ALBCOM - Algorismia, Bioinformàtica, Complexitat i Mètodes Formals
http://hdl.handle.net/2117/3092
2017-05-25T05:09:57ZNon recursive functions have transcendental generating functions
http://hdl.handle.net/2117/104671
Non recursive functions have transcendental generating functions
Cucker Farkas, Juan Felipe; Gabarró Vallès, Joaquim
Proves that nonprimitive recursive functions have transcendental generating series. This result translates a certain measure of the complexity of a function, the fact of not being primitive recursive, into another measure of the complexity of the generating series associated to the function, the fact of being transcendental.; On démontre que les fonctions qui ne sont pas recursives primitives ont des séries génératrices transcendantes. Ce résultat traduit une certaine mesure de complexité d'une fonction, le fait de ne pas être recursive primitive, dans une autre mesure de la complexité de la série génératrice associée à cette fonction, le fait d'être transcendante.
2017-05-22T09:14:24ZCucker Farkas, Juan FelipeGabarró Vallès, JoaquimProves that nonprimitive recursive functions have transcendental generating series. This result translates a certain measure of the complexity of a function, the fact of not being primitive recursive, into another measure of the complexity of the generating series associated to the function, the fact of being transcendental.
On démontre que les fonctions qui ne sont pas recursives primitives ont des séries génératrices transcendantes. Ce résultat traduit une certaine mesure de complexité d'une fonction, le fait de ne pas être recursive primitive, dans une autre mesure de la complexité de la série génératrice associée à cette fonction, le fait d'être transcendante.Nonuniform complexity classes specified by lower and upper bounds
http://hdl.handle.net/2117/104347
Nonuniform complexity classes specified by lower and upper bounds
Balcázar Navarro, José Luis; Gabarró Vallès, Joaquim
We characterize in terms of oracle Turing machines the classes defined by exponential lower bounds on some nonuniform complexity measures. After, we use the same methods to giue a new characterization of classes defined by polynomial and polylog upper bounds, obtaining an unified approach to deal with upper and lower bounds, The main measures are the initial index, the context-free cosU ond the boolean circuits size. We interpret our results by discussing a trade- off between oracle information and computed information for oracle Turing machines.; NOMS caractérisons en termes de machines de Turing avec oracles les classes définies par des bornes inférieures exponentielles pour des mesures de complexité non uniformes. Nous utilisons ensuite les mêmes méthodes pour donner une nouvelle caractérisation des classes définies par des bornes supérieures polynomiales et polylogarithmiques, obtenanrainsi une approche unifiée pour les bornes inférieures et supérieures. Les mesures principales sont F index initial, le coût grammatical et la taille des circuits booléens. Nous interprétons nos résultats en étudiant, pour les machines de Turing avec oracle, la relation entre l'information due à Voracle et l'information calculée par la machine.
2017-05-12T08:15:24ZBalcázar Navarro, José LuisGabarró Vallès, JoaquimWe characterize in terms of oracle Turing machines the classes defined by exponential lower bounds on some nonuniform complexity measures. After, we use the same methods to giue a new characterization of classes defined by polynomial and polylog upper bounds, obtaining an unified approach to deal with upper and lower bounds, The main measures are the initial index, the context-free cosU ond the boolean circuits size. We interpret our results by discussing a trade- off between oracle information and computed information for oracle Turing machines.
NOMS caractérisons en termes de machines de Turing avec oracles les classes définies par des bornes inférieures exponentielles pour des mesures de complexité non uniformes. Nous utilisons ensuite les mêmes méthodes pour donner une nouvelle caractérisation des classes définies par des bornes supérieures polynomiales et polylogarithmiques, obtenanrainsi une approche unifiée pour les bornes inférieures et supérieures. Les mesures principales sont F index initial, le coût grammatical et la taille des circuits booléens. Nous interprétons nos résultats en étudiant, pour les machines de Turing avec oracle, la relation entre l'information due à Voracle et l'information calculée par la machine.Anti-alignments in conformance checking: the dark side of process models
http://hdl.handle.net/2117/103958
Anti-alignments in conformance checking: the dark side of process models
Chatain, Thomas; Carmona Vargas, Josep
Conformance checking techniques asses the suitability of a process model in representing an underlying process, observed through a collection of real executions. These techniques suffer from the wellknown state space explosion problem, hence handling process models exhibiting large or even infinite state spaces remains a challenge. One important metric in conformance checking is to asses the precision of the model with respect to the observed executions, i.e., characterize the ability of the model to produce behavior unrelated to the one observed. By avoiding the computation of the full state space of a model, current techniques only provide estimations of the precision metric, which in some situations tend to be very optimistic, thus hiding real problems a process model may have. In this paper we present the notion of antialignment as a concept to help unveiling traces in the model that may deviate significantly from the observed behavior. Using anti-alignments, current estimations can be improved, e.g., in precision checking. We show how to express the problem of finding anti-alignments as the satisfiability of a Boolean formula, and provide a tool which can deal with large models efficiently.
