consistent labeling problems and their algorithms expected complexities and theory based heuristics a new parameter is introduced to characterize a type of search problem of broad relevance in artificial intelligence operations research and symbolic logic this parameter which we call inter variable compatibility is particularly important in that complexity analyses incorporating it are able to capture the dependence of problem complexity on search order used by an algorithm thus compatibility based theories can provide a theoretical basis for the extraction of heuristics for choosing good search orderings a long sought goal for such problems since it can lead to significant savings during search we carry out expected complexity analyses for the traditional backtrack algorithm as well as for two more recent algorithms that have been found empirically to be significant improvements forward checking and word wise forward checking we extract compatibility based ordering heuristics from the theory for forward checking preliminary experimental results are presented showing the large savings that result from their use similar savings can be expected for other algorithms when heuristics taking account of inter variable compatibilities are used our compatibility based theories also provide a more precise way of predicting which algorithm is best for a given problem

dynamic balanced randomization for clinical trials common methods of treatment allocation for multi centre and or stratified randomized clinical trials can result in substantial differences between the number of patients allocated to each treatment arm this can occur in the overall trial for a permuted block design or within individual institutions strata when using a minimization scheme this may lead to a bias in the result also these procedures can be predictable with the possibility of an investigator introduced selection bias an easily implemented method of randomization is proposed which attempts to overcome these problems by balancing treatment allocations both within strata and across the trial as a whole the method keeps a running tally on total treatment allocation numbers at all stratification levels when a patient accrues a hierarchical decision rule is applied and the allocation is deterministic if certain pre defined limits are exceeded and random otherwise the method is an extension of the big stick design of soares and wu and is related to both zelen s key number randomization methods and the schemes of nordle and brantmark simulation studies are used to demonstrate that major imbalances possible with other schemes do not occur using this method and that the potential for selection bias is much reduced

noise memory induced excitability and pattern formation in oscillatory neural models we report a noise memory induced phase transition in an array of oscillatory neural systems which leads to the suppression of synchronous oscillations and restoration of excitable dynamics this phenomenon is caused by the systematic contributions of temporally correlated parametric noise i e possessing a memory which stabilizes a deterministically unstable fixed point changing the noise correlation time a reentrant phase transition to noise induced excitability is observed in a globally coupled array since noise induced excitability implies the restoration of the ability to transmit information associated spatiotemporal patterns are observed afterwards furthermore an analytic approach to predict the systematic effects of exponentially correlated noise is presented and its results are compared with the simulations

optimal allocation for the comparison of proportions optimal allocation strategies for the comparison of proportions p1 and p2 in two groups are discussed allocations which i maximize the precision in the estimation of the difference p1 p2 ii maximize the precision in the estimation of the ratio p1 p2 iii maximize the power to detect a group difference and iv minimize the total cost of a study are compared the recommended allocation varies markedly with the desired objective furthermore there is a wide range of allocation schemes which are effectively optimal with regard to each criterion considered a study of congenital malformations occurring in pregnancies of diabetic women is used to illustrate how these considerations apply to the planning of a study

temporal constraint networks abstract this paper extends network based methods of constraint satisfaction to include continuous variables thus providing a framework for processing temporal constraints in this framework called temporal constraint satisfaction problem tcsp variables represent time points and temporal information is represented by a set of unary and binary constraints each specifying a set of permitted intervals the unique feature of this framework lies in permitting the processing of metric information namely assessments of time differences between events we present algorithms for performing the following reasoning tasks finding all feasible times that a given event can occur finding all possible relationships between two given events and generating one or more scenarios consistent with the information provided we distinguish between simple temporal problems stps and general temporal problems the former admitting at most one interval constraint on any pair of time points we show that the stp which subsumes the major part of vilain and kautz s point algebra can be solved in polynomial time for general tcsps we present a decomposition scheme that performs the three reasoning tasks considered and introduce a variety of techniques for improving its efficiency we also study the applicability of path consistency algorithms as preprocessing of temporal problems demonstrate their termination and bound their complexities

