Dissertationen zum Thema „Belief“

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Linguistics and Philosophy, 2008.
Includes bibliographical references (leaves 127-132).
This dissertation studies the logics of value and conditionals, and the question of whether they should be given cognitivist analyses. Emotivist theories treat value judgments as expressions of desire, rather than beliefs about goodness. Inference ticket theories of conditionals treat them as expressions of conditional beliefs, rather than propositions. The two issues intersect in decision theory, where judgments of expected goodness are expressible by means of decision-making conditionals. In the first chapter, I argue that decision theory cannot be given a Humean foundation by means of money pump arguments, which purport to show that the transitivity of preference and indifference is a requirement of instrumental reason. Instead, I argue that Humeans should treat the constraints of decision theory as constitutive of the nature of preferences. Additionally, I argue that transitivity of preference is a stricter requirement than transitivity of indifference. In the second chapter, I investigate whether David Lewis has shown that decision theory is incompatible with anti-Humean theories of desire. His triviality proof against "desire as belief' seems to show that desires can be at best conditional beliefs about goodness. I argue that within causal decision theory we can articulate the cognitivist position where desires align with beliefs about goodness, articulated by the decision making conditional. In the third chapter, I turn to conditionals in their own right, and especially iterated conditionals.
(cont.) I defend the position that indicative conditionals obey the import-export equivalence rather than modus ponens (except for simple conditionals), while counterfactual subjunctive conditionals do obey modus ponens. The logic of indicative conditionals is often thought to be determined by conditional beliefs via the Ramsey Test. I argue that iterated conditionals show that the conditional beliefs involved in indicative supposition diverge from the conditional beliefs involved in learning, and that half of the Ramsey Test is untenable for iterated conditionals.
by David Jeffrey Etlin.
Ph.D.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Linguistics and Philosophy, 2001.
Includes bibliographical references (p. 207-209).
My dissertation is about Frege's classic problem of the morning and the evening star. I distinguish two aspects of the problem. One aspect I call it psychological, and it consists in describing the content of the beliefs of people who are willing to assent to pairs like (1) 'Hesperus is nice' and (2) 'Phosphorus is not nice.' I assume an interpretivist account of belief content, according to which an agent has the beliefs that best explain her behavior, and I propose certain principles of interpretation to substantiate this view. I use this account to argue that the person who assents to (1) and (2) is not incoherent, but simply mistaken about the proposition expressed by those sentences. In my view, the subject who assents to (1) and (2) takes them to express propositions about different planets, but at least one of those planets cannot be a real planet. I propose that it is a fictional one, and appeal to Kendall Walton's account of prop-oriented make-believe to explain how to use propositions that are about fictional entities to describe the belief state of people who are confused about some identity. The other aspect of the problem I call it semantical, and it consists in explaining how pairs of attributions like 'Charles believes that Hesperus is nice' and 'Charles does not believe that Phosphorus is nice' can be true at the same time. I offer a semantics based on the idea that, when we describe the belief state of people who are confused about some identity, we have to put ourselves in their shoes. We put ourselves in someone else's shoes by modifying our belief state to resemble the belief state of the other person; when we change our beliefs in this way, we acquire the beliefs necessary to talk of a single object as if it were two different ones. I argue that this Simulation Semantics can offer a satisfactory treatment of certain examples of belief attribution that cannot be handled by contemporary theories (examples in which the subject of the attribution is both confused about an identity, and is not familiar with the words that we use to attribute a belief to her). I also argue that this semantics has interesting applications to other problems in the philosophy of language, like for example the problem of the informativeness of identity statements. 7102 M
by Miguel Hernando.
Ph.D.

