
Zeroprobability and coherent betting: a logical point of viewIn S. S. Destercke & T. Denoeux (eds.), Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2015), Springer Lnai 9161. pp. 206217. 2015.

3Zeroprobability and coherent betting: a logical point of viewIn T. Flaminio, L. Godo & Hykel Hosni (eds.), Symbolic and Quantiative Approaches to Resoning With Uncertainty. Lecture notes in artificial intelligence. pp. 206217. 2013.

61This paper initiates an investigation of conditional measures as simple measures on conditional events. As a first step towards this end we investigate the construction of conditional algebras which allow us to distinguish between the logical properties of conditional events and those of the conditional measures which we can be attached to them. This distinction, we argue, helps us clarifying both concepts

244Betting methods, of which de Finetti's Dutch Book is by far the most wellknown, are uncertainty modelling devices which accomplish a twofold aim. Whilst providing an interpretation of the relevant measure of uncertainty, they also provide a formal definition of coherence. The main purpose of this paper is to put forward a betting method for belief functions on MValgebras of manyvalued events which allows us to isolate the corresponding coherence criterion, which we term coherence in the aggre…Read more

19A logicogeometric comparison of coherence for nonadditive uncertainty measuresAnnals of Pure and Applied Logic 175 (9): 103342. 2024.

Probability and Degrees of TruthIn Igor Sedlár (ed.), The Logica Yearbook 2021, College Publications. pp. 118. 2022.

Logical perspectives on the foundations of probabilityOpen Mathematics 21 (1). 2023.We illustrate how a variety of logical methods and techniques provide useful, though currently underappreciated, tools in the foundations and applications of reasoning under uncertainty. The field is vast spanning logic, artificial intelligence, statistics, and decision theory. Rather than (hopelessly) attempting a comprehensive survey, we focus on a handful of telling examples. While most of our attention will be devoted to frameworks in which uncertainty is quantified probabilistically, we wil…Read more

79On the logical structure of de Finetti's notion of eventJournal of Applied Logic 12 (3): 279301. 2014.This paper sheds new light on the subtle relation between probability and logic by (i) providing a logical development of Bruno de Finetti's conception of events and (ii) suggesting that the subjective nature of de Finetti's interpretation of probability emerges in a clearer form against such a logical background. By making explicit the epistemic structure which underlies what we call Choicebased probability we show that whilst all rational degrees of belief must be probabilities, the converse …Read more

134You better play 7: mutual versus common knowledge of advice in a weaklink experimentSynthese 190 (8): 13511381. 2013.This paper presents the results of an experiment on mutual versus common knowledge of advice in a twoplayer weaklink game with random matching. Our experimental subjects play in pairs for thirteen rounds. After a brief learning phase common to all treatments, we vary the knowledge levels associated with external advice given in the form of a suggestion to pick the strategy supporting the payoffdominant equilibrium. Our results are somewhat surprising and can be summarized as follows: in all o…Read more

12Analogies and Theories: Formal Models of Reasoning, Itzhak Gilboa, Larry Samuelson and David Schmeidler. Oxford University Press, 2015Economics and Philosophy 32 (2): 373381. 2016.

10Zeroprobability and coherent betting: a logical point of viewIn T. Flaminio, L. Godo & Hykel Hosni (eds.), Symbolic and Quantiative Approaches to Resoning With Uncertainty. Lecture notes in artificial intelligence. pp. 206217. 2013.

28Boolean algebras of conditionals, probability and logicArtificial Intelligence 286 (C): 103347. 2020.

16Zeroprobability and coherent betting: a logical point of viewIn T. Flaminio, L. Godo & Hykel Hosni (eds.), Symbolic and Quantiative Approaches to Resoning With Uncertainty. Lecture notes in artificial intelligence. pp. 206217. 2013.

69Forecasting in Light of Big DataPhilosophy and Technology 31 (4): 557569. 2018.Predicting the future state of a system has always been a natural motivation for science and practical applications. Such a topic, beyond its obvious technical and societal relevance, is also interesting from a conceptual point of view. This owes to the fact that forecasting lends itself to two equally radical, yet opposite methodologies. A reductionist one, based on first principles, and the naïveinductivist one, based only on data. This latter view has recently gained some attention in respon…Read more

35Convex MVAlgebras: ManyValued Logics Meet Decision TheoryStudia Logica 106 (5): 913945. 2018.This paper introduces a logical analysis of convex combinations within the framework of Łukasiewicz realvalued logic. This provides a natural link between the fields of manyvalued logics and decision theory under uncertainty, where the notion of convexity plays a central role. We set out to explore such a link by defining convex operators on MValgebras, which are the equivalent algebraic semantics of Łukasiewicz logic. This gives us a formal language to reason about the expected value of boun…Read more

69Interpretation, coordination and conformityIn Ondrej Majer, AhtiVeikko Pietarinen & Tero Tulenheimo (eds.), Games: Unifying Logic, Language, and Philosophy, Springer Verlag. pp. 3755. 2009.

41Rationality As ConformitySynthese 144 (2): 249285. 2005.We argue in favour of identifying one aspect of rational choice with the tendency to conform to the choice you expect another likeminded, but noncommunicating, agent to make and study this idea in the very basic case where the choice is from a nonempty subset K of 2 A and no further structure or knowledge of A is assumed.

22Machine learning from examples: A noninductivist analysisLogic and Philosophy of Science 3 (1): 131. 2005.

48Jon Williamson: In Defence of Objective Bayesianism: Oxford University Press, Oxford, 2010, vi+185, $85.00 , ISBN 9780199228003 (review)Minds and Machines 23 (2): 255258. 2013.

104Secondorder uncertainty, also known as model uncertainty and Knightian uncertainty, arises when decisionmakers can (partly) model the parameters of their decision problems. It is widely believed that subjective probability, and more generally Bayesian theory, are illsuited to represent a number of interesting secondorder uncertainty features, especially “ignorance” and “ambiguity”. This failure is sometimes taken as an argument for the rejection of the whole Bayesian approach, triggering a B…Read more

17Bridges from classical to nonmonotonic logic (review)Bulletin of Symbolic Logic 12 (3): 499502. 2006.

9Book review: in defence of objective bayesianism (review)Minds and Machines 23 (2): 255258. 2013.

33Book review: in defence of objective bayesianism (review)Minds and Machines 23 (2): 255258. 2013.

43Makinson David. Bridges from classical to nonmonotonic logic. Text in Computing, vol. 5. King's College, London, 2005, xvi+ 216 pp (review)Bulletin of Symbolic Logic 12 (3): 499502. 2006.
Areas of Interest
Epistemology 
Logic and Philosophy of Logic 
Philosophy of Probability 