A knowledge-based analysis of zero knowledge
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
Concurrent common knowledge: a new definition of agreement for asynchronous systems
PODC '88 Proceedings of the seventh annual ACM Symposium on Principles of distributed computing
The knowledge complexity of interactive proof systems
SIAM Journal on Computing
The complexity of reasoning about knowledge and time. I. lower bounds
Journal of Computer and System Sciences - 18th Annual ACM Symposium on Theory of Computing (STOC), May 28-30, 1986
Knowledge and common knowledge in a distributed environment
Journal of the ACM (JACM)
A logic for reasoning about probabilities
Information and Computation - Selections from 1988 IEEE symposium on logic in computer science
Uncertainty, belief, and probability
Computational Intelligence
A guide to completeness and complexity for modal logics of knowledge and belief
Artificial Intelligence
Reasoning about Knowledge and Probability
Proceedings of the 2nd Conference on Theoretical Aspects of Reasoning about Knowledge
Notes on Data Base Operating Systems
Operating Systems, An Advanced Course
Reasoning about knowledge and probability
Journal of the ACM (JACM)
Approximate Common Knowledge and Co-ordination: Recent Lessons from Game Theory
Journal of Logic, Language and Information
How Much Privacy? - A System to Safe Guard Personal Privacy while Releasing Databases
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
CSFW '02 Proceedings of the 15th IEEE workshop on Computer Security Foundations
Probabilistic Dynamic Epistemic Logic
Journal of Logic, Language and Information
TARK '94 Proceedings of the 5th conference on Theoretical aspects of reasoning about knowledge
TARK '96 Proceedings of the 6th conference on Theoretical aspects of rationality and knowledge
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Updating beliefs with incomplete observations
Artificial Intelligence
A logical approach to multilevel security of probabilistic systems
Distributed Computing
Anonymity and information hiding in multiagent systems
Journal of Computer Security
ACM Transactions on Information and System Security (TISSEC)
Towards an Epistemic Logic for Uncertain Agents
CEEMAS '07 Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V
Reasoning about actions with sensing under qualitative and probabilistic uncertainty
ACM Transactions on Computational Logic (TOCL)
An epistemic characterization of zero knowledge
Proceedings of the 12th Conference on Theoretical Aspects of Rationality and Knowledge
Journal of Artificial Intelligence Research
A logic for reasoning about evidence
Journal of Artificial Intelligence Research
Reasoning about noisy sensors in the situation calculus
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Quantifying information flow with beliefs
Journal of Computer Security - 18th IEEE Computer Security Foundations Symposium (CSF 18)
A complete probabilistic belief logic
CLIMA VII'06 Proceedings of the 7th international conference on Computational logic in multi-agent systems
Verification of epistemic properties in probabilistic multi-agent systems
MATES'09 Proceedings of the 7th German conference on Multiagent system technologies
Using multi-agent systems to represent uncertainty
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Symbolic model checking of probabilistic knowledge
Proceedings of the 13th Conference on Theoretical Aspects of Rationality and Knowledge
Detecting and repairing anomalous evolutions in noisy environments
Annals of Mathematics and Artificial Intelligence
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Representing causal information about a probabilistic process
JELIA'06 Proceedings of the 10th European conference on Logics in Artificial Intelligence
Updating with incomplete observations
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Probabilistic reasoning about actions in nonmonotonic causal theories
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
A logic for reasoning about evidence
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Using probabilistic kleene algebra for protocol verification
RelMiCS'06/AKA'06 Proceedings of the 9th international conference on Relational Methods in Computer Science, and 4th international conference on Applications of Kleene Algebra
Common knowledge and state-dependent equilibria
SAGT'12 Proceedings of the 5th international conference on Algorithmic Game Theory
A logic of probabilistic knowledge and strategy
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Reasoning about continuous uncertainty in the situation calculus
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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What should it mean for an agent to know or believe an assertion is true with probability 9.99? Different papers [2, 6, 15] give different answers, choosing to use quite different probability spaces when computing the probability that an agent assigns to an event. We show that each choice can be understood in terms of a betting game. This betting game itself can be understood in terms of three types of adversaries influencing three different aspects of the game. The first selects the outcome of all nondeterministic choices in the system; the second represents the knowledge of the agent's opponent in the betting game (this is the key place the papers mentioned above differ); and the third is needed in asynchronous systems to choose the time the bet is placed. We illustrate the need for considering all three types of adversaries with a number of examples. Given a class of adversaries, we show how to assign probability spaces to agents in a way most appropriate for that class, where “most appropriate” is made precise in terms of this betting game. We conclude by showing how different assignments of probability spaces (corresponding to different opponents) yield different levels of guarantees in probabilistic coordinated attack.