The purpose of this study was to describe the views of peer evaluators within a career ladder system in one school district in the Southwestern United States. The methods and data analysis used 3 parts of a theoretical framework developed by Lortie (1975): goals sought in the workplace (perspectives on purpose), effective teaching (and the effects of endemic uncertainties of teaching to effectiveness), and preferences in job tasks (logic of sentiments). Eleven peer evaluators were interviewed. The data from the interviews were qualitatively analyzed and presented. Among the findings, peer evaluators' perspectives on purpose included goals to gain experience for leaving the classroom. Peer evaluators' endemic uncertainties included the assessment of teaching and the description of an effective teacher. Within peer evaluators' logic of sentiments, they preferred to observe students and work with teachers. Peer evaluators disliked determining the compensation of teachers. Within their logic of sentiments, peer evaluators viewed teachers as a well-qualified group willing to continue their own professional growth. Peer evaluators found their relationship with teachers constrained because of their roles of assisting teachers in their professional growth and summatively assessing teachers. Implications of this study include the need for further study to describe the views of teachers involved in differentiated staffing in career ladder programs. Additionally, further study is needed to determine the relationship of the views of teachers within a career ladder program to the success of the policies and activities of these programs.

This thesis proposes an acausal version of the Loopy Belief Propagation (LBP) algorithm, motivated by the conjecture that such algorithms might possess different stability and convergence properties than in their usual causal formulation. It is shown that, prior to the introduction of evidence, the new algorithm has a fixedpoint giving the correct marginal distributions even for loopy networks, unlike its causal counterpart. A translation for causal networks is given to allow for behavior of the two algorithms to be compared for the same networks, and the comparison is discussed based on empirical results. The acausal algorithm is seen to exhibit different, but not necessarily superior, convergence properties for the networks tested. It may nonetheless be useful as an application of the principle of Loopy Belief Propogation for systems which are given by acausal rather than causal models, for which it provides a much faster computation than the sampling-based techniques frequently applied in such cases.

The measurement of religious belief has some social desirability concerns that make the development of an implicit measure of religiosity advantageous. Currently, there are few options for implicitly measuring religious belief. This study attempted to add to this literature by analyzing the automatic judgements of religious belief through the use of an implicit measure known as the MouseTrack task, allowing for the measurement of latency in the expression of these beliefs as well as the certainty of these beliefs by tracking the path taken during the decision process. A sample of 121 undergraduates was recruited from the UK SONA subject pool. Desired religious variance was not achieved in the sample, making interpretation of results difficult. Detailed breakdowns of these path analyses are given. Key trends in findings are discussed.

Usually, the researchers of traditional belief change theories (e.g., AGM theory) assume that the knowledge of the agents which have the lower priorities should fully accept the knowledge of those higher priority ones in the process of belief revision. These kinds of theories are called prioritized belief change theories. On the contrary, in the discussion of non-prioritized belief change theories (e.g., Konieczny and Pino-P{\'e}rez's merging theory), the belief changes happen among the agents which have the same priorities. In this dissertation, we provide a new style of epistemic states and the belief change operations on this kind of epistemic states such that the prioritized or non-prioritized characteristics of belief change operators will be determined only by the properties of agents' knowledge.

I argue for a view I call sensitivism about belief. According to sensitivism, belief is sensitive to just those factors of context which epistemic contextualists claim are relevant to the semantics of words like "know": in particular, whether an agent believes p depends on the not-p alternatives salient to the agent, and the practical importance of p for the agent. I argue for sensitivism about both outright belief and partial belief, and outline a sensitivist formal model of belief. In chapter 1, I make a preliminary case for sensitivism, and for interest in sensitivism. After surveying some similar views in the literature, I present a scenario which is nicely explained by sensitivism, and which gives the view some intuitive plausibility. I also argue for the relevance of sensitivism to the debate over epistemic contextualism. In chapter 2, I argue that we need sensitivism about outright belief if we want to maintain both a Stalnakerian picture of how assertion works, and the principle that an assertion that p is sincere if and only if the assertor believes that p. I then outline a sensitivist formal model of outright belief. In chapter 3, I present a solution to the preface paradox which this model of belief makes available, and argue that it is more intuitively appealing than the more popular probabilistic solutions. In chapter 4, I argue that we should extend sensitivism to credences as well as outright belief. In particular, I advance the following two theses: (CONTEXT) Degrees of belief change from context to context, depending on the space of alternative possibilities. (UNITY) Outright belief is belief to degree 1. I claim that (UNITY) solves the usual paradoxes to which threshold views of outright belief fall prey, and (CONTEXT) undermines the usual reasons given for rejecting (UNITY).