influence of spatiotemporally correlated noise on structure formation in excitable media we discuss the influence of additive spatiotemporally correlated i e colored noise on pattern formation in a two dimensional network of excitable systems the signature of spatiotemporal stochastic resonance stsr is analyzed using cross correlation and information theoretic measures it is found that the stsr behavior is affected by both the spatial and temporal correlations of the noise due to an interplay with the length scales of the deterministic network increasing the spatiotemporal noise correlation shifts the occurrence of stsr to smaller values of the noise variance additionally if the spatial correlation of the noise exceeds that of the network the excitation patterns disappear in favor of cloudy structures directly rendering the underlying spatial noise field

the complexity of some polynomial network consistency algorithms for constraint satisfaction problems abstract constraint satisfaction problems play a central role in artificial intelligence a class of network consistency algorithms for eliminating local inconsistencies in such problems has previously been described we analyze the time complexity of several node arc and path consistency algorithms and prove that arc consistency is achievable in time linear in the number of binary constraints the waltz filtering algorithm is a special case of the arc consistency algorithm in the edge labelling computational vision application the constraint graph is planar and so the time complexity is linear in the number of variables

fast algorithms for solving path problems let g v e be a directed graph with a distinguished source vertex s the single source path expression problem is to find for each vertex v a regular expression p s v which represents the set of all paths in g from s to v a solution to this problem can be used to solve shortest path problems solve sparse systems of linear equations and carry out global flow analysis we describe a method to compute path expressions by dividing g into components computing path expressions on the components by gaussian elimination and combining the solutions this method requires o m alpha m n time on a reducible flow graph where n is the number of vertices in g m is the number of edges in g and alpha is a functional inverse of ackermann s function the method makes use of an algorithm for evaluating functions defined on paths in trees a simplified version of the algorithm which runs in o m log n time on reducible flow graphs is quite easy to implement and efficient in practice

formal language constrained path problems given an alphabet sigma a directed graph g whose edges are weighted and sigma labeled and a formal language l subseteq sigma the formal language constrained shortest simple path problem consists of finding a shortest simple path p in g complying with the additional constraint that l p in l here l p denotes the unique word obtained by concatenating the sigma labels of the edges along the path p the main contributions of this paper include the following we show that the formal language constrained shortest path problem is solvable efficiently in polynomial time when l is restricted to be a context free language cfl when l is specified as a regular language we provide algorithms with improved space and time bounds in contrast we show that the problem of finding a simple path between a source and a given destination is np hard even when l is restricted to fixed simple regular languages and to very simple classes of graphs e g complete grids for the class of treewidth bounded graphs we show that i the problem of finding a regular language constrained simple path between source and destination is solvable in polynomial time and ii the extension to finding cfl constrained simple paths is np complete our results extend the previous results in siam j comput 24 1995 pp 1235 1258 proceedings of the 76th annual meeting of the transportation research board 1997 and proceedings of the 9th acm sigact sigmod sigart symposium on database systems 1990 pp 230 242 several additional extensions and applications of our results in the context of transportation problems are presented for instance as a corollary of our results we obtain a polynomial time algorithm for the best k similar path problem studied in proceedings of the 76th annual meeting of the transportation reasearch board 1997 the previous best algorithm was given by proceedings of the 76th annual meeting of the transportation research board 1997 and takes exponential time in the worst case

network based heuristics for constraint satisfaction problems abstract many ai tasks can be formulated as constraint satisfaction problems csp i e the assignment of values to variables subject to a set of constraints while some csps are hard those that are easy can often be mapped into sparse networks of constraints which in the extreme case are trees this paper identifies classes of problems that lend themselves to easy solutions and develops algorithms that solve these problems optimally the paper then presents a method of generating heuristic advice to guide the order of value assignments based on both the sparseness found in the constraint network and the simplicity of tree structured csps the advice is generated by simplifying the pending subproblems into trees counting the number of consistent solutions in each simplified subproblem and comparing these counts to decide among the choices pending in the original problem

use of unequal allocation in survival trials in some two treatment clinical survival trials a large imbalance in the allocation of patients to treatments will result in approximately the same power for the logrank test as equal allocation this fact can be used in some trials to reduce significantly the number of patients allocated to a potentially inferior treatment

lifetime enhancement of scroll rings by spatiotemporal fluctuations the dynamics of three dimensional scroll rings with spatiotemporal random excitability is investigated numerically using the fitzhugh nagumo model depending on the correlation time and length scales of the fluctuations the lifetime of the ring filament is enlarged and a resonance effect between the time scale of the scroll ring and the time correlation of the noise is observed numerical results are interpreted in terms of a simplified stochastic model derived from the kinematical equations for three dimensional excitable waves

search rearrangement backtracking and polynomial average time the average time required for simple search rearrangement backtracking is compared with that for ordinary backtracking when each algorithm is used to find all solutions for random conjunctive normal form predicates the sets of random predicates are characterized by v the number of variables t v the number of clauses and p v the probability that a literal appears in clause for large v if vp v 1n 2 there is a difficult region where the average number of solutions per problem is exponentially small but backtracking requires an exponentially large time the difficult region for search rearrangement backtracking is only slightly smaller than the difficult region for ordinary backtracking it is conjectured that search rearrangement backtracking is exponentially faster than ordinary backtracking for nearly all of the difficult region it is proved that there is no major advantage in using search rearrangement backtracking outside of the difficult region

local consistency for extended csps we extend the framework of constraint satisfaction problems to make it more suitable for applicable to modern constraint programming languages where both constraint satisfaction and constraint solving have a role some rough principles for local consistency conditions in the extended framework are developed appropriate notions of local consistency are formulated and relationships between the various consistency conditions are established

combining qualitative and quantitative constraints in temporal reasoning abstract this paper presents a general model for temporal reasoning that is capable of handling both qualitative and quantitative information this model allows the representation and processing of many types of constraints discussed in the literature to date including metric constraints restricting the distance between time points and qualitative disjunctive constraints specifying the relative position of temporal objects reasoning tasks in this unified framework are formulated as constraint satisfaction problems and are solved by traditional constraint satisfaction techniques such as backtracking and path consistency new classes of tractable problems are characterized involving qualitative networks augmented by quantitative domain constraints some of which can be solved in polynomial time using arc and path consistency

simple linear time algorithms to test chordality of graphs test acyclicity of hypergraphs and selectively reduce acyclic hypergraphs chordal graphs arise naturally in the study of gaussian elimination on sparse symmetric matrices acyclic hypergraphs arise in the study of relational data bases rose tarjan and lueker siam j c

ftclogic fuzzy temporal constraint logic abstract in this paper we present ftclogic a formal first order logic that can manage fuzzy temporal constraints between variables efficiently in this logic the use of explicit temporal axioms is unnecessary and therefore the deduction mechanism doesn t slow down for this reason ftclogic has an immediate precedent the extended fuzzy temporal constraint logic or eftcl however while eftcl is based on timed possibilistic logic ftclogic uses the possibilistic logic to formulate an original semantics according to its syntax in fact ftclogic defines both syntax and semantics from a powerful combination of two formalisms the possibilistic logic and the fuzzy temporal constraints networks ftclogic has provided the basis for the creation of a fuzzy temporal prolog prologic which is implemented through haskell and which is currently undergoing evaluation

deciding linear inequalities by computing loop residues v r pratt has shown that the real and integer feastbdlty of sets of linear mequallues of the form x y c can be decided quickly by examining the loops m certain graphs pratt s method is generahzed first to real feaslbdlty of mequahues m two variables and arbitrary coefficients and ultimately to real feaslbdlty of arbitrary sets of hnear mequahtles the method is well suited to apphcatlons m program verification

enhancement schemes for constraint processing backjumping learning and cutset decomposition abstract researchers in the areas of constraint satisfaction problems logic programming and truth maintenance systems have suggested various schemes for enhancing the performance of the backtracking algorithm this paper defines and compares the performance of three such schemes backjumping learning and cycle cutset the backjumping and the cycle cutset methods work best when the constraint graph is sparse while the learning scheme mostly benefits problem instances with dense constraint graphs an integrated strategy is described which utilizes the distinct advantages of each scheme experiments show that in hard problems the average improvement realized by the integrated scheme is 20 25 higher than any of the individual schemes

