Some Remarks on the Model Theory of Epistemic Plausibility Models

Classical logics of knowledge and belief are usually interpreted on Kripke models, for which a mathematically well-developed model theory is available. However, such models are inadequate to capture dynamic phenomena. Therefore, epistemic plausibility models have been introduced. Because these are much richer structures than Kripke models, they do not straightforwardly inherit the model-theoretical results of modal logic. Therefore, while epistemic plausibility structures are well-suited for modeling purposes, an extensive investigation of their model theory has been lacking so far. The aim of the present paper is to fill exactly this gap, by initiating a systematic exploration of the model theory of epistemic plausibility models. Like in 'ordinary' modal logic, the focus will be on the notion of bisimulation. We define various notions of bisimulations (parametrized by a language L) and show that L-bisimilarity implies L-equivalence. We prove a Hennesy-Milner type result, and also two undefinability results. However, our main point is a negative one, viz. that bisimulations cannot straightforwardly be generalized to epistemic plausibility models if conditional belief is taken into account. We present two ways of coping with this issue: (i) adding a modality to the language, and (ii) putting extra constraints on the models. Finally, we make some remarks about the interaction between bisimulation and dynamic model changes.Comment: 19 pages, 3 figure

Interpreting an action from what we perceive and what we expect

International audienceIn update logic as studied by Baltag, Moss, Solecki and van Benthem, little attention is paid to the interpretation of an action by an agent, which is just assumed to depend on the situation. This is actually a complex issue that nevertheless complies to some logical dynamics. In this paper, we tackle this topic. We also deal with actions that change propositional facts of the situation. In parallel, we propose a formalism to accurately represent an agent's epistemic state based on hyperreal numbers. In that respect, we use infinitesimals to express what would surprise the agents (and by how much) by contradicting their beliefs. We also use a subjective probability to model the notion of belief. It turns out that our probabilistic update mechanism satisfies the AGM postulates of belief revision

Dynamic context logic

International audienceBuilding on a simple modal logic of context, the paper presents a dynamic logic characterizing operations of contraction and expansion on theories. We investigate the mathematical properties of the logic, and show how it can capture some aspects of the dynamics of normative systems once they are viewed as logical theories

Postulates for Revocation Schemes

In access control frameworks with the possibility of delegating permissions and administrative rights, delegation chains can form. There are di erent ways to treat these delegation chains when revoking rights, which give rise to di erent revocation schemes. Hagstr om et al. [11] proposed a framework for classifying revocation schemes, in which the di erent revocation schemes are de ned graph-theoretically. At the outset, we identify multiple problems with Hagstr om et al.'s de nitions of the revocation schemes, which can pose security risks. This paper is centered around the question how one can systematically ensure that improved de nitions of the revocation schemes do not lead to similar problems. For this we propose to apply the axiomatic method originating in social choice theory to revocation schemes. Our use of the axiomatic method resembles its use in belief revision theory. This means that we de ne postulates that describe the desirable behaviour of revocation schemes, study which existing revocation frameworks satisfy which postulates, and show how all de ned postulates can be satis ed by de ning the revocation schemes in a novel way

On the Right Path: A Modal Logic for Supervised Learning

Formal learning theory formalizes the process of inferring a general result from examples, as in the case of inferring grammars from sentences when learning a language. Although empirical evidence suggests that children can learn a language without responding to the correction of linguistic mistakes, the importance of Teacher in many other paradigms is significant. Instead of focusing only on learner(s), this work develops a general framework---the supervised learning game (SLG)---to investigate the interaction between Teacher and Learner. In particular, our proposal highlights several interesting features of the agents: on the one hand,Learner may make mistakes in the learning process, and she may also ignore the potential relation between different hypotheses; on the other hand, Teacher is able to correct Learner's mistakes, eliminate potential mistakes and point out the facts ignored by Learner. To reason about strategies in this game, we develop a modal logic of supervised learning (SLL). Broadly, this work takes a small step towards studying the interaction between graph games, logics and formal learning theory.Comment: The paper was accepted by LORI 2019. But due to the page-limit constraints, that Proceedings version does not include any proofs. In this version, we show the proofs for the result

Dynamics of Macrophage Trogocytosis of Rituximab-Coated B Cells

Macrophages can remove antigen from the surface of antibody-coated cells by a process termed trogocytosis. Using live cell microscopy and flow cytometry, we investigated the dynamics of trogocytosis by RAW264.7 macrophages of Ramos B cells opsonized with the anti-CD20 monoclonal antibody rituximab. Spontaneous and reversible formation of uropods was observed on Ramos cells, and these showed a strong enrichment in rituximab binding. RAW-Ramos conjugate interfaces were highly enriched in rituximab, and transfer of rituximab to the RAW cells in submicron-sized puncta occurred shortly after cell contact. Membrane from the target cells was concomitantly transferred along with rituximab to a variable extent. We established a flow cytometry-based approach to follow the kinetics of transfer and internalization of rituximab. Disruption of actin polymerization nearly eliminated transfer, while blocking phosphatidylinositol 3-kinase activity only resulted in a delay in its acquisition. Inhibition of Src family kinase activity both slowed acquisition and reduced the extent of trogocytosis. The effects of inhibiting these kinases are likely due to their role in efficient formation of cell-cell conjugates. Selective pre-treatment of Ramos cells with phenylarsine oxide blocked uropod formation, reduced enrichment of rituximab at cell-cell interfaces, and reduced the efficiency of trogocytic transfer of rituximab. Our findings highlight that dynamic changes in target cell shape and surface distribution of antigen may significantly influence the progression and extent of trogocytosis. Understanding the mechanistic determinants of macrophage trogocytosis will be important for optimal design of antibody therapies