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29
Bisimulation through probabilistic testing
 in “Conference Record of the 16th ACM Symposium on Principles of Programming Languages (POPL
, 1989
"... We propose a language for testing concurrent processes and examine its strength in terms of the processes that are distinguished by a test. By using probabilistic transition systems as the underlying semantic model, we show how a testing algorithm can distinguish, with a probability arbitrarily clos ..."
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Cited by 405 (5 self)
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We propose a language for testing concurrent processes and examine its strength in terms of the processes that are distinguished by a test. By using probabilistic transition systems as the underlying semantic model, we show how a testing algorithm can distinguish, with a probability arbitrarily close to one, between processes that are not bisimulation equivalent. We also show a similar result (in a slightly stronger form) for a new process relation called $bisimulationwhich lies strictly between that of simulation and bisimulation. Finally, the ultimately strength of the testing language is shown to identify a new process relation called probabilistic bisimulationwhich is strictly stronger than bisimulation. li? 1991 Academic Press. Inc. 1.
ALLIANCE: An Architecture for Fault Tolerant MultiRobot Cooperation
 IEEE Transactions on Robotics and Automation
, 1998
"... ALLIANCE is a software architecture that fa cilitates the fault tolerant cooperative control of teams of heterogeneous mobile robots performing missions composed of loosely coupled subtasks that may have ordering dependencies. ALLIANCE allows teams of robots, each of which possesses a variety of hi ..."
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Cited by 392 (13 self)
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ALLIANCE is a software architecture that fa cilitates the fault tolerant cooperative control of teams of heterogeneous mobile robots performing missions composed of loosely coupled subtasks that may have ordering dependencies. ALLIANCE allows teams of robots, each of which possesses a variety of highlevel functions that it can perform during a mission, to individually select appropriate actions throughout the mission based on the requirements of the mission, the activities of other robots, the current environmental conditions, and the robot's own internal states. ALLIANCE is a fully distributed, behaviorbased architecture that incorporates the use of mathematicallymodeled motivations (such as impatience and acquiescence) within each robot to achieve adaptive action selection. Since cooperative robotic teams usually work in dynamic and unpredictable environments, this software architecture allows the robot team members to respond robustly, reliably, flexibly, and coherently to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. The feasibility of this architecture is demonstrated in an implementation on a team of mobile robots performing a laboratory version of hazardous waste cleanup.
Learning Probabilistic Networks
 THE KNOWLEDGE ENGINEERING REVIEW
, 1998
"... A probabilistic network is a graphical model that encodes probabilistic relationships between variables of interest. Such a model records qualitative influences between variables in addition to the numerical parameters of the probability distribution. As such it provides an ideal form for combini ..."
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Cited by 37 (1 self)
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A probabilistic network is a graphical model that encodes probabilistic relationships between variables of interest. Such a model records qualitative influences between variables in addition to the numerical parameters of the probability distribution. As such it provides an ideal form for combining prior knowledge, which might be limited solely to experience of the influences between some of the variables of interest, and data. In this paper, we first show how data can be used to revise initial estimates of the parameters of a model. We then progress to showing how the structure of the model can be revised as data is obtained. Techniques for learning with incomplete data are also covered.
On Computing the Homology Type of a Triangulation
, 1994
"... :We analyze an algorithm for computing the homology type of a triangulation. By triangulation we mean a finite simplicial complex; its homology type is given by its homology groups (with integer coefficients). The algorithm could be used in computeraided design to tell whether two finiteelement me ..."
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Cited by 22 (0 self)
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:We analyze an algorithm for computing the homology type of a triangulation. By triangulation we mean a finite simplicial complex; its homology type is given by its homology groups (with integer coefficients). The algorithm could be used in computeraided design to tell whether two finiteelement meshes or B'ezierspline surfaces are of the same "topological type," and whether they can be embedded in R³. Homology computation is a purely combinatorial problem of considerable intrinsic interest. While the worstcase bounds we obtain for this algorithm are poor, we argue that many triangulations (in general) and virtually all triangulations in design are very "sparse," in a sense we make precise. We formalize this sparseness measure, and perform a probabilistic analysis of the sparse case to show that the expected running time of the algorithm is roughly quadratic in the geometric complexity (number of simplices) and linear in the dimension.
A theory of hyperfinite processes: the complete removal of individual uncertainty via exact LLN
, 1998
"... The aim of this paper is to provide a viable measuretheoretic framework for the study of random phenomena involving a large number of economic entities. The work is based on the fact that processes which are measurable with respect to hyperfinite Loeb product spaces capture the limiting behaviors ..."
