REASONING ABOUT KNOWLEDGE AND PROBABILITY: Preliminary Report
نویسندگان
چکیده
A b s t r a c t : We provide a model for reasoning about knowledge anti probability together. We a.llow explicit mention of probabilities in formulas, so that our language has formulas tha.t essentia.lly say "a.ccording to agent i, formula. (p holds with probability a.t least o~." The language is powerfid enough to allow reasoning a~bout higher-order 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, a.nd consider various properties that might hold of the interrelationship between agents' subjective probability spaces at different states. We provide a. complete a.xiomatiza.tion for rea.soning about knowledge a.nd probability, prove a. small model property, and obtain decision procedures. We then consider the effects of adding common knowledge and a. probabilistic va.ria.nt of common knowledge to the language.
منابع مشابه
Epistemology of Information Flow in the Multilevel Security of Probabilistic Systems
We set out a modal logic for reasoning about multilevel security of probabilistic systems. This logic includes modalities for time, probability, knowledge, and permitted-knowledge. Making use of the Halpern-Tuttle framework for reasoning about knowledge and probability, we give a semantics for our logic and prove that it is sound. We give two syntactic de nitions of perfect multilevel security ...
متن کاملReasoning Constructively about Probability and Programming with Chance
Probability and statistics are the deductive and inductive theories, respectively, of chance and uncertainty. However, they typically do not have a role in traditional logic and theorem proving. This is unfortunate, because chance is an important concept in computer science. The interaction between computer science and uncertainty typically takes three forms. First, algorithms may make random d...
متن کاملReasoning with Models of Probabilistic Knowledge over Probabilistic Knowledge
In multi-agent systems, the knowledge of agents about other agents’ knowledge often plays a pivotal role in their decisions. In many applications, this knowledge involves uncertainty. This uncertainty may be about the state of the world or about the other agents’ knowledge. In this thesis, we answer the question of how to model this probabilistic knowledge and reason about it efficiently. Modal...
متن کاملLogical Probability Preferences
We present a unified logical framework for representing and reasoning about both probability quantitative and qualitative preferences in probability answer set programming [Saad and Pontelli, 2006; Saad, 2006; Saad, 2007a], called probability answer set optimization programs. The proposed framework is vital to allow defining probability quantitative preferences over the possible outcomes of qua...
متن کاملThe new psychology of reasoning: A mental probability logical perspective
Mental probability logic (MPL) has been proposed as a competence theory of human inference. MPL interprets indicative conditionals as conditional events. While recent probabilistic approaches assume an uncertain relation between the premises and the conclusion, the consequence relation remains deductive in MPL. The underlying rationality framework of MPL is coherence based probability logic. I ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1988