logics of communication and change current dynamic epistemic logics for analyzing effects of informational events often become cumbersome and opaque when common knowledge is added for groups of agents still postconditions involving common knowledge are essential to successful multi agent communication we propose new systems that extend the epistemic base language with a new notion of relativized common knowledge in such a way that the resulting full dynamic logic of information flow allows for a compositional analysis of all epistemic postconditions via perspicuous reduction axioms we also show how such systems can deal with factual alteration rather than just information change making them cover a much wider range of realistic events after a warmup stage of analyzing logics for public announcements our main technical results are expressivity and completeness theorems for a much richer logic that we call lcc this is a dynamic epistemic logic whose static base is propositional dynamic logic pdl interpreted epistemically this system is capable of expressing all model shifting operations with finite action models while providing a compositional analysis for a wide range of informational events this makes lcc a serious candidate for a standard in dynamic epistemic logic as we illustrate by analyzing some complex communication scenarios including sending successive emails with both cc and bcc lines and other private announcements to subgroups our proofs involve standard modal techniques combined with a new application of kleene s theorem on finite automata as well as new ehrenfeucht games of model comparison

non variational effects in a domain wall model equation abstract we study in two dimensions a ginzburg landau equation for a complex amplitude with broken phase invariance the addition of non variational terms breaks the chiral symmetry of the equation and leads to striking effects a non variational term is provided by an external complex field with time dependence our results which are for two dimensional systems can be phrased in the language of domain walls we investigate how these walls move when a weak complex magnetic field is applied there occurs spiral type behavior around stationary points where the amplitude is zero and there exists a critical radius above which circular domains grow

qualitative reasoning about relative direction of oriented points an important issue in qualitative spatial reasoning is the representation of relative directions in this paper we present simple geometric rules that enable reasoning about the relative direction between oriented points this framework the oriented point algebra opra m has a scalable granularity m we develop a simple algorithm for computing the opra m composition tables and prove its correctness using a composition table algebraic closure for a set of opra m statements is very useful for solving spatial navigation tasks it turns out that scalable granularity is useful in these navigation tasks

on the interaction of spiral waves in non equilibrium media abstract we show that the asymptotic interaction of spirals in two dimensionally oscillating continuous media falls off exponentially and can be attractive as well as repulsive depending on the parameters of the system but not on the topological charges the exponent is in qualitative agreement with simulations for moderate distances the simulations show that spirals may form a stable bound state pairs with opposite topological charges drift with constant velocity and like charged spirals rotate around each other with constant frequency this is in contrast with the stationary non oscillating case where the interaction of vortices or dislocations is long range and monotonical and depends on topological charges

asynchronous knowledge with hidden actions in the situation calculus abstract we present a powerful new account of multi agent knowledge in the situation calculus and an automated reasoning procedure for knowledge queries existing accounts of epistemic reasoning in the situation calculus require that whenever an action occurs all agents know that an action has occurred this demands a level of synchronicity that is unreasonable in many multi agent domains in asynchronous domains each agent s knowledge must instead account for arbitrarily long sequences of hidden actions by using a persistence condition meta operator to augment traditional regression techniques we show how agents can reason about their own knowledge using only their internal history of observations rather than requiring a full history of the world the result is a more robust and flexible account of knowledge in the situation calculus suitable for asynchronous partially observable multi agent domains

arbitrary arrow update logic in this paper we introduce arbitrary arrow update logic aaul the logic aaul takes arrow update logic a dynamic epistemic logic where the accessibility relations of agents are updated rather than the set of possible worlds and adds a quantifier over such arrow updates we investigate the relative expressivity of aaul compared to other logics most notably arbitrary public announcement logic apal additionally we show that the model checking problem for aaul is pspace complete finally we introduce a proof system for aaul and prove it to be sound and complete

hidden protocols modifying our expectations in an evolving world when agents know a protocol this leads them to have expectations about future observations agents can update their knowledge by matching their actual observations with the expected ones they eliminate states where they do not match in this paper we study how agents perceive protocols that are not commonly known and propose a semantics driven logical framework to reason about knowledge in such scenarios in particular we introduce the notion of epistemic expectation models and a propositional dynamic logic style epistemic logic for reasoning about knowledge via matching email protected expectations to their observations it is shown how epistemic expectation models can be obtained from epistemic protocols furthermore a characterization is presented of the effective equivalence of epistemic protocols we introduce a new logic that incorporates updates of protocols and that can model reasoning about knowledge and observations finally the framework is extended to incorporate fact changing actions and a worked out example is given

dynamics of phase singularities in two dimensional oscillating systems abstract we study the dynamics of vortices that arise in two dimensional nonequilibrium systems above a hopf bifurcation to uniform temporal oscillations evolution equations for the vortex positions and for a global phase field are derived and used to study vortex interactions we suggest that the interactions need not be purely attractive or repulsive bound vortex pairs can exist which either precess around fixed points in the plane or drift in directions perpendicular to the inter vortex axes