Two assumptions are often made about the nature of the cognitive attitudes that allow us to engage with fiction and in pretence: the uniformity and the non-doxastic assumptions. The uniformity assumption tells us that both of these activities involve the same cognitive attitudes. The non-doxastic assumption tells us that these cognitive attitudes are not beliefs, but belief-like states that we can call belief-like imaginings. I will challenge both of these assumptions in this thesis. In the case of the uniformity assumption, I will draw a distinction between voluntary and involuntary imaginative counterparts. I will argue that if a belief-like counterpart is involved in our engagement in pretence, it will be a voluntary counterpart, whereas an involuntary one will have to be associated with our engagement with fiction. Against the non-doxastic assumption, I will argue that we can explain our engagement with these activities by introducing beliefs with distinct contents. In the case of pretence, I will suggest that the relevant beliefs are of the form ‘[I believe] I PRETEND that “p”’. In the case of fiction, I will argue that the relevant beliefs are of the form ‘I believe p [in the fiction]’. This will lead to us challenging the non-doxastic assumption on the grounds that belief-like imaginings are unnecessary for explaining how we are able to engage with fiction and in pretence. I will also offer some arguments for why belief-like imaginings might be insufficient for explaining how we are able to engage with fiction and in pretence. In particular, I will argue that belief-like imaginings do not do enough to explain how we recognise when someone else is engaging in pretence, and that they struggle to make sense of why our representations related to fiction and pretence exhibit what Walton calls ‘clustering’.

Thesis: Ph. D. in Philosophy, Massachusetts Institute of Technology, Department of Linguistics and Philosophy, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 76-80).
Chapter 1, 'Living on the Edge: Against Epistemic Permissivism,' argues that Epistemic Permissivists face a special problem about the relationship between our first- and higher-order attitudes. They claim that rationality often permits a range of doxastic responses to the evidence. Given plausible assumptions about the relationship between your first- and higher-order attitudes, you can't stably be on the edge of the range, so there can't be a range at all. Permissivism, at least as it has been developed so far, can't be right. I consider some new ways of developing Permissivism, but each has problems of its own. Chapter 2, 'Belief and Probability,' argues that rational belief doesn't reduce to subjective probability. Under the right circumstances, I argue, acquiring conflicting evidence can defeat your entitlement to believe a certain hypothesis without probabilistically disconfirming that hypothesis. I consider three probabilistic theories of rational belief-a simple threshold view, Hannes Leitgeb's stability theory, and a new theory involving imprecise credence-and show that none of them can account for the cases I describe. Chapter 3, 'Can We Decide to Believe?', takes up the question of whether we can decide to believe. There are two main arguments for the conclusion that believing at will is impossible, which I call the retrospective argument and the aim-of-belief argument, respectively. Neither, I argue, demonstrates that believing at will is impossible in all cases. The retrospective argument leaves open the possibility of believing at will in acknowledged permissive cases; the aim-of-belief argument leaves open the possibility of believing at will when credal attitudes are imprecise.
by Ginger Schultheis.
Ph. D. in Philosophy

