Toni Mancini

Detecting and breaking symmetries by reasoning on problem specifications

In this paper we address the problem of detecting and breaking symmetries in combinatorial problems, following the approach of imposing additional symmetry-breaking constraints. Differently from other works in the literature, we attack the problem at the specification level. In fact, many symmetries depend on the structure of the problem, and not on the particular input instance. Hence, they can be easily detected by reasoning on the specification, and appropriate symmetry-breaking formulae generated. We give formal definitions of symmetries and symmetry-breaking formulae on specifications written in existential second-order logic, clarifying the new definitions on some specifications: Graph 3-coloring, Social golfer, and Protein folding problems. Finally, we show experimentally that, applying this technique, even if in a naive way, to specifications written in state-of-the-art languages, e.g., opl, may greatly improve search efficiency.

USING A THEOREM PROVER FOR REASONING ON CONSTRAINT PROBLEMS

The efficiency of systems for constraint programming (CP) is currently highly affected by the actual formulation of the input problem. To this end, several choices have to be made by modelers in order to write efficient specifications and handle instances of realistic size, and this, of course, represents a major obstacle to reach full declarativeness. Several structural properties of problem specifications have been investigated in order to provide techniques that reformulate a constraint program into one which is more efficiently evaluable by the solver at hand. In this paper we consider two such properties, symmetries and functional dependencies among variables, and show that, by characterizing problem specifications as logical formulae, the task of deciding whether such properties hold, and consequently that of performing the relevant reformulations, can be practically mechanized by means of automated theorem proving (ATP) technology. In particular, we report the results on using ATP technology for checking the existence of symmetries, checking whether a given constraint is symmetry-breaking, and checking the existence of functional dependencies in a specification. The output of the reasoning phase is a transformed constraint program, consisting in a reformulated specification and, possibly, a search strategy. We show our techniques on problems such as graph coloring, Sailco inventory, and protein folding.

SAT as an effective solving technology for constraint problems

In this paper we investigate the use of SAT technology for solving constraint problems. In particular, we solve many instances of several common benchmark problems for CP with different SAT solvers, by exploiting the declarative modelling language NPSpec, and Spec2Sat, an application that allows us to compile NPSpec specifications into SAT instances. Furthermore, we start investigating whether some reformulation techniques already used in CP are effective when using SAT as solving engine. We present encouraging experimental results in this direction, showing that this approach can be appealing.

Evaluating ASP and Commercial Solvers on the CSPLib

This paper deals with four solvers for combinatorial problems: the commercial state-of-the-art solver ILOG oplstudio, and the research answer set programming (ASP) systems dlv, smodels and cmodels. The first goal of this research is to evaluate the relative performance of such systems when used in a purely declarative way, using a reproducible and extensible experimental methodology. In particular, we consider a third-party problem library, i.e., the CSPLib, and uniform rules for modelling and instance selection. The second goal is to analyze the marginal effects of popular reformulation techniques on the various solving technologies. In particular, we consider structural symmetry breaking, the adoption of global constraints, and the addition of auxiliary predicates. Finally, we evaluate, on a subset of the problems, the impact of numbers and arithmetic constraints on the different solving technologies. Results show that there is not a single solver winning on all problems, and that reformulation is almost always beneficial: symmetry-breaking may be a good choice, but its complexity has to be carefully chosen, by taking into account also the particular solver used. Global constraints often, but not always, help opl, and the addition of auxiliary predicates is usually worth, especially when dealing with ASP solvers. Moreover, interesting synergies among the various modelling techniques exist.

System Level Formal Verification via Distributed Multi-core Hardware in the Loop Simulation

The goal of System Level Formal Verification (SLFV) is to show system correctness notwithstanding uncontrollable events (such as: faults, variation in system parameters, external inputs, etc). Hardware In the Loop Simulation (HILS) based SLFV attains such a goal by considering exhaustively all relevant simulation scenarios. We present a distributed multi-core algorithm for HILS-based SLFV. Our experimental results on the Fuel Control System example in the Simulink distribution show that by using 64 machines with an 8 core processor each we can complete the SLFV activity in about 27 hours whereas a sequential approach would require more than 200 days. To the best of our knowledge this is the first time that a distributed multi-core algorithm for HILS-based SLFV is presented.