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Cited by 20 (10 self)
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The aim of this paper is to provide a viable measuretheoretic framework for the study of random phenomena involving a large number of economic entities. The work is based on the fact that processes which are measurable with respect to hyperfinite Loeb product spaces capture the limiting behaviors of triangular arrays of random variables and thus constitute the `right' class for general stochastic modeling. The primary concern of the paper is to characterize those hyperfinite processes satisfying the exact law of large numbers by using the basic notions of conditional expectation, orthogonality, uncorrelatedness and independence together with some unifying multiplicative properties of random variables. The general structure of the processes is also analyzed via a biorthogonal expansion of the KarhunenLoeve type and via the representation in terms of the simpler hyperfinite Loeb counting spaces. A universality property for atomless Loeb product spaces is formulated to show the abun...
On The Effect of Populations in Evolutionary Multiobjective Optimization
"... Abstract. Multiobjective evolutionary algorithms (MOEAs) have become increasingly popular as multiobjective problem solving techniques. Most studies of MOEAs are empirical. Only recently, a few theoretical results have appeared. It is acknowledged that more theoretical research is needed. An impor ..."
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Cited by 18 (3 self)
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Abstract. Multiobjective evolutionary algorithms (MOEAs) have become increasingly popular as multiobjective problem solving techniques. Most studies of MOEAs are empirical. Only recently, a few theoretical results have appeared. It is acknowledged that more theoretical research is needed. An important open problem is to understand the role of populations in MOEAs. We present a simple biobjective problem which emphasizes when populations are needed. Rigorous runtime analysis point out an exponential runtime gap between a populationbased algorithm (SEMO) and several single individualbased algorithms on this problem. This means that among the algorithms considered, only the populationbased MOEA is successful and all other algorithms fail. 1
Unifying Control In A Layered Agent Architecture
 IN IJCAI95, AGENT THEORY, ARCHITECTURE AND LANGUAGE WORKSHOP 95
, 1995
"... In this paper, we set up a unifying perspective of the individual control layers of the architecture InteRRaP for autonomous interacting agents. InteRRaP is a pragmatic approach to designing complex dynamic agent societies, e.g. for robotics [Muller & Pischel 94a] and cooperative scheduling appl ..."
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Cited by 16 (1 self)
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In this paper, we set up a unifying perspective of the individual control layers of the architecture InteRRaP for autonomous interacting agents. InteRRaP is a pragmatic approach to designing complex dynamic agent societies, e.g. for robotics [Muller & Pischel 94a] and cooperative scheduling applications [Fischer et al. 94]. It is based on three general functions describing how the actions an agent commits to are derived from its perception and from its mental model: belief revision and abstraction, situation recognition and goal activation, and planning and scheduling. It is argued that each InteRRaP control layer  the behaviourbased layer, the local planning layer, and the cooperative planning layer  can be described by a combination of different instantiations of these control functions. The basic structure of a control layer is defined. The individual functions and their implementation in the different layers are outlined. We demonstrate various options for the d...
Theory and Practice of Acoustic Confusability
, 2000
"... In this paper we define two alternatives to the familiar perplexity statistic (hereafter lexical perplexity), which is widely applied both as a measureofgoodness and as an objective function for training language models. These alternatives, respectively acoustic perplexity and the synthetic acoust ..."
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Cited by 15 (1 self)
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In this paper we define two alternatives to the familiar perplexity statistic (hereafter lexical perplexity), which is widely applied both as a measureofgoodness and as an objective function for training language models. These alternatives, respectively acoustic perplexity and the synthetic acoustic word error rate, fuse information from both the language model and the acoustic model. We show how to compute these statistics by effectively synthesizing a large acoustic corpus, demonstrate their superiority to lexical perplexity as predictors of language model performance, and investigate their use as objective functions for training language models. We present results from a simple speech recognition experiment that demonstrate a small reduction in word error rate.
Stabilizing PhaseClocks
 Information Processing Letters
, 1993
"... This note considers the problem of synchronizing a network of digital clocks: the clocks all run at the same rate, however, an initial state of the network may place the clocks in arbitrary phases. The problem is to devise a protocol to advance or retard clocks so that eventually all clocks are in p ..."
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Cited by 12 (1 self)
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This note considers the problem of synchronizing a network of digital clocks: the clocks all run at the same rate, however, an initial state of the network may place the clocks in arbitrary phases. The problem is to devise a protocol to advance or retard clocks so that eventually all clocks are in phase. The solutions presented in this note are protocols in which all processes are identical and use a constant amount of space per process. One solution is a deterministic protocol for a tree network; another solution is a probabilistic protocol for a network of arbitrary topology. Keywords: Distributed computing, Selfstabilization, Clock synchronization, Uniform processes 1 Introduction One of the primary themes of program design in a distributed system is synchronization. Within this broad topic, we consider here the problem of coordinating phases of a nonterminating protocol. In particular, this protocol's execution consists of the repetition of a sequence of phases, P 0 P 1 . . . P ...