To defend the objectivity and epistemic significance of science from claims that theory choice reflects scientists' values, McMullin has suggested that we clearly identify epistemic values - those such as truth which are the characteristic normative goals of science - and distinguish them from non-epistemic values. The question of the objectivity of a scientific inquiry then reduces to the question of whether it is primarily driven by epistemic values. This thesis illustrates how, using a decision-theoretic model, we can decide whether a motivation is epistemic or non-epistemic by looking at the consequences of potential actions that it attaches to. Building on this structural definition, we produce a succession of further definitions, distinguishing between epistemically and non-epistemically motivated inquiries, people, methods of persuasion and processes of interpretation. The resulting concept of epistemic value can demarcate science and non-science that is not committed to any particular method, nor to methodological anarchy. The model allows us to examine the potential behaviour of hypothetical agents. This method shows that epistemic motivation results in a desire for reliable information, while non-epistemic motivation makes information undesirable or even aversive. From this we get an empirical criterion distinguishing the two attitudes. Another useful hypothetical is to imagine a scientist who wants to assert a maximum number of truths by making a small number of statements. Under these circumstances, we find it can be rational to assert a theory with known false consequences, or a theory that is strictly meaningless but empirically adequate. Since the thesis makes use of Bayesian decision theory, the question naturally arises of how applicable it is to real people. The first part of the thesis defends the descriptive use of BDT in ordinary belief/desire explanation and shows that this does not involve any strong metaphysical presumptions about the entity being explained.

In my thesis I ask the epistemological question: If a speaker testifies to some proposition p to some hearer, and the hearer learns that p, must that speaker believe that p? Those who maintain the traditional view in the epistemology of testimony claim that testimony is primarily a way in which speakers transmit beliefs to hearers. If this is the case, then in order to transmit the belief that p, the speaker must be in possession of a belief that p. Other epistemologists reject this view altogether and argue that when speakers stand in the right sort of epistemic relation to the statements they issue they properly testify. My project carves out a position between these two views. I argue that speakers need not believe p, but speakers must be in some appropriate epistemic state with respect to p in order to properly testify to p. On my view, understanding is among the epistemic states that can place a speaker in the right sort of epistemic relation to p. Thus, if p is a consequence of a speaker's understanding of a subject, the speaker is licensed to testify that p.
Master of Arts

This thesis develops the belief space scheduling framework for scheduling under uncertainty in Stochastic Collection and Replenishment (SCAR) scenarios. SCAR scenarios involve the transportation of a resource such as fuel to agents operating in the field. Key characteristics of this scenario are persistent operation of the agents, and consideration of uncertainty. Belief space scheduling performs optimisation on probability distributions describing the state of the system. It consists of three major components---estimation of the current system state given uncertain sensor readings, prediction of the future state given a schedule of tasks, and optimisation of the schedule of the replenishing agents. The state estimation problem is complicated by a number of constraints that act on the state. A novel extension of the truncated Kalman Filter is developed for soft constraints that have uncertainty described by a Gaussian distribution. This is shown to outperform existing estimation methods, striking a balance between the high uncertainty of methods that ignore the constraints and the overconfidence of methods that ignore the uncertainty of the constraints. To predict the future state of the system, a novel analytical, continuous-time framework is proposed. This framework uses multiple Gaussian approximations to propagate the probability distributions describing the system state into the future. It is compared with a Monte Carlo framework and is shown to provide similar discrimination performance while computing, in most cases, orders of magnitude faster. Finally, several branch and bound tree search methods are developed for the optimisation problem. These methods focus optimisation efforts on earlier tasks within a model predictive control-like framework. Combined with the estimation and prediction methods, these are shown to outperform existing approaches.

We must change our beliefs, and change them in particular ways, in response to new information. But not all changes are created equal: some are rational changes, some not. The Problem of Epistemic Change is the problem of specifying the rational constraints on how the epistemic state of an agent ought to change in the face of new information. This dissertation is about the philosophical and logical investigation of rational belief change. I start by arguing that the familiar foundations---coherence distinction from static epistemology does not adequately carve up the logical space of theories of epistemic change. It is better to think of theories as being loosely ordered along a continuum from more to less foundational. The ordering, however, is "clumpy" in the sense that there are large regions in the ordering which remain unexplored. I then present and develop GDEC which is a new foundations model of belief revision that fills a gap in this ordering of theories of epistemic change. The key insight in GDEC is that belief that...is ambiguous between the attitudes of accept that...and expect that... GDEC respects the difference and how it matters for epistemic change. I show that GDEC is a genuine competitor to the AGM theory of belief revision in the sense that the two approaches are incompatible. The remainder of the dissertation is devoted to exploring the logical dynamics of GDEC and the models I develop here which extend it by applying them to a series of richer epistemic environments. I show how puzzles and paradoxes which confound other theories of belief revision are solved in a unified way by GDEC and its extensions. In particular, I give solutions to Moore's Paradox, Fuhrmann's Impossibility Theorem, the Reduction Problem of Epistemic Conditionals, and the Gardenfors Impossibility Theorem.

