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Minimizing Expected Cost Under Hard Boolean Constraints, with Applications to Quantitative Synthesis [article]

Shaull Almagor, Orna Kupferman, Yaron Velner
2016 arXiv   pre-print
expected cost we would like to minimize with respect to a probabilistic environment.  ...  Beyond direct applications, in synthesis with costs and rewards to certain behaviors, it allows us to compute the minimal sensing cost of ω-regular specifications -- a measure of quality in which we look  ...  While the specification ψ is a hard constraint, as we only allow correct computations, minimizing the expected cost of computations with respect to γ is a soft constraint.  ... 
arXiv:1604.07064v1 fatcat:kaehp637e5dujiclgji3wguffu

Randomized Synthesis for Diversity and Cost Constraints with Control Improvisation [article]

Andreas Gittis, Eric Vin, Daniel J. Fremont
2022 arXiv   pre-print
In this paper, we enable this type of application by generalizing the CI problem to support quantitative soft constraints which bound the expected value of a given cost function, and randomness constraints  ...  The recently-proposed framework of control improvisation (CI) provides techniques for the correct-by-construction synthesis of randomized systems subject to hard and soft constraints.  ...  As a result, synthesis of systems under such constraints requires new techniques.  ... 
arXiv:2206.02775v1 fatcat:244ch36sgbajrd6eih2qdanoc4

The Embedded Systems Design Challenge [chapter]

Thomas A. Henzinger, Joseph Sifakis
2006 Lecture Notes in Computer Science  
probabilities; with functional and performance requirements; with qualitative and quantitative analysis; with booleans and reals.  ...  The former tries to guarantee system safety at all costs, even when the system operates under extreme conditions; the latter tries to optimize system performance (and cost) when the system operates under  ... 
doi:10.1007/11813040_1 fatcat:3hvzxh3snjbhhc6lcm4gydnye4

Quantitative reactive modeling and verification

Thomas A. Henzinger
2013 Computer Science - Research and Development  
and abstraction refinement, model checking, and synthesis.  ...  The project aims to build and evaluate a theory of quantitative fitness measures for reactive models.  ...  In this way, reactive synthesis is lifted from a constraint-solving problem to an optimization problem.  ... 
doi:10.1007/s00450-013-0251-7 pmid:27069511 pmcid:PMC4811300 fatcat:cimfqu272beijj6dgqpvsz7koy

The Discipline of Embedded Systems Design

Thomas A. Henzinger, Joseph Sifakis
2007 Computer  
In industry, trained electrical engineers routinely design software architectures, and trained computer scientists routinely deal with physical constraints.  ...  Fortunately, with crises comes opportunity-in this case, the chance to reinvigorate computer science research by focusing on embedded systems design.  ...  Best-effort methods try to optimize system performance (and cost) when the system operates under expected conditions.  ... 
doi:10.1109/mc.2007.364 fatcat:qvwikwqfovbchkjk5o6ltaq5re

Model Predictive Control for Signal Temporal Logic Specification [article]

Vasumathi Raman, Alexandre Donzé, Mehdi Maasoumy, Richard M. Murray, Alberto Sangiovanni-Vincentelli, Sanjit A. Seshia
2017 arXiv   pre-print
For synthesis, we encode STL specifications as mixed integer-linear constraints on the system variables in the optimization problem at each step of a receding horizon control framework.  ...  We describe the use of STL to specify a wide range of properties of these systems, including safety, response and bounded liveness.  ...  The purpose of the MPC is to maintain a comfort temperature given by T comf whenever the room is occupied while minimizing the cost of heating.  ... 
arXiv:1703.09563v1 fatcat:qz4sm5j6wjf2tgodrbhbynpjay

Structured learning modulo theories

Stefano Teso, Roberto Sebastiani, Andrea Passerini
2017 Artificial Intelligence  
The ability to model these kind of domains is crucial in "learning to design" tasks, that is, learning applications where the goal is to learn from examples how to perform automatic de novo design of novel  ...  optimization over continuous linear arithmetical constraints.  ...  Acknowledgements We would like to thank Luc De Raedt, Guy Van den Broeck and Bernd Gutmann for useful discussions, and Patrick Trentin for his support with the usage of OptiMathSAT. R.  ... 
doi:10.1016/j.artint.2015.04.002 fatcat:rticr56sibbfdpjma4fvdixhxq

Repairing Decision-Making Programs Under Uncertainty [chapter]

Aws Albarghouthi, Loris D'Antoni, Samuel Drews
2017 Lecture Notes in Computer Science  
The goal of the repair is to construct a new program that satisfies a probabilistic Boolean expression.  ...  , (ii) synthesizes a minimal repair to the program over the sampled inputs using an smt-based encoding, and (iii) verifies that the resulting program is correct and is semantically close to the original  ...  This material is based upon work supported by the National Science Foundation under Grant numbers 1566015 and 1652140.  ... 
doi:10.1007/978-3-319-63387-9_9 fatcat:hsoxn3ebsrdttltt67o3xtd63u

