect for the reciprocal transformation of the "path problem" and the "time float problem". A reciprocal transformation can be used to solve a complex problem in one field by translating it into a simpler one in another field. In this case, owing to the generalized concept of length, various types of non-path problems such as the optimum allocation problem and equipment replacement problem can be represented as "path problems". A "length network", which is generalized in nature, is translated into a "time network" by changing the meanings of arcs and lengths. Furthermore, "path problems" can be represented as "time float problems" by discovering the relationships of paths in the length network and time floats in the time network. Base on the relationships, "time float problems" also can be represented as "path problems". The relationships are keys to updating the mutual correspondence of path problems and time float problems. The relationships mirror the uniform qualities of networks in various disciplines and fields. We apply such relationships to solve optimum allocation problems, equipment replacement problems, and path problems with required lengths and to analyze anomalies in projects under generalized precedence relations. These applications test the effectiveness of our proposed approach to theoretical and applied researches in various disciplines and fields.

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Genomics and Artificial Intelligence Working Together in Drug Discovery and Repositioning: The Advent of Adaptive Pharmacogenomics in Glioblastoma and Chronic Arterial Inflammation Therapies

Pereira

2017

Biotechnology and Production of Anti-Cancer Compounds

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Mapping and Combining Combinatorial Problems into Energy Landscapes via Pseudo-Boolean Constraints

Cited by 7 publications

References 7 publications

SATyrus: a SAT-based neuro-symbolic architecture for constraint processing

SATyrus: a SAT-based neuro-symbolic architecture for constraint processing

Theory and application of reciprocal transformation of “path problem” and “time float problem”

Genomics and Artificial Intelligence Working Together in Drug Discovery and Repositioning: The Advent of Adaptive Pharmacogenomics in Glioblastoma and Chronic Arterial Inflammation Therapies

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