The paper deals with credible and relevantinformation flow in dialogs: How useful is it for areceiver to get some information, how useful is it fora sender to give this information, and how much credibleinformation can we expect to flow between sender andreceiver? What is the relation between semantics andpragmatics? These Gricean questions will be addressedfrom a decision and game-theoretical point of view.

The paper deals with credible and relevantinformation flow in dialogs: How useful is it for areceiver to get some information, how useful is it fora sender to give this information, and how much credibleinformation can we expect to flow between sender andreceiver? What is the relation between semantics andpragmatics? These Gricean questions will be addressedfrom a decision and game-theoretical point of view.

Economists have always recognised that human endeavours are constrained by our limited and uncertain knowledge, but only recently has an accepted theory of uncertainty and information evolved. This theory has turned out to have surprisingly practical applications: for example in analysing stock market returns, in evaluating accident prevention measures, and in assessing patent and copyright laws. This book presents these intellectual advances in readable form for the first time. It unifies many important but partial results into a satisfying single picture, (...) making it clear how the economics of uncertainty and information generalises and extends standard economic analysis. Part One of the volume covers the economics of uncertainty: how each person adapts to a given fixed state of knowledge by making an optimal choice among the immediate 'terminal' actions available. These choices in turn determine the overall market equilibrium reflecting the social distribution of risk bearing. In Part Two, covering the economics of information, the state of knowledge is no longer held fixed. Instead, individuals can to a greater or lesser extent overcome their ignorance by 'informational' actions. The text also addresses at appropriate points many specific topics such as insurance, the Capital Asset Pricing model, auctions, deterrence of entry, and research and invention. (shrink)

In this paper I combine the dynamic epistemic logic ofGerbrandy (1999) with the probabilistic logic of Fagin and Halpern (1994). The resultis a new probabilistic dynamic epistemic logic, a logic for reasoning aboutprobability, information, and information change that takes higher orderinformation into account. Probabilistic epistemic models are defined, and away to build them for applications is given. Semantics and a proof systemis presented and a number of examples are discussed, including the MontyHall Dilemma.

Reasoning About Knowledge is the first book to provide a general discussion of approaches to reasoning about knowledge and its applications to distributed ...

We discuss games of both perfect and imperfect information at two levels of structural detail: players’ local actions, and their global powers for determining outcomes of the game. We propose matching logical languages for both. In particular, at the ‘action level’, imperfect information games naturally model a combined ‘dynamic-epistemic language’ – and we find correspondences between special axioms and particular modes of playing games with their information dynamics. At the ‘outcome level’, we present suitable notions of game equivalence, plus some (...) simple representation results. (shrink)

Logic is not just about single-agent notions like reasoning, or zero-agent notions like truth, but also about communication between two or more people. What we tell and ask each other can be just as 'logical' as what we infer in Olympic solitude. We show how such interactive phenomena can be studied systematically by merging epistemic and dynamic logic.