77 research outputs found
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
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