2017-05-03T11:38:28ZChatain, ThomasCarmona Vargas, JosepConformance checking techniques asses the suitability of a process model in representing an underlying process, observed through a collection of real executions. These techniques suffer from the wellknown state space explosion problem, hence handling process models exhibiting large or even infinite state spaces remains a challenge. One important metric in conformance checking is to asses the precision of the model with respect to the observed executions, i.e., characterize the ability of the model to produce behavior unrelated to the one observed. By avoiding the computation of the full state space of a model, current techniques only provide estimations of the precision metric, which in some situations tend to be very optimistic, thus hiding real problems a process model may have. In this paper we present the notion of antialignment as a concept to help unveiling traces in the model that may deviate significantly from the observed behavior. Using anti-alignments, current estimations can be improved, e.g., in precision checking. We show how to express the problem of finding anti-alignments as the satisfiability of a Boolean formula, and provide a tool which can deal with large models efficiently.Trade-offs between time and memory in a tighter model of CDCL SAT solvers
http://hdl.handle.net/2117/103872
Trade-offs between time and memory in a tighter model of CDCL SAT solvers
Elffers, J.; Johannsen, Jan; Lauria, Massimo; Magnard, Thomas; Nordström, Jakob; Vinyals, Marc
A long line of research has studied the power of conflict- driven clause learning (CDCL) and how it compares to the resolution proof system in which it searches for proofs. It has been shown that CDCL can polynomially simulate resolution even with an adversarially chosen learning scheme as long as it is asserting. However, the simulation only works under the assumption that no learned clauses are ever forgot- ten, and the polynomial blow-up is significant. Moreover, the simulation requires very frequent restarts, whereas the power of CDCL with less frequent or entirely without restarts remains poorly understood. With a view towards obtaining results with tighter relations between CDCL and resolution, we introduce a more fine-grained model of CDCL that cap- tures not only time but also memory usage and number of restarts. We show how previously established strong size-space trade-offs for resolution can be transformed into equally strong trade-offs between time and memory usage for CDCL, where the upper bounds hold for CDCL with- out any restarts using the standard 1UIP clause learning scheme, and the (in some cases tightly matching) lower bounds hold for arbitrarily frequent restarts and arbitrary clause learning schemes.
"The final publication is available at http://link.springer.com/chapter/10.1007/978-3-319-40970-2_11
2017-04-28T20:33:22ZElffers, J.Johannsen, JanLauria, MassimoMagnard, ThomasNordström, JakobVinyals, MarcA long line of research has studied the power of conflict- driven clause learning (CDCL) and how it compares to the resolution proof system in which it searches for proofs. It has been shown that CDCL can polynomially simulate resolution even with an adversarially chosen learning scheme as long as it is asserting. However, the simulation only works under the assumption that no learned clauses are ever forgot- ten, and the polynomial blow-up is significant. Moreover, the simulation requires very frequent restarts, whereas the power of CDCL with less frequent or entirely without restarts remains poorly understood. With a view towards obtaining results with tighter relations between CDCL and resolution, we introduce a more fine-grained model of CDCL that cap- tures not only time but also memory usage and number of restarts. We show how previously established strong size-space trade-offs for resolution can be transformed into equally strong trade-offs between time and memory usage for CDCL, where the upper bounds hold for CDCL with- out any restarts using the standard 1UIP clause learning scheme, and the (in some cases tightly matching) lower bounds hold for arbitrarily frequent restarts and arbitrary clause learning schemes.The complexity of testing properties of simple games
http://hdl.handle.net/2117/103171
The complexity of testing properties of simple games
Freixas Bosch, Josep; Molinero Albareda, Xavier; Olsen, Martin; Serna Iglesias, María José
Simple games cover voting systems in which a single alternative, such as a bill or an amendment, is pitted against the status quo. A simple game or a yes-no voting system is a set of rules that specifies exactly which collections of ``yea'' votes yield passage of the issue at hand. A collection of ``yea'' voters forms a winning coalition.
We are interested on performing a complexity analysis of problems on such games depending on the game representation. We consider four natural explicit representations, winning, loosing, minimal winning, and maximal loosing. We first analyze the computational complexity of obtaining a particular representation of a simple game from a different one. We show that some cases this transformation can be done in polynomial time while the others require exponential time. The second question is classifying the complexity for testing whether a game is simple or weighted. We show that for the four types of representation both problem can be solved in polynomial time. Finally, we provide results on the complexity of testing whether a simple game or a weighted game is of a special type. In this way, we analyze strongness, properness, decisiveness and homogeneity, which are desirable properties to be fulfilled for a simple game.