a symbolic approach to qualitative kinematics abstract an important problem for mechanism design and analysis is reasoning about the relationship between object shapes and their kinematic function such reasoning is difficult because of the unstructured influence of the shapes metric dimensions in this paper we show how a qualitative kinematic analysis can be based solely on symbolic reasoning and evaluation of predicates on metric dimensions this allows symbolic reasoning about kinematics without explicit numerical representations of object dimensions and automatic generation of operators relating kinematic goals to shape modifications which may achieve them

a logic framework for reasoning with movement based on fuzzy qualitative representation abstract we present a logic approach to reason with moving objects under fuzzy qualitative representation this way we can deal both with qualitative and quantitative information and consequently to obtain more accurate results the proposed logic system is introduced as an extension of propositional dynamic logic this choice on the one hand simplifies the theoretical study concerning soundness completeness and decidability on the other hand provides the possibility of constructing complex relations from simpler ones and the use of a language very close to programming languages

empirical bayes estimation for combinations of multivariate bioassays summary this article presents a new empirical bayes estimator ebe and a shrinkage estimator for determining the relative potency from several multivariate bioassays by incorporating prior information on the model parameters based on jeffreys rules the ebe can account for any extra variability among the bioassays and if this extra variability is 0 then the ebe reduces to the maximum likelihood estimator for combinations of multivariate bioassays the shrinkage estimator turns out to be a compromise of the prior information and the estimator from each multivariate bioassay with the weights depending on the prior variance

a growth curve model approach to multivariate quantal bioassay the typical quantal bioassay is used to estimate that concentration which will affect a given response in loop of the subjects of interest when p 50 we speak of ec50 for median effective concentration or lc50 for a lethal effect more explicitly such a controlled laboratory experiment usually involves subjecting nj experimental units to a concentration cj and recording the number zj of experimental units affected by this concentration level for an increasing sequence of concentrations cj j 1 2 d with different corresponding sets of nj subjects a sequence zj of the number of subjects responding is obtained when a lethal effect occurs the ratios zj nj pj say become mortality rates and the problem is to estimate the concentration lc50 which corresponds to p 50 various univariate methods can be used to solve this problem the most popular being probit analysis see for example finney 1971 or hubert 1984 if the responses are recorded after a time of t hours the parameter to be estimated is referred to as the t hour lc50 when the experiment is monitored over a sequence of time points the corresponding response variables become functions of concentration and time however the application of univariate probit analysis at each time point neglects the dependency in time and also the possible interaction of time and concentration on the response the analysis of indirect quantitative assays with correlated data has been described by box and hay 1953 their analysis assumes a repeated measures model that is the correlations between observations on the same experimental unit are assumed to be equal elashoff 1981 studied the effect of heterogeneity of variances and correlations on this analysis v0lund 1980 treated the case in which these correlations are arbitrary thereby extending the work of rao 1954 multivariate indirect quantal assays have been studied by kolakowski and bock 1981 and by kooijman 1981 kolakowski and bock 1981 assumed a latent structural model with independence among the responses over time kooijrman 1981 assumed that the mortality counts follow a multinomial distribution with the probability of death being a function of time and concentration such a model does not differentiate between sampling units and experimental units for example if concentrations of copper are administered to tanks of 20 fish the model requires the assumption that there is no error variation among tanks of fish some work on the inclusion of this extra variation in the model for experiments involving litters of subjects has been done by segreti and munson 1981

spatial reasoning in a fuzzy region connection calculus although the region connection calculus rcc offers an appealing framework for modelling topological relations its application in real world scenarios is hampered when spatial phenomena are affected by vagueness to cope with this we present a generalization of the rcc based on fuzzy set theory and discuss how reasoning tasks such as satisfiability and entailment checking can be cast into linear programming problems we furthermore reveal that reasoning in our fuzzy rcc is np complete thus preserving the computational complexity of reasoning in the rcc and we identify an important tractable subfragment moreover we show how reasoning tasks in our fuzzy rcc can also be reduced to reasoning tasks in the original rcc while this link with the rcc could be exploited in practical reasoning algorithms we mainly focus on the theoretical consequences in particular using this link we establish a close relationship with the egg yolk calculus and we demonstrate that satisfiable knowledge bases can be realized by fuzzy regions in any dimension

mccarthy variations in a modal key we take a fresh look at some major strands in john mccarthy s work from a logician s perspective first we re analyze circumscription in dynamic logics of belief change under hard and soft information next we re analyze the regression method in the situation calculus in terms of update axioms for dynamic epistemic temporal logics finally we draw some general methodological comparisons between logical ai and practices in modal logic pointing at some creative tensions