Minimal specification revision for weighted transition systems

Kangjin Kim, Georgios Fainekos
2013 2013 IEEE International Conference on Robotics and Automation  
If the cost bounds cannot be satisfied with the initial specification, then it is desirable to return to the user a specification that can be satisfied on the system within the desired cost budget.  ...  The LTL specification captures the system requirements which must be satisfied by a plan which costs less than a certain cost budget.  ...  Acknowledgments: The authors would like to thank A. Agung Julius for recommending taking a linear programming approach.  ... 
doi:10.1109/icra.2013.6631151 dblp:conf/icra/KimF13 fatcat:yadrbjo5l5cjvi3juqau3tecry

Structured Learning Modulo Theories [article]

Stefano Teso and Roberto Sebastiani and Andrea Passerini
2014 arXiv   pre-print
The ability to model this kind of domains is crucial in "learning to design" tasks, that is, learning applications where the goal is to learn from examples how to perform automatic de novo design of novel  ...  optimization over continuous linear arithmetical constraints.  ...  Acknowledgements We would like to thank Luc De Raedt, Guy Van den Broeck and Bernd Gutmann for useful discussions.  ... 
arXiv:1405.1675v2 fatcat:s3ypi3wzenbwdlkhrfwbe3dfbe

HDL-Mutation Based Simulation Data Generation by Propagation Guided Search

Tao Xie, Wolfgang Mueller, Florian Letombe
2011 2011 14th Euromicro Conference on Digital System Design  
Then the progress of fault detection can be measured quantitatively on this graph to be the cost value. By minimizing this cost we approach the target test data.  ...  Case study with a floating point arithmetic IP design has shown that the cost function is able to guide effectively the search procedure towards a fault-detecting test.  ...  The cost function should reflect quantitatively to what an extent these two conditions are satisfied, so that by minimizing this cost a search algorithm can find the target test.  ... 
doi:10.1109/dsd.2011.83 dblp:conf/dsd/XieML11 fatcat:qszkqo6phvaivauags6drbwlme

Explicit and implicit algorithms for binate covering problems

T. Villa, T. Kam, R.K. Brayton, A.L. Sangiovanni-Vincenteili
1997 IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems  
We survey techniques for solving binate covering problems, an optimization step often occurring in logic synthesis applications.  ...  Standard approaches are said to be explicit because they work on a direct representation of the binate table, usually as a matrix.  ...  Under this assumption, BCP amounts to finding an assignment for that minimizes the cost function and that satisfies all 's simultaneously.  ... 
doi:10.1109/43.644030 fatcat:u3jkmzff6jafhjys5ol6bmvely

Synthesis of Minimum-Cost Shields for Multi-agent Systems

Suda Bharadwaj, Roderik Bloem, Rayna Dimitrova, Bettina Konighofer, Ufuk Topcu
2019 American Control Conference (ACC)  
This work is the first to discuss the shield synthesis problem with quantitative objectives.  ...  We provide several cost functions that are utilized in the multi-agent setting and provide methods for the synthesis of cost-optimal shields and fair shields, under the given assumptions on the multi-agent  ...  Acknowledgments 1 We thank Jesse Quattrociocchi for his help with the simulations.  ... 
doi:10.23919/acc.2019.8815233 pmid:32020984 pmcid:PMC6999756 fatcat:3mrlmklyrzg3vdsh5nycifutyu

Quantitative Games under Failures

Thomas Brihaye, Gilles Geeraerts, Axel Haddad, Benjamin Monmege, Guillermo A. Pérez, Gabriel Renault, Marc Herbstritt
2015 Foundations of Software Technology and Theoretical Computer Science  
We show that, on the one hand, for most of the classical cost functions considered in the literature, the problem of determining if Runner has a strategy to ensure a cost below some threshold is EXPTIME-complete  ...  In our model of quantitative sabotage games, Saboteur is now given a budget that he can distribute amongst the edges of the graph, whilst Runner attempts to minimise the quantity of budget witnessed while  ...  We have also shown the applicability of our framework to deal with the more general problem of reactive synthesis in systems under failures.  ... 
doi:10.4230/lipics.fsttcs.2015.293 dblp:conf/fsttcs/BrihayeGHMPR15 fatcat:rog3ha3uhzgt7ciufgkjv6ni3a

Variations on the Stochastic Shortest Path Problem [chapter]

Mickael Randour, Jean-François Raskin, Ocan Sankur
2015 Lecture Notes in Computer Science  
with multiple guarantees on the distribution of the length of paths reaching a given target, rather than simply minimizing its expected value.  ...  In this invited contribution, we revisit the stochastic shortest path problem, and show how recent results allow one to improve over the classical solutions: we present algorithms to synthesize strategies  ...  The classical strategy synthesis setting often considers a single objective to be optimized such as the reachability probability, or the expected cost to target.  ... 
doi:10.1007/978-3-662-46081-8_1 fatcat:7wx6urrbyrgunh2nj6r5w5usx4
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