The justification of Bayes' rule by cognitive rationality principles is undertaken by extending the propositional axiom systems usually proposed in two contexts of belief change: revising and updating. Probabilistic belief change axioms are introduced, either by direct transcription of the set-theoretic ones, or in a stronger way but nevertheless in the spirit of the underlying propositional principles. Weak revising axioms are shown to be satisfied by a General Conditioning rule, extending Bayes' rule but also compatible with others, and weak updating (...) axioms by a General Imaging rule, extending Lewis' rule. Strong axioms (equivalent to the Miller–Popper axiom system) are necessary to justify Bayes' rule in a revising context, and justify in fact an extended Bayes' rule which applies, even if the message has zero probability. (shrink)

Despite its importance in various fields, analogical reasoning has not yet received a unified formal representation. Our contribution proposes a general scheme of inference that is compatible with different types of logic (deductive, probabilistic, non-monotonic). Firstly, analogical assessment precisely defines the similarity of two objects according to their properties, in a relative rather than absolute way. Secondly, analogical inference transfers a new property from one object to a similar one, thanks to an over-hypothesis linking two sets of properties. The belief (...) strength in the conclusion is then directly related to the belief strength in this meta-hypothesis. (shrink)

The Sleeping Beauty problem is presented in a formalized framework which summarizes the underlying probability structure. The two rival solutions proposed by Elga and Lewis differ by a single parameter concerning her prior probability. They can be supported by considering, respectively, that Sleeping Beauty is “fuzzy-minded” and “blank-minded”, the first interpretation being more natural than the second. The traditional absent -minded driver problem is reinterpreted in this framework and sustains Elga’s solution.

Abduction was first introduced in the epistemological context of scientific discovery. It was more recently analyzed in artificial intelligence, especially with respect to diagnosis analysis or ordinary reasoning. These two fields share a common view of abduction as a general process of hypotheses formation. More precisely, abduction is conceived as a kind of reverse explanation where a hypothesis H can be abduced from events E if H is a good explanation of E. The paper surveys four known schemes for abduction (...) that can be used in both fields. Its first contribution is a taxonomy of these schemes according to a common semantic framework based on belief revision. Its second contribution is to produce, for each non-trivial scheme, a representation theorem linking its semantic framework to a set of postulates. Its third contribution is to present semantic and axiomatic arguments in favor of one of these schemes, ordered abduction, which has never been vindicated in the literature. (shrink)

Two main schemes explain how a system adapts to its environment. Evolutionary models are grounded on three usual processes (variation, transmission, selection) acting at the population level. Learning models are concerned with the endogenous search for a better performance at the individual level. The first ones were initially favored by biology and the second well illustrated by game theory. The article examines first how game theory went to evolution and how biology later considered learning. It shows some examples of a (...) hybrid use of models of each type. It finally proposes a common framework for both types of models. (shrink)

L’article propose d’abord une version simplifiée d’une ontologie universelle, conçue comme un cadre général de description du monde matériel et mental. Il examine les notions d’entité, de propriété, de relation et de temporalité et leurs développements conjoints en termes de rapport entre les parties et le tout ou encore d’émergence d’une entité nouvelle. Il illustre ensuite les principes précédents en ce qui concerne la science économique, dont les entités de base sont les agents, les biens et les institutions. Il insiste (...) sur le couplage que cette dernière réalise entre leurs propriétés physiques ou psychologiques et le raisonnement qu’elle propose en termes d’équilibre et plus récemment d’apprentissage. Classification JEL : A12. (shrink)

RésuméEn dépit de son importance dans divers domaines, le raisonnement analogique n'a pas encore reçu de représentation formelle unifiée. Notre contribution propose un schéma d'inférence général, compatible avec différentes logiques (déductive, probabiliste, non monotone). Premièrement, un énoncé analogique définit précisément la similarité entre deux objets en fonction de leurs propriétés, de façon relative et non absolue. Deuxièmement, une inférence analogique transfère une propriété nouvelle d'un objet à un objet similaire, grâce à une hypothèse d'arrière-plan qui relie deux ensembles de propriétés. (...) Le degré de croyance dans la conclusion est alors directement relié au degré de croyance dans cette méta-hypothèse. (shrink)

The paper studies a specific adaptive learning rule when each player faces a unidimensional strategy set. The rule states that a player keeps on incrementing her strategy in the same direction if her utility increased and reverses direction if it decreased. The paper concentrates on games on the square [0,1]×[0,1]\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$[0,1]\times [0,1]$$\end{document} as mixed extensions of 2×2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2\times 2$$\end{document} games. We study in general the (...) behavior of the system in the interior as well as on the borders of the strategy space. We then describe the system asymptotic behavior for symmetric, zero-sum, and twin games. Original patterns emerge. For instance, for the “prisoner’s dilemma” with symmetric initial conditions, the system goes directly to the symmetric Pareto optimum. For “matching pennies,” the system follows slowly expanding cycles around the mixed strategy equilibrium. (shrink)