2,466 research outputs found
Recommended from our members
Working notes of the 1991 spring symposium on constraint-based reasoning
Experiments in reactive constraint logic programming1This paper is the complete version of a previous paper published in [14].1
AbstractIn this paper we study a reactive extension of constraint logic programming (CLP). Our primary concerns are search problems in a dynamic environment, where interactions with the user (e.g. in interactive multi-criteria optimization problems) or interactions with the physical world (e.g. in time evolving problems) can be modeled and solved efficiently. Our approach is based on a complete set of query manipulation commands for both the addition and the deletion of constraints and atoms in the query. We define a fully incremental model of execution which, contrary to other proposals, retains as much information as possible from the last derivation preceding a query manipulation command. The completeness of the execution model is proved in a simple framework of transformations for CSLD derivations, and of constraint propagation seen as chaotic iteration of closure operators. A prototype implementation of this execution model is described and evaluated on two applications
Constraint-based Programming: A Survey
Report on constraint-based computer programming analyzing finite-domain and continuous-domain constraint satisfaction methods and existing systems which apply constraints to problem-solving, modeling, and simulation
A Quantitative Flavour of Robust Reachability
Many software analysis techniques attempt to determine whether bugs are
reachable, but for security purpose this is only part of the story as it does
not indicate whether the bugs found could be easily triggered by an attacker.
The recently introduced notion of robust reachability aims at filling this gap
by distinguishing the input controlled by the attacker from those that are not.
Yet, this qualitative notion may be too strong in practice, leaving apart bugs
which are mostly but not fully replicable. We aim here at proposing a
quantitative version of robust reachability, more flexible and still amenable
to automation. We propose quantitative robustness, a metric expressing how
easily an attacker can trigger a bug while taking into account that he can only
influence part of the program input, together with a dedicated quantitative
symbolic execution technique (QRSE). Interestingly, QRSE relies on a variant of
model counting (namely, functional E-MAJSAT) unseen so far in formal
verification, but which has been studied in AI domains such as Bayesian
network, knowledge representation and probabilistic planning. Yet, the existing
solving methods from these fields turn out to be unsatisfactory for formal
verification purpose, leading us to propose a novel parametric method. These
results have been implemented and evaluated over two security-relevant case
studies, allowing to demonstrate the feasibility and relevance of our ideas
Optimization and inference under fuzzy numerical constraints
Εκτεταμένη έρευνα έχει γίνει στους τομείς της Ικανοποίησης Περιορισμών με
διακριτά (ακέραια) ή πραγματικά πεδία τιμών. Αυτή η έρευνα έχει οδηγήσει σε
πολλαπλές σημασιολογικές περιγραφές, πλατφόρμες και
συστήματα για την περιγραφή σχετικών προβλημάτων με επαρκείς βελτιστοποιήσεις.
Παρά ταύτα, λόγω της ασαφούς φύσης
πραγματικών προβλημάτων ή ελλιπούς μας γνώσης για αυτά, η σαφής μοντελοποίηση
ενός προβλήματος ικανοποίησης περιορισμών δεν είναι πάντα ένα εύκολο ζήτημα ή
ακόμα και η καλύτερη προσέγγιση. Επιπλέον, το πρόβλημα της μοντελοποίησης και
επίλυσης ελλιπούς γνώσης είναι ακόμη δυσκολότερο. Επιπροσθέτως, πρακτικές
απαιτήσεις μοντελοποίησης και μέθοδοι βελτιστοποίησης του χρόνου αναζήτησης
απαιτούν συνήθως ειδικές πληροφορίες για το πεδίο εφαρμογής,
καθιστώντας τη δημιουργία ενός γενικότερου πλαισίου βελτιστοποίησης ένα
ιδιαίτερα δύσκολο πρόβλημα. Στα πλαίσια αυτής της εργασίας θα μελετήσουμε το
πρόβλημα της μοντελοποίησης και αξιοποίησης σαφών, ελλιπών ή ασαφών
περιορισμών, καθώς και πιθανές στρατηγικές βελτιστοποίησης. Καθώς τα
παραδοσιακά προβλήματα ικανοποίησης περιορισμών λειτουργούν βάσει συγκεκριμένων
και προκαθορισμένων κανόνων και σχέσεων, παρουσιάζει ενδιαφέρον η διερεύνηση
στρατηγικών και βελτιστοποιήσεων που θα επιτρέπουν το συμπερασμό νέων ή/και
αποδοτικότερων περιορισμών. Τέτοιοι επιπρόσθετοι κανόνες θα μπορούσαν να
βελτιώσουν τη διαδικασία αναζήτησης μέσω της εφαρμογής αυστηρότερων περιορισμών
και περιορισμού του χώρου αναζήτησης ή να προσφέρουν χρήσιμες πληροφορίες στον
αναλυτή για τη φύση του προβλήματος που
μοντελοποιεί.Extensive research has been done in the areas of Constraint Satisfaction with
discrete/integer
and real domain ranges. Multiple platforms and systems to deal with these kinds
of domains have been developed and appropriately optimized. Nevertheless, due
to the incomplete and possibly vague nature of real-life problems, modeling a
crisp and adequately strict satisfaction problem may not always be easy or even
appropriate. The problem of modeling incomplete
knowledge or solving an incomplete/relaxed representation of a problem is a
much harder issue to tackle. Additionally, practical modeling requirements and
search optimizations require specific domain knowledge in order to be
implemented, making the creation of a more generic optimization framework an
even harder problem.In this thesis, we will study the problem of modeling and
utilizing incomplete and fuzzy constraints, as well as possible optimization
strategies. As constraint satisfaction problems usually contain hard-coded
constraints based on specific problem and domain knowledge, we will investigate
whether strategies and generic heuristics exist for inferring new constraint
rules. Additional rules could optimize the search process by implementing
stricter constraints and thus pruning the search space or even provide useful
insight to the researcher concerning the nature of the investigated problem
Efficient Constraints on Possible Worlds for Reasoning About Necessity
Modal logics offer natural, declarative representations for describing both the modular structure of logical specifications and the attitudes and behaviors of agents. The results of this paper further the goal of building practical, efficient reasoning systems using modal logics. The key problem in modal deduction is reasoning about the world in a model (or scope in a proof) at which an inference rule is applied - a potentially hard problem. This paper investigates the use of partial-order mechanisms to maintain constraints on the application of modal rules in proof search in restricted languages. The main result is a simple, incremental polynomial-time algorithm to correctly order rules in proof trees for combinations of K, K4, T and S4 necessity operators governed by a variety of interactions, assuming an encoding of negation using a scoped constant ⊥. This contrasts with previous equational unification methods, which have exponential performance in general because they simply guess among possible intercalations of modal operators. The new, fast algorithm is appropriate for use in a wide variety of applications of modal logic, from planning to logic programming
Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities
Decision-focused learning (DFL) is an emerging paradigm in machine learning
which trains a model to optimize decisions, integrating prediction and
optimization in an end-to-end system. This paradigm holds the promise to
revolutionize decision-making in many real-world applications which operate
under uncertainty, where the estimation of unknown parameters within these
decision models often becomes a substantial roadblock. This paper presents a
comprehensive review of DFL. It provides an in-depth analysis of the various
techniques devised to integrate machine learning and optimization models,
introduces a taxonomy of DFL methods distinguished by their unique
characteristics, and conducts an extensive empirical evaluation of these
methods proposing suitable benchmark dataset and tasks for DFL. Finally, the
study provides valuable insights into current and potential future avenues in
DFL research.Comment: Experimental Survey and Benchmarkin
- …