Second-order uncertainty, also known as model uncertainty and Knightian uncertainty, arises when decision-makers can (partly) model the parameters of their decision problems. It is widely believed that subjective probability, and more generally Bayesian theory, are ill-suited to represent a number of interesting second-order uncertainty fea-tures, especially "ignorance" and "ambiguity". This failure is sometimes taken as an argument for the rejection of the whole Bayesian approach, triggering a Bayes vs anti-Bayes debate which is in many ways analogous to what the classical vs non-classical debate used to be in logic. This pa-per attempts to unfold this analogy and suggests that the development of non-standard logics offers very useful lessons on the contextualisa-tion of justified norms of rationality. By putting those lessons to work I will flesh out an epistemological framework suitable for extending the expressive power of standard Bayesian norms of rationality to second-order uncertainty in a way which is both formally and foundationally conservative.
A textbook giving a coordinated account of various approaches to nonmonotonic reasoning, dsigned for graduate students of philosophy, computer science, and mathematics, with exercises and solutions.
The volume analyses and develops David Makinson’s efforts to make classical logic useful outside its most obvious application areas. The book contains chapters that analyse, appraise, or reshape Makinson’s work and chapters that develop themes emerging from his contributions. These are grouped into major areas to which Makinsons has made highly influential contributions and the volume in its entirety is divided into four sections, each devoted to a particular area of logic: belief change, uncertain reasoning, normative systems, and the resources of classical logic.
Among the contributions included in the volume, one chapter focuses on the “inferential preferential method”, i.e. the combined use of classical logic and mechanisms of preference and choice and provides examples from Makinson’s work in non-monotonic and defeasible reasoning and belief revision. One chapter offers a short autobiography by Makinson which details his discovery of modern logic, his travels across continents and reveals his intellectual encounters and inspirations. The chapter also contains an unsually explicit statement on his views on the (limited but important) role of logic in philosophy.
The paper provides a mathematical model of an agent's belief in an event by identifying it with his ability to imagine the event within the context of his previous experience. This approach leads to belief having properties different from those normally ascribed to it.
The notion of uncertainty in robotics has to date largely involved the uncertainty, or variability, in the information the robot was receiving from its sensors, information about an outside world which itself is known, certain, unambiguous. For example, the uncertainty the robot may experience in answering the question Is that object a cube?. With the emergence of autonomous, really useful robots, however, robots also need to address the problems of uncertainty which will require the robot to reason about the real world, It is a cube, but is there something hiding behind it?. In this paper we reconsider a mode of intelligent uncertain reasoning, based on forming beliefs by constructing models, which would seem to be a natural, and simple, step in the evolution of certain of today's robots and may provide the robot with a means of reasoning about the uncertainties of the world it encounters.
Epistemic Utility Arguments for Probabilism. Stanford Encyclopedia of Philosophy
Jan 2015
R Pettigrew
Pettigrew, R. 2015 Epistemic Utility Arguments for Probabilism. Stanford Encyclopedia of Philosophy E.N. Zalta (ed.), URL http://plato.
stanford.edu/entries/epistemic-utility/.
A Textbook of Belief Dynamics Dordrecht: Springer. 1 Dipartimento di Filosofia, Università degli Studi di Milano, via Festa del Perdono 7
Jan 1999
S O Hansson
Hansson, S. O. 1999. A Textbook of Belief Dynamics Dordrecht: Springer.
1 Dipartimento di Filosofia, Università degli Studi di Milano, via Festa
del Perdono 7, 20122, Milano, Italy.
Email hykel.hosni@unimi.it URL:
http://www.filosofia.unimi.it/ hosni/