Distributed Computing
The synthesis of digital machines with provable epistemic properties
Proceedings of the 1986 Conference on Theoretical aspects of reasoning about knowledge
On play by means of computing machines
Proceedings of the 1986 Conference on Theoretical aspects of reasoning about knowledge
Belief, awareness, and limited reasoning
Artificial Intelligence
A knowledge-based analysis of zero knowledge
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
The knowledge complexity of interactive proof systems
SIAM Journal on Computing
Knowledge and common knowledge in a distributed environment
Journal of the ACM (JACM)
Reasoning situated in time I: basic concepts
Journal of Experimental & Theoretical Artificial Intelligence
A guide to completeness and complexity for modal logics of knowledge and belief
Artificial Intelligence
Artificial Intelligence
Knowledge, probability, and adversaries
Journal of the ACM (JACM)
A method for obtaining digital signatures and public-key cryptosystems
Communications of the ACM
A Deduction Model of Belief
Distributed Processes and the Logic of Knowledge
Proceedings of the Conference on Logic of Programs
Proceedings of the 2nd Conference on Theoretical Aspects of Reasoning about Knowledge
Proceedings of the fourteenth annual ACM symposium on Principles of distributed computing
Simulative inference about nonmonotonic reasoners
TARK '98 Proceedings of the 7th conference on Theoretical aspects of rationality and knowledge
Probabilistic algorithmic knowledge
Proceedings of the 9th conference on Theoretical aspects of rationality and knowledge
A logical toolbox for knowledge approximation
TARK '01 Proceedings of the 8th conference on Theoretical aspects of rationality and knowledge
Local knowledge assertions in a changing world: extended abstract
TARK '96 Proceedings of the 6th conference on Theoretical aspects of rationality and knowledge
A complete and decidable security-specialised logic and its application to the TESLA protocol
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Dealing with logical omniscience
TARK '07 Proceedings of the 11th conference on Theoretical aspects of rationality and knowledge
Verifying time, memory and communication bounds in systems of reasoning agents
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Journal of Logic, Language and Information
Using deductive knowledge to improve cryptographic protocol verification
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
Dealing with logical omniscience: Expressiveness and pragmatics
Artificial Intelligence
Toward opportunistic collaboration in target pursuit problems
AIS'11 Proceedings of the Second international conference on Autonomous and intelligent systems
DALT'05 Proceedings of the Third international conference on Declarative Agent Languages and Technologies
Journal of Computer Security - CSF 2010
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The standard model of knowledge in multi-agent systems suffers from what has been called the logical omniscience problem: agents know all tautologies, and know all the logical consequences of their knowledge. For many types of analysis, this turns out not to be a problem. Knowledge is viewed as being ascribed by the system designer to the agents; agents are not assumed to compute their knowledge in any way, nor is it assumed that they can necessarily answer questions based on their knowledge. Nevertheless, in many applications that we are interested in, agents need to act on their knowledge. In such applications, an externally ascribed notion of knowledge is insufficient: clearly an agent can base his actions only on what he explicitly knows. Furthermore, an agent that has to act on his knowledge has to be able to compute this knowledge; we do need to take into account the algorithms available to the agent, as well as the "effort" required to compute knowledge. In this paper, we show how the standard model can be modified in a natural way to take the computational aspects of knowledge into account.