Demand-aware price policy synthesis and verification services for Smart Grids

In management tasks for modern electricity networks the stakeholders face typically two conflicting objectives: maximization of income (increasing demand) and reduction of demand peaks (reducing costs). To improve management of electricity distribution networks, an integrated service-based methodology is presented in this paper. Namely, the proposed approach: i) computes the operational constraints in order to improve utilization of the whole network; ii) enforces those constraints by focusing on each network substation separately; iii) verifies that probability of violating those constraints in nonnominal cases is fairly low. The feasibility of the approach has been tested tested by using a realistic scenario taken from an existing medium voltage Danish distribution network. In such scenario, the proposed method improves the network utilization and offers economic benefits for all the principal participants, i.e. DSOs, retailers and end users.

Anytime System Level Verification via Random Exhaustive Hardware in the Loop Simulation

We present a parallel random exhaustive Hardware In the Loop Simulation based model checker for hybrid systems that, by simulating all operational scenarios exactly once in a uniform random order, is able to provide, at any time during the verification process, an upper bound to the probability that the System Under Verification exhibits an error in a yet-to-be-simulated scenario (Omission Probability). We show effectiveness of the proposed approach by presenting experimental results on System Level Formal Verification of the Fuel Control System example in the Simulink distribution. To the best of our knowledge, no previously published model checker can exhaustively verify hybrid systems of such a size and provide at any time an upper bound to the Omission Probability.

Using a theorem prover for reasoning on constraint problems

Specifications of constraint problems can be considered logical formulae. As a consequence, it is possible to infer their properties by means of automated reasoning tools, with the goal of automatically synthesizing transformations that can make the solving process more efficient. The purpose of this paper is to link two important technologies: automated theorem proving and constraint programming. We report the results on using ATP technology for checking existence of symmetries, checking whether a given formula breaks a symmetry, and checking existence of functional dependencies in a specification. The output of the reasoning phase is a transformed constraint program, consisting in a reformulated specification and, possibly a search strategy. We show our techniques on problems such as Graph coloring, Sailco inventory and Protein folding.

Combining relational algebra, SQL, constraint modelling, and local search

The goal of this paper is to provide a strong integration between constraint modelling and relational DBMSs. To this end we propose extensions of standard query languages such as relational algebra and SQL, by adding constraint modelling capabilities to them. In particular, we propose non-deterministic extensions of both languages, which are specially suited for combinatorial problems. Non-determinism is introduced by means of a guessing operator, which declares a set of relations to have an arbitrary extension. This new operator results in languages with higher expressive power, able to express all problems in the complexity class NP. Some syntactical restrictions which make data complexity polynomial are shown. The effectiveness of both extensions is demonstrated by means of several examples. The current implementation, written in Java using local search techniques, is described.

Lack of Associations between Female Hormone Levels and Visuospatial Working Memory, Divided Attention and Cognitive Bias across Two Consecutive Menstrual Cycles

Background: Interpretation of observational studies on associations between prefrontal cognitive functioning and hormone levels across the female menstrual cycle is complicated due to small sample sizes and poor replicability. Methods: This observational multisite study comprised data of n = 88 menstruating women from Hannover, Germany, and Zurich, Switzerland, assessed during a first cycle and n = 68 re-assessed during a second cycle to rule out practice effects and false-positive chance findings. We assessed visuospatial working memory, attention, cognitive bias and hormone levels at four consecutive time-points across both cycles. In addition to inter-individual differences we examined intra-individual change over time (i.e., within-subject effects). Results: Estrogen, progesterone and testosterone did not relate to inter-individual differences in cognitive functioning. There was a significant negative association between intra-individual change in progesterone and change in working memory from pre-ovulatory to mid-luteal phase during the first cycle, but that association did not replicate in the second cycle. Intra-individual change in testosterone related negatively to change in cognitive bias from menstrual to pre-ovulatory as well as from pre-ovulatory to mid-luteal phase in the first cycle, but these associations did not replicate in the second cycle. Conclusions: There is no consistent association between womens hormone levels, in particular estrogen and progesterone, and attention, working memory and cognitive bias. That is, anecdotal findings observed during the first cycle did not replicate in the second cycle, suggesting that these are false-positives attributable to random variation and systematic biases such as practice effects. Due to methodological limitations, positive findings in the published literature must be interpreted with reservation.