In this dissertation I explore the relative roles of cognition and culture play as the foundations of religious and supernatural belief. On the cognitive side, theories of religion have postulated several cognitive biases that predispose human minds towards supernatural belief. However, to this date, very little empirical evidence exists to show how these hypotheses preform in predicting actual religious beliefs. I explore these biases and how they interrelate to support supernatural beliefs using individual difference measures across several large samples from Canada, the US, the Czech Republic and Slovakia. On the cultural side, I look at how different theories of secularization and the CREDs theory of cultural learning support supernatural belief and religious practice. I compare these effects of culture to the effects of cognition and find that cognitive biases support supernatural belief generally, but these effects are stronger for paranormal beliefs than religious ones and are almost non-existence for religious practice. Religious belief and practice are largely supported by social and cultural factors. Finally, I compare religious and non-religious participants to spiritual but not religious (SBNR) participants to further break down the differences between religious and non-religious supernatural beliefs and religious practice. I find that the SBNR are more like the religious than the non-religious but can still be identified as a unique group in terms of cognition and culture.
Arts, Faculty of
Psychology, Department of
Graduate

Karmic beliefs, centered on the notion of ethical causation within and across lifetimes, appear in religious traditions and spiritual movements around the world, yet they remain an unexplored topic in psychology. I developed and validated a 16-item measure of belief in karma, and used this measure to assess the cultural distribution, cognitive content, and correlates of karmic beliefs among participants from culturally and religiously diverse backgrounds, including Canadian students (Sample 1: N = 3193, Sample 2: N = 3072) and broad national samples of adults from Canada (N = 1000) and India (N = 1006). Belief in karma showed predictable variation based on participant’s cultural (e.g., Indian) and religious (e.g., Hindu and Buddhist) background, but was also surprisingly common among people from cultural groups with no tradition of karmic beliefs (e.g., nonreligious or Christian Canadians). I demonstrate how karmic beliefs are related to, but distinct from, conceptually-similar beliefs, including belief in a just world and belief in a moralizing god. Finally, I provide preliminary evidence of intuitive conceptions of karma, and investigate how karma is related to self-reported prosocial behaviour and moral judgments. Karma is a form of supernatural justice belief, endorsed by many people from diverse cultural and religious backgrounds that lies at the intersection between beliefs about justice and morality, and beliefs about supernatural forces that shape the course of life’s events.
Arts, Faculty of
Psychology, Department of
Graduate

Hume’s theory of belief and his normative standard or ethics of belief are founded on empirically observable, natural principles, principles which have been misunderstood by those who view Hume’s belief theory as one based on the forcefulness and liveliness of our ideas. In this dissertation, I argue that, according to Hume, both factual and value judgments are arrived at via the same basic, natural processes of the mind. All human judgments are ultimately derived from feeling or affect, that is, from internal impressions which arise within the human mind in tandem with, or in reaction to, its experience of ideational content, that is, the “parts or composition of the idea, which we conceive.” According to Hume, then, our feelings, operating in concert with the sensory and cognitive functions of the mind, provide us with our final standards of judgment, whether factual or evaluative. Our ethics of belief—our normative standards of belief—are therefore, like belief itself, more properly ascribable to the “sensitive” or feeling part of our nature, than to the non-affective, rational, or cogitative aspects of cognition. In sum, for Hume, belief is a complex but wholly natural cognitive phenomenon, consisting of, firstly, our experience of ideational content, and secondly, our feeling of cognitive commitment—the feeling of believing in the ideational content experienced. All judgments, factual and evaluative, are composed in this way.

This is a study of a problem in the logic of belief revision. On the assumption of a number of fairly traditional views concerning the relationship between mind and world, the mechanics of perception, