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JOSEPH Y. HALPERN AND YORAM MOSES TAKEN BY SURPRISE: THE PARADOX OF THE SURPRISE TEST REVISITED
"... A teacher announced to his pupils that on exactly one of the days of the following school week (Monday through Friday) he would give them a test. But it would be a surprise test; on the evening before the test they would not know that the test would take place the next day. One of the brighter stude ..."
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A teacher announced to his pupils that on exactly one of the days of the following school week (Monday through Friday) he would give them a test. But it would be a surprise test; on the evening before the test they would not know that the test would take place the next day. One of the brighter students in the class then argued that the teacher could never give them the test. "It can't be Friday, " she said, "since in that case we'll expect it on Thurday evening. But then it can't be Thursday, since having already eliminated Friday we'll know Wednesday evening that it has to be Thursday. And by similar reasoning we can also eliminate Wednesday, Tuesday, and Monday. So there can't be a test!" The students were somewhat baffled by the situation. The teacher was wellknown to be truthful, so if he said there would be a test, then it was safe to assume that there would be one. On the other hand, he also said that the test would be a surprise. But it seemed that whenever he gave the test, it wouldn't be a surprise. Well, the teacher gave the test on Tuesday, and, sure enough, the students were surprised. 1.
Logic in Computer Science: Modelling and Reasoning about Systems
, 1999
"... ion. ACM Transactions on Programming Languages and Systems, 16(5):15121542, September 1994. Bibliography 401 [Che80] B. F. Chellas. Modal Logic  an Introduction. Cambridge University Press, 1980. [Dam96] D. R. Dams. Abstract Interpretation and Partition Refinement for Model Checking. PhD thesi ..."
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Cited by 345 (11 self)
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of Programming Languages. ACM Press, January 1996. [EN94] R. Elmasri and S. B. Navathe. Fundamentals of Database Systems. Benjamin/Cummings, 1994. [FHMV95] Ronald Fagin, Joseph Y. Halpern, Yoram Moses, and Moshe Y. Vardi. Reasoning about Knowledge. MIT Press, Cambridge, 1995. [Fit93] M. Fitting. Basic modal
Knowledge and Common Knowledge in a Distributed Environment
 Journal of the ACM
, 1984
"... : Reasoning about knowledge seems to play a fundamental role in distributed systems. Indeed, such reasoning is a central part of the informal intuitive arguments used in the design of distributed protocols. Communication in a distributed system can be viewed as the act of transforming the system&apo ..."
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Cited by 577 (55 self)
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: Reasoning about knowledge seems to play a fundamental role in distributed systems. Indeed, such reasoning is a central part of the informal intuitive arguments used in the design of distributed protocols. Communication in a distributed system can be viewed as the act of transforming the system's state of knowledge. This paper presents a general framework for formalizing and reasoning about knowledge in distributed systems. We argue that states of knowledge of groups of processors are useful concepts for the design and analysis of distributed protocols. In particular, distributed knowledge corresponds to knowledge that is "distributed" among the members of the group, while common knowledge corresponds to a fact being "publicly known". The relationship between common knowledge and a variety of desirable actions in a distributed system is illustrated. Furthermore, it is shown that, formally speaking, in practical systems common knowledge cannot be attained. A number of weaker variants...
Fundamental challenges in mobile computing
 In ACM Symposium on Principles of Distributed Computing
, 1996
"... This paper is an answer to the question: "What is unique and conceptually different about mobile computing? " The paper begins by describing a set of constraints intrinsic to mobile computing, and examining the impact of these constraints on the design of distributed systems. Next, it summ ..."
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Cited by 259 (18 self)
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This paper is an answer to the question: "What is unique and conceptually different about mobile computing? " The paper begins by describing a set of constraints intrinsic to mobile computing, and examining the impact of these constraints on the design of distributed systems. Next, it summarizes the key results of the Coda and Odyssey systems. Finally, it describes the research opportunities in five important topics relevant to mobile computing: caching metrics, semantic callbacks and validators, resource revocation, analysis of adaptation, and global estimation from local observations. 1.2. The Need for Adaptation Mobility exacerbates the tension between autonomy and interdependence that is characteristic of all distributed systems. The relative resource poverty of mobile elements as well as their lower trust and robustness argues for reliance on static servers. But the need to cope with unreliable and lowperformance networks, as well as the need to be sensitive to power consumption argues for selfreliance. 1.
Greedy strikes back: Improved facility location algorithms
 Journal of Algorithms
, 1999
"... A fundamental facility location problem is to choose the location of facilities, such as industrial plants and warehouses, to minimize the cost of satisfying the demand for some commodity. There are associated costs for locating the facilities, as well as transportation costs for distributing the co ..."