2017-03-31T15:48:07ZFreixas Bosch, JosepMolinero Albareda, XavierOlsen, MartinSerna Iglesias, María JoséSimple games cover voting systems in which a single alternative, such as a bill or an amendment, is pitted against the status quo. A simple game or a yes-no voting system is a set of rules that specifies exactly which collections of ``yea'' votes yield passage of the issue at hand. A collection of ``yea'' voters forms a winning coalition.
We are interested on performing a complexity analysis of problems on such games depending on the game representation. We consider four natural explicit representations, winning, loosing, minimal winning, and maximal loosing. We first analyze the computational complexity of obtaining a particular representation of a simple game from a different one. We show that some cases this transformation can be done in polynomial time while the others require exponential time. The second question is classifying the complexity for testing whether a game is simple or weighted. We show that for the four types of representation both problem can be solved in polynomial time. Finally, we provide results on the complexity of testing whether a simple game or a weighted game is of a special type. In this way, we analyze strongness, properness, decisiveness and homogeneity, which are desirable properties to be fulfilled for a simple game.Computing alignments with constraint programming : the acyclic case
http://hdl.handle.net/2117/103063
Computing alignments with constraint programming : the acyclic case
Borrego, Diana; Gómez López, María Teresa; Carmona Vargas, Josep; Martínez Gasca, Rafael
Conformance checking confronts process models with real process executions to detect and measure deviations between modelled and observed behaviour. The core technique for conformance checking is the computation of an alignment. Current approaches for alignment computation rely on a shortest-path technique over the product of the state-space of a model and the observed trace, thus suffering from the well-known state explosion problem. This paper presents a fresh alternative for alignment computation of acyclic process models, that encodes the alignment problem as a Constraint Satisfaction Problem. Since modern solvers for this framework are capable of dealing with large instances, this contribution has a clear potential. Remarkably, our prototype implementation can handle instances that represent a real challenge for current techniques. Main advantages of using Constraint Programming paradigm lie in the possibility to adapt parameters such as the maximum search time, or the maximum misalignment allowed. Moreover, using search and propagation algorithms incorporated in Constraint Programming Solvers permits to find solutions for problems unsolvable with other techniques.
2017-03-30T06:45:05ZBorrego, DianaGómez López, María TeresaCarmona Vargas, JosepMartínez Gasca, RafaelConformance checking confronts process models with real process executions to detect and measure deviations between modelled and observed behaviour. The core technique for conformance checking is the computation of an alignment. Current approaches for alignment computation rely on a shortest-path technique over the product of the state-space of a model and the observed trace, thus suffering from the well-known state explosion problem. This paper presents a fresh alternative for alignment computation of acyclic process models, that encodes the alignment problem as a Constraint Satisfaction Problem. Since modern solvers for this framework are capable of dealing with large instances, this contribution has a clear potential. Remarkably, our prototype implementation can handle instances that represent a real challenge for current techniques. Main advantages of using Constraint Programming paradigm lie in the possibility to adapt parameters such as the maximum search time, or the maximum misalignment allowed. Moreover, using search and propagation algorithms incorporated in Constraint Programming Solvers permits to find solutions for problems unsolvable with other techniques.The HOM problem is EXPTIME-complete
http://hdl.handle.net/2117/102817
The HOM problem is EXPTIME-complete
Creus López, Carles; Gascon Caro, Adrian; Godoy Balil, Guillem; Ramos Garrido, Lander
We define a new class of tree automata with constraints and prove decidability of the emptiness problem for this class in exponential time. As a consequence, we obtain several EXPTIME-completeness results for problems on images of regular tree languages under tree homomorphisms, like set inclusion, regularity (HOM problem), and finiteness of set difference. Our result also has implications in term rewriting, since the set of reducible terms of a term rewrite system can be described as the image of a tree homomorphism. In particular, we prove that inclusion of sets of normal forms of term rewrite systems can be decided in exponential time. Analogous consequences arise in the context of XML typechecking, since types are defined by tree automata and some type transformations are homomorphic.
