Online research in philosophy

A common line of argument for the impossibility of closed causal loops is that they would involve causal paradoxes. The usual reply is that such loops impose heavy consistency constraints on the nature of causal connections in them; constraints that are overlooked by the impossibility arguments. Hugh Mellor has maintained that arguments for the possibility of causal loops also overlook some constraints, which are related to the chances (single-case, objective probabilities) that causes give to their effects. And he argues that a consideration of these constraints demonstrates that causal loops are impossible. I consider Mellor's argument and more generally the nature of chance in causal loops. I argue that Mellor's line of reasoning is unwarranted since it is based on untenable premisses about the relation between chances and long-run frequencies in causal loops. Yet, this line of reasoning may still be of interest to those who maintain that causes determine the chances of their effects; for it raises some unresolved questions about the nature of chance in causal loops.

Agents need to be able to change their beliefs; in particular, they should be able to contract or remove a certain belief in order to restore consistency to their set of beliefs, and revise their beliefs by incorporating a new belief which may be inconsistent with their previous beliefs. An influential theory of belief change proposed by Alchourron, G¨ardenfors and Makinson (AGM) [1] describes postulates which a rational belief revision and contraction operations should satisfy. The AGM postulates have been perceived as characterising idealised rational reasoners, and the corresponding belief change operations are considered unsuitable for implementable agents due to their high computational cost [3]. The main result of this paper is showing that an efficient (linear time) belief contraction operation nevertheless satisfies all but one of the AGM postulates for contraction. This contraction operation is defined for a realistic rule-based agent which can be seen as a reasoner in a very weak logic; although the agent’s beliefs are deductively closed with respect to this logic, checking consistency and tracing dependencies between beliefs is not computationally expensive. Finally, we give a non-standard definition of belief revision in terms of contraction for our agent.

In the context of a general framework for belief dynamics which interprets revision as doxastic constraint satisfaction, we discuss a proposal for revising quasi-probabilistic belief measures with finite sets of graded conditionals. The belief states are ranking measures with divisible values (generalizing Spohn’s epistemology), and the conditionals are interpreted as ranking constraints. The approach is inspired by the minimal information paradigm and based on the principle-guided canonical construction of a ranking model of the input conditionals. This is achieved by extending techniques known from conditional default reasoning. We give an overview of how it handles different principles for conditional and parallel revision and compare it with similar accounts.

In this article, a qualitative notion of subjective plausibility and its revision based on a preorder relation are implemented in higher-order logic. This notion of plausibility is used for modeling pragmatic aspects of communication on top of traditional two-dimensional semantic representations.

We propose a modal logic based on three operators, representing intial beliefs, information and revised beliefs. Three simple axioms are used to provide a sound and complete axiomatization of the qualitative part of Bayes’ rule. Some theorems of this logic are derived concerning the interaction between current beliefs and future beliefs. Information flows and iterated revision are also discussed.

We propose a revision operator on a stratified belief base, i.e., a belief base that stores beliefs in different strata corresponding to the value an agent assigns to these beliefs. Furthermore, the operator will be defined as to perform the revision in such a way that information is never lost upon revision but stored in a stratum or layer containing information perceived as having a lower value. In this manner, if the revision of one layer leads to the rejection of some information to maintain consistency, instead of being withdrawn it will be kept and introduced in a different layer with lower value. Throughout this development we will follow the principle of minimal change, being one of the important principles proposed in belief change theory, particularly emphasized in the AGM model. Regarding the reasoning part from the stratified belief base, the agent will obtain the inferences using an argumentative formalism. Thus, the argumentation framework will decide which information prevails when sentences of different layers are used for entailing conflicting beliefs. We will also illustrate how inferences are changed and how the status of arguments can be modified after a revision process.

We show in this paper that the AGM postulates are too weak to ensure the rational preservation of conditional beliefs during belief revision, thus permitting improper responses to sequences of observations. We remedy this weakness by proposing four additional postulates, which are sound relative to a qualitative version of probabilistic conditioning. Contrary to the AGM framework, the proposed postulates characterize belief revision as a process which may depend on elements of an epistemic state that are not necessarily captured by a belief set. We also show that a simple modification to the AGM framework can allow belief revision to be a function of epistemic states. We establish a model-based representation theorem which characterizes the proposed postulates and constrains, in turn, the way in which entrenchment orderings may be transformed under iterated belief revision.

We report empirical results on factors that influence how people reason with default rules of the form "Most x's have property P", in scenarios that specify information about exceptions to these rules and in scenarios that specify default-rule inheritance. These factors include (a) whether the individual, to which the default rule might apply, is similar to a known exception, when that similarity may explain why the exception did not follow the default, and (b) whether the problem involves classes of naturally occurring kinds or classes of artifacts. We consider how these findings might be integrated into formal approaches to default reasoning and also consider the relation of this sort of qualitative default reasoning to statistical reasoning.

This paper continues the recent tradition of investigating iterated AGM revision by reasoning directly about the dynamics for total pre-order (“implausibility ordering”) representations of AGM revision functions. We reorient discussion, however, by proving that symmetry considerations, almost by themselves, suffice to determine a particular, AGM-friendly implausibility ordering dynamics due to Spohn 1988, which we call “J-revision”. After exploring the connections between implausibility ordering dynamics and the social choice theory of Arrow 1963, we provide symmetry arguments in the social choice-theoretic framework for an interesting generalization of J-revision due to Nayak 1994. We conclude by arguing that the symmetry principles that uniquely favor J-revision and its generalizations are importantly expressive of the purely qualitative framework for representing beliefs that distinguishes the AGM program. Our results therefore comprehensively vindicate Spohn's 1988 conjecture that essentially J-revision is the best that can be done by way of a purely qualitative model of belief revision.

The process of changing beliefs as a result of accepting the new information is often called Belief revision. It occupies a central position in the area of philosophy, theoretical computer science and logic. However, problem of Belief revision in general is how an agent revises her current beliefs when new information obtained from reliable and evidential source contradicts some of the old beliefs, while preserving the core beliefs. One of the key aspects of the problem of changing beliefs is to provide a means of accommodating new information causing minimal change to the beliefs already held by an agent. Therefore, providing an appropriate mechanism for ordering beliefs in the belief revision is important. This dissertation is a contribution to the study of belief revision from both causal and constructive perspective. Modeling of belief revision address the following general question: Given an initial knowledge base and a new piece of information to be incorporated into it, what should be the appropriate ordering of beliefs so that less entrenched beliefs are lost when compared to more entrenched beliefs. In this study we focus on \emph{causal relevance} and propose a new entrenchment ordering, called as causal epistemic entrenchment (CEE). We ground it on a solid semantic foundation by making use of structure, intervention, causal properties, and causal mechanism. The key idea of such an entrenchment ordering is that not all conditional beliefs in a belief set are important and hence not all beliefs would be relevant for the Belief revision. Precisely, the thesis makes the following contributions. 1. Motivated by scientific theory change in the philosophy and history of science in the context of causality, we present an explanatory approach to model belief revision based on the notion causal relevance. However, our formulation of causal relevance is based on semantic considerations such as structure, intervention, causal process, and causal mechanism. 2. Development of a new entrenchment ordering namely the Causal Epistemic Entrenchment (CEE), suitable for prioritizing conditional beliefs in the belief revision process. It works better especially in preserving the core beliefs, and cases arising from iterated belief revision, theory choice, and the causal dependencies of beliefs. 3. We explored the link between causality and the dynamics of beliefs while emphasizing on causal consistency apart from the logicalconsistency.