tractable disjunctions of linear constraints basic results and applications to temporal reasoning we study the problems of deciding consistency and performing variable elimination for disjunctions of linear inequalities and disequations with at most one inequality per disjunction this new class of constraints extends the class of generalized linear constraints originally studied by lassez and mcaloon we show that deciding consistency of a set of constraints in this class can be done in polynomial time we also present a variable elimination algorithm which is similar to fourier s algorithm for linear inequalities finally we use these results to provide new temporal reasoning algorithms for the ord horn subclass of allen s interval formalism we also show that there is no low level of local consistency that can guarantee global consistency for the ord horn subclass this property distinguishes the ord horn subclass from the pointizable subclass for which strong 5 consistency is sufficient to guarantee global consistency and the continuous endpoint subclass for which strong 3 consistency is sufficient to guarantee global consistency copyright 2001 elsevier science b v

a unified approach to path problems we describe a general method for solving path problems on directed graphs such path problems include finding shortest paths solving sparse systems of linear equations and carrying out global flow analysis of computer programs our method consists of two steps first we construct a collection of regular expressions representing sets of paths in the graph this can be done by using any standard algorithm such as gaussian or gauss jordan elimination next we apply a natural mapping from regular expressions into the given problem domain we exhibit the mappings required to find shortest paths solve sparse systems of linear equations and carry out global flow analysis our results provide a general purpose algorithm for solving any path problem and show that the problem of constructing path expressions is in some sense the most general path problem

heuristic testing procedures for general coherent systems abstract we consider the problem of minimizing the expected cost of inspecting a general coherent system except for certain special cases for which simple optimal testing policies do exist the problem is generally known to be computationally intractable in this paper we first give some upper and lower bounds on the minimum expected total inspection cost then we propose some heuristic optimization procedures for solving the problem approximately our computational experience indicates that these heuristics are extremely effective in comparison with the dynamic programming exact solution procedure

noise induced stabilization of bumps in systems with long range spatial coupling the position of a localized region of active neurons a bump has been proposed to encode information for working memory the head direction system and feature selectivity in the visual system stationary bumps are ordinarily stable but including spike frequency adaptation in the neural dynamics causes a stationary bump to become unstable to a moving bump through a supercritical pitchfork bifurcation in bump speed adding spatiotemporal noise to the network supporting the bump can cause the average speed of the bump to decrease to almost zero reversing the effect of the adaptation and restabilizing the bump this restabilizing occurs for noise levels lower than those required to break up the bump the restabilizing can be understood by examining the effects of noise on the normal form of the pitchfork bifurcation where the variable involved in the bifurcation is bump speed this noisy normal form can be further simplified to a persistent random walk in which the probability of changing direction is related to the noise level through an arrhenius type rate the probability density function of position for the continuous time version of this random walk satisfies the telegrapher s equation and the closed form solution of this pde allows us to find expressions for the mean and variance of the average speed of the particle the bump undergoing the random walk this noise induced stabilization is a novel example in which moderate amounts of noise have a beneficial effect on a system specifically stabilizing a spatiotemporal pattern 2001 elsevier science b v all rights reserved

tree clustering for constraint networks research note abstract the paper offers a systematic way of regrouping constraints into hierarchical structures capable of supporting search without backtracking the method involves the formation and preprocessing of an acyclic database that permits a large variety of queries and local perturbations to be processed swiftly either by sequential backtrack free procedures or by distributed constraint propagation processes

periodic sets of integers abstract consider the following kinds of sets the set of all possible distances between two vertices of a directed graph any set of integers that is either finite or periodic for all n greater or equal to some n0 such a set is called ultimately periodic a context free language over an alphabet with one letter such a language is also regular the set of all possible lengths of words of a context free language all these sets are isomorphic relatively to the operations of union or sum concatenation and kleene or transitive closure furthermore they all share a particularly important property which is not valid in some similar algebraic structure the concatenation is commutative the purpose of this paper is to investigate the representation and properties of these sets and also the algorithms to compute the operations mentioned above the concepts of linear number and sum are developed in order to provide convenient methods of representation and manipulation it should be noted that although sums and regular expressions or finite automata over a one letter alphabet denote essentially the same sets the corresponding algebras are quite different for example it is always possible to eliminate the closure and concatenation operations from a sum by expanding it as a sum of linear numbers no such elimination is possible for regular expressions although special forms of regular expressions or finite automata are sufficient to denote regular sets over one letter alphabets the algorithms using sums are often faster and simpler than those based on finite automata or regular expressions over a one letter alphabet we think that this improvement comes from the fact that a set of words over one letter is represented by the set of their lengths and manipulated by arithmetic operations we apply these methods to the first kind of sets listed above and present new algorithms dealing with a variety of problems related to distances in directed graphs

on the computational complexity of querying bounds on differences constraints abstract given a consistent knowledge base formed by a set of constraints efficient query answering e g checking whether a set of constraints is consistent with the knowledge base or necessarily true in it is practically very important in the paper we consider bounds on differences which are an important class of constraints based on linear inequalities and we analyze the computational complexity of query answering more specifically we consider various common types of queries and we prove that if the minimal network produced by constraint satisfaction algorithms and characterizing the solutions to a set of constraints is maintained then the complexity of answering a query depends only on the dimension of the query and not on the dimension of the knowledge base which is usually much larger than the query we also analyse how the approach can be used to deal efficiently with a class of updates to the knowledge base some applications of the results are sketched in the conclusion

a unifying approach to temporal constraint reasoning abstract we present a formalism disjunctive linear relations dlrs for reasoning about temporal constraints dlrs subsume most of the formalisms for temporal constraint reasoning proposed in the literature and is therefore computationally expensive we also present a restricted type of dlrs horn dlrs which have a polynomial time satisfiability problem we prove that most approaches to tractable temporal constraint reasoning can be encoded as horn dlrs including the ord horn algebra by nebel and burckert and the simple temporal constraints by dechter et al thus dlrs is a suitable unifying formalism for reasoning about temporal constraints

towards a general theory of action and time abstract a formalism for reasoning about actions is proposed that is based on a temporal logic it allows a much wider range of actions to be described than with previous approaches such as the situation calculus this formalism is then used to characterize the different types of events processes actions and properties that can be described in simple english sentences in addressing this problem we consider actions that involve non activity as well as actions that can only be defined in terms of the beliefs and intentions of the actors finally a framework for planning in a dynamic world with external events and multiple agents is suggested

on point duration networks for temporal reasoning we present here a point duration network formalism which extends the point algebra model to include additional variables that represent durations between points of time thereafter the new qualitative model is enlarged for allowing unary metric constraints on points and durations subsuming in this way several point based approaches to temporal reasoning we deal with some reasoning tasks within the new models and we show that the main problem deciding consistency is np complete however tractable special cases are identified and we show efficient algorithms for checking consistency finding a solution and obtaining the minimal network

constraint propagation with interval labels abstract constraint propagation is often used in ai systems to perform inference about quantities this paper studies one particular kind of constraint propagation where quantities are labelled with signs or with intervals and these labels are propagated through recorded constraints we review the uses of such inference schemes in ai systems of various kinds and evaluate their strengths and weaknesses in particular we determine the completeness and running time of constraint propagation for various kinds of labels and constraints

fuzzy constraint networks for signal pattern recognition this paper deals with representation and reasoning on information concerning the evolution of a physical parameter by means of a model based on the fuzzy constraint satisfaction problem formalism and with which it is possible to define what we call fuzzy temporal profiles ftp based on fundamentally linguistic information this model allows the integration of knowledge on the evolution of a set of parameters into a knowledge representation scheme in which time plays a fundamental role the ftp model describes the behaviour of a physical parameter on the basis of a set of signal events and which allows the evolution of the parameter between each pair of events to be modelled as signal episodes given the fundamentally linguistic nature of the information represented the consistency analysis of this information is an essential task nevertheless the obtention of the minimal representation of the network that defines an ftp is an np hard problem in spite of this we supply algorithms guaranteeing local levels of consistency that allow to correct a large proportion of the errors committed by a human expert in the linguistic description of the profile furthermore we propose a new topology whose consistency can be guaranteed in polynomial time we also study the applicability of this model in the recognition of signal patterns

algebraic structures with hard equivalence and minimization problems on considere la relation entre la forme dans laquelle un probleme algebrique est pose et la complexite de resoudre le probleme les problemes etudies sont l equivalence la minimisation et les problemes de minimisation approchee pour des formules comprenant des variables des parentheses des operateurs et optionnellement des constantes