estimating prediction equations in repeated measures designs experimental designs with repeated measures allow response patterns over time or dose to be modelled and compared between different homogeneous groups issues in data analysis often focus on the pattern of variation of the repeated measures the appropriateness of a univariate or multivariate analysis and the shape of the response pattern an aspect of analysis that is often of equal importance is the development of a regression model for response once the pattern has been characterized analysis of variance or multivariate growth curve results often do not include easily interpretable regression equation estimates that can be used for prediction we present methods and tables that permit simple construction of such predictive equations for repeated measures designs when response is modelled as a polynomial over time with univariate or multivariate analyses

regression models with unknown singular covariance matrix in the analysis of the classical multivariate linear regression model it is assumed that the covariance matrix is nonsingular this assumption of nonsingularity limits the number of characteristics that may be included in the model in this paper we relax the condition of nonsingularity and consider the case when the covariance matrix may be singular maximum likelihood estimators and likelihood ratio tests for the general linear hypothesis are derived for the singular covariance matrix case these results are extended to the growth curve model with a singular covariance matrix we also indicate how to analyze data where several new aspects appear

a two step method for understanding and fitting growth curve models with data from a repeated measures design analysts often overlook growth curve analysis based on the potthoff roy model the reluctance to perform a growth analysis may result partially from unfamiliarity with the technique and partially from the lack of readily available computational programs to fit the models although growth curve analysis has traditionally appeared as a special technique in multivariate analysis one can fit the models with the use of two simple ideas transformation of variables and weighted least squares wls when presented in this manner growth models are a natural extension of univariate repeated measures models growth curve analyses share with univariate analyses the common objective to limit estimation to a parsimonious set of parameters that characterize the response profiles one can readily fit models with commonly available software the two step methodology also allows the fit of more general growth models that are appropriate when groups have different shape profiles two examples illustrate this approach to growth curve analysis

an expert fuzzy cognitive map for reactive navigation of mobile robots a control technique is described for reactive navigation of mobile robots the problems of large number of rules and inefficient definition of contributing factors e g robot wheel slippage are resolved causal inference mechanism of the fuzzy cognitive map fcm is hired for deriving the required control values from the fcm s motion concepts and their causal interactions the fcm based control is proven to be advantageous over rule based techniques the developed system is utilized to control a pioneer platform the results and comparisons with the related works are given using activmedia simulation and a developed fcm simulation tool an error estimation technique is used to measure the error between the actual and the simulation results

inferring additional knowledge from qtcn relations it is widely held that people tend to use qualitative rather than quantitative phrases when raising or answering questions about moving objects queries about whether an object is moving towards or away from another object or whether objects are getting closer to each other or further away from each other require qualitative responses this characteristic should be reflected in a calculus to be used to describe and reason about continuously moving objects in this paper we present a qualitative trajectory calculus of relations between two disjoint moving objects whose movement is constrained by a network the proposed calculus qtc n is formally introduced and illustrated particular attention is placed on how to infer additional knowledge from qtc n relations by means of composition tables and the transformation of qtc n relations into relations defined by the relative trajectory calculus on networks rtc n

analysis of linear combinations with extreme ratios of variance abstract if the covariance matrices 1 and 2 of two multivariate populations are not identical insight into the differences between 1 and 2 can often be gained by analyzing the linear combinations with extreme ratios of variances that is those defined by the eigenvectors associated with the extreme roots of 1 1 2 this article gives a descriptive method similar to variable selection procedures in regression for screening and simplifying these linear combinations a hypothesis of redundancy of variables is defined and a statistic for testing this hypothesis is derived the method is illustrated by an example

evolution of nonsoliton and quasi classical wavetrains in nonlinear schro dinger and korteweg de vries equations with dissipative perturbations abstract nonlinear schrodinger equations with attraction and with repulsion nse and nse and the korteweg de vries equation perturbed by small dissipative terms are considered near the linear instability threshold where nonlinear and spatially nonuniform dissipations dominate explicit solutions expressing the local amplitude and occupation numbers of a nonsoliton dispersive wavetrain in terms of arbitrary initial data are obtained at sufficiently large times in the logarithmic approximation for nse the particular case of the wavetrain near the soliton birth threshold is also considered the influence of the dissipation on the evolution of a quasi classical strongly nonlinear wavetrain is studied it is demonstrated that for nse the dissipation can be taken into account within the framework of the eikonal approximation while for the nse a perturbation theory based on the inverse scattering transform is relevant

on the improvement of combined fuzzy topological and directional relations information concept of combined extraction of topological and directional relations information developed by zahzah et al 1 by employing the allen s temporal relations in 1d spatial domain was improved by matsakis and nikitenko 2 this latter algorithm has high computational complexity due to its limitations of object approximation and segment fuzzification in this paper fuzzy allen relations are used to define the fuzzy topological and directional relations information between different objects some extended results of salamat and zahzah 3 are discussed polygonal object approximation allows us to use fuzzy operators and this approach reduces computational complexity of the method for computing the combined topological and directional relations to validate the method some experiments are tested giving satisfactory and promising results affine transformation are depicted these properties will be helpful for using the method in other areas of image analysis such as object tracking