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Cited by 221 (11 self)
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A fundamental facility location problem is to choose the location of facilities, such as industrial plants and warehouses, to minimize the cost of satisfying the demand for some commodity. There are associated costs for locating the facilities, as well as transportation costs for distributing the commodities. We assume that the transportation costs form a metric. This problem is commonly referred to as the uncapacitated facility location (UFL) problem. Applications to bank account location and clustering, as well as many related pieces of work, are discussed by Cornuejols, Nemhauser and Wolsey [2]. Recently, the first constant factor approximation algorithm for this problem was obtained by Shmoys, Tardos and Aardal [16]. We show that a simple greedy heuristic combined with the algorithm by Shmoys, Tardos and Aardal, can be used to obtain an approximation guarantee of 2.408. We discuss a few variants of the problem, demonstrating better approximation factors for restricted versions of the problem. We also show that the problem is Max SNPhard. However, the inapproximability constants derived from the Max SNP hardness are very close to one. By relating this problem to Set Cover, we prove a lower bound of 1.463 on the best possible approximation ratio assuming NP / ∈ DT IME[n O(log log n)]. 1
Acknowledgments
, 2006
"... I would like to thank my supervisors, Dr. Ziv BarYossef and Dr. Idit Keidar, for their patience, for believing in me, and for bringing me down to earth when needed. I could not have asked for better supervisors, and I truly feel lucky to have had them both. I would also like to thank Prof. Israel C ..."
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Cidon, Prof. Yoram Moses, and Dr. Avigdor Gal for their insightful and helpful input. Finally, I would like to thank Tal Cohen and the forum site team, and Greg Pendler and the ee.technion.ac.il admins for providing us with access to web logs and for technical assistance. The generous financial help
Reasoning about Knowledge and Probability
 Journal of the ACM
, 1994
"... : We provide a model for reasoning about knowledge and probability together. We allow explicit mention of probabilities in formulas, so that our language has formulas that essentially say "according to agent i, formula ' holds with probability at least b." The language is powerful en ..."
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Cited by 195 (20 self)
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: We provide a model for reasoning about knowledge and probability together. We allow explicit mention of probabilities in formulas, so that our language has formulas that essentially say "according to agent i, formula ' holds with probability at least b." The language is powerful enough to allow reasoning about higherorder probabilities, as well as allowing explicit comparisons of the probabilities an agent places on distinct events. We present a general framework for interpreting such formulas, and consider various properties that might hold of the interrelationship between agents' probability assignments at different states. We provide a complete axiomatization for reasoning about knowledge and probability, prove a small model property, and obtain decision procedures. We then consider the effects of adding common knowledge and a probabilistic variant of common knowledge to the language. A preliminary version of this paper appeared in the Proceedings of the Second Conference on T...
THE GENEROUS FINANCIAL HELP OF THE TECHNION IS GRATEFULLY ACKNOWLEDGED. Acknowledgments
"... I would like to thank the many people who made this work possible and made the experience truly remarkable. I am deeply indebted to my adviser, Prof. Idit Keidar, for her continuous guidance and unwavering confidence in where we were going. Working and thinking with you has been humbling, and I than ..."
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thank you for always being available and keen to help when I needed it. I would like to thank Prof. Yoram Moses, for his friendship and advice over the years. I thank my fellow students at the Technion, who struggled and succeeded with me, encouraged and motivated me. Thank you Ayelet, Kirill and Daniel
A Propositional Modal Logic of Time Intervals
 Journal of the ACM
, 1996
"... : In certain areas of artificial intelligence there is need to represent continuous change and to make statements that are interpreted with respect to time intervals rather than time points. To this end we develop a modal temporal logic based on time intervals, a logic which can be viewed as a gener ..."
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Cited by 162 (2 self)
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: In certain areas of artificial intelligence there is need to represent continuous change and to make statements that are interpreted with respect to time intervals rather than time points. To this end we develop a modal temporal logic based on time intervals, a logic which can be viewed as a generalization of pointbased modal temporal logic. We discuss related logics, give an intuitive presentation of the new logic, and define its formal syntax and semantics. We make no assumption about the underlying nature of time, allowing it to be discrete (such as the natural numbers) or continuous (such as the rationals or the reals), linear or branching, complete (such as the reals) or not (such as the rationals). We show, however, that there are formulas in the logic that allow us to distinguish all these situations. We also give a translation of our logic into firstorder logic, which allows us to apply some results on firstorder logic to our modal one. Finally, we consider the difficulty o...
Model Checking vs. Theorem Proving: A Manifesto
, 1991
"... We argue that rather than representing an agent's knowledge as a collection of formulas, and then doing theorem proving to see if a given formula follows from an agent's knowledge base, it may be more useful to represent this knowledge by a semantic model, and then do model checking to se ..."
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Cited by 136 (6 self)
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We argue that rather than representing an agent's knowledge as a collection of formulas, and then doing theorem proving to see if a given formula follows from an agent's knowledge base, it may be more useful to represent this knowledge by a semantic model, and then do model checking to see if the given formula is true in that model. We discuss how to construct a model that represents an agent's knowledge in a number of different contexts, and then consider how to approach the modelchecking problem.
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