2017-03-23T09:26:34ZCreus López, CarlesGascon Caro, AdrianGodoy Balil, GuillemRamos Garrido, LanderWe define a new class of tree automata with constraints and prove decidability of the emptiness problem for this class in exponential time. As a consequence, we obtain several EXPTIME-completeness results for problems on images of regular tree languages under tree homomorphisms, like set inclusion, regularity (HOM problem), and finiteness of set difference. Our result also has implications in term rewriting, since the set of reducible terms of a term rewrite system can be described as the image of a tree homomorphism. In particular, we prove that inclusion of sets of normal forms of term rewrite systems can be decided in exponential time. Analogous consequences arise in the context of XML typechecking, since types are defined by tree automata and some type transformations are homomorphic.Construct, Merge, Solve and Adapt: Application to the repetition-free longest common subsequence problem
http://hdl.handle.net/2117/102814
Construct, Merge, Solve and Adapt: Application to the repetition-free longest common subsequence problem
Blum, Christian; Blesa Aguilera, Maria Josep
In this paper we present the application of a recently proposed, general, algorithm for combinatorial optimization to the repetition-free longest common subsequence problem. The applied algorithm, which is labelled Construct, Merge, Solve & Adapt, generates sub-instances based on merging the solution components found in randomly constructed solutions. These sub-instances are subsequently solved by means of an exact solver. Moreover, the considered sub-instances are dynamically changing due to adding new solution components at each iteration, and removing existing solution components on the basis of indicators about their usefulness. The results of applying this algorithm to the repetition-free longest common subsequence problem show that the algorithm generally outperforms competing approaches from the literature. Moreover, they show that the algorithm is competitive with CPLEX for small and medium size problem instances, whereas it outperforms CPLEX for larger problem instances.
2017-03-23T07:48:23ZBlum, ChristianBlesa Aguilera, Maria JosepIn this paper we present the application of a recently proposed, general, algorithm for combinatorial optimization to the repetition-free longest common subsequence problem. The applied algorithm, which is labelled Construct, Merge, Solve & Adapt, generates sub-instances based on merging the solution components found in randomly constructed solutions. These sub-instances are subsequently solved by means of an exact solver. Moreover, the considered sub-instances are dynamically changing due to adding new solution components at each iteration, and removing existing solution components on the basis of indicators about their usefulness. The results of applying this algorithm to the repetition-free longest common subsequence problem show that the algorithm generally outperforms competing approaches from the literature. Moreover, they show that the algorithm is competitive with CPLEX for small and medium size problem instances, whereas it outperforms CPLEX for larger problem instances.On the stability of generalized second price auctions with budgets
http://hdl.handle.net/2117/101923
On the stability of generalized second price auctions with budgets
Díaz Cort, Josep; Giotis, Ioannis; Kirousis, Lefteris; Markakis, Evangelos; Serna Iglesias, María José
The Generalized Second Price (GSP) auction used typically to model sponsored search auctions does not include the notion of budget constraints, which is present in practice. Motivated by this, we introduce the different variants of GSP auctions that take budgets into account in natural ways. We examine their stability by focusing on the existence of Nash equilibria and envy-free assignments. We highlight the differences between these mechanisms and find that only some of them exhibit both notions of stability. This shows the importance of carefully picking the right mechanism to ensure stable outcomes in the presence of budgets.
2017-03-04T12:43:43ZDíaz Cort, JosepGiotis, IoannisKirousis, LefterisMarkakis, EvangelosSerna Iglesias, María JoséThe Generalized Second Price (GSP) auction used typically to model sponsored search auctions does not include the notion of budget constraints, which is present in practice. Motivated by this, we introduce the different variants of GSP auctions that take budgets into account in natural ways. We examine their stability by focusing on the existence of Nash equilibria and envy-free assignments. We highlight the differences between these mechanisms and find that only some of them exhibit both notions of stability. This shows the importance of carefully picking the right mechanism to ensure stable outcomes in the presence of budgets.Fraud detection in energy consumption: a supervised approach
http://hdl.handle.net/2117/101913
Fraud detection in energy consumption: a supervised approach
Coma Puig, Bernat; Carmona Vargas, Josep; Gavaldà Mestre, Ricard; Alcoverro, Santiago; Martín, Victor
Data from utility meters (gas, electricity, water) is a rich source of information for distribution companies, beyond billing. In this paper we present a supervised technique, which primarily but not only feeds on meter information, to detect meter anomalies and customer fraudulent behavior (meter tampering). Our system detects anomalous meter readings on the basis of models built using machine learning techniques on past data. Unlike most previous work, it can incrementally incorporate the result of field checks to grow the database of fraud and non-fraud patterns, therefore increasing model precision over time and potentially adapting to emerging fraud patterns. The full system has been developed with a company providing electricity and gas and already used to carry out several field checks, with large improvements in fraud detection over the previous checks which used simpler techniques.
2017-03-03T12:09:34ZComa Puig, BernatCarmona Vargas, JosepGavaldà Mestre, RicardAlcoverro, SantiagoMartín, VictorData from utility meters (gas, electricity, water) is a rich source of information for distribution companies, beyond billing. In this paper we present a supervised technique, which primarily but not only feeds on meter information, to detect meter anomalies and customer fraudulent behavior (meter tampering). Our system detects anomalous meter readings on the basis of models built using machine learning techniques on past data. Unlike most previous work, it can incrementally incorporate the result of field checks to grow the database of fraud and non-fraud patterns, therefore increasing model precision over time and potentially adapting to emerging fraud patterns. The full system has been developed with a company providing electricity and gas and already used to carry out several field checks, with large improvements in fraud detection over the previous checks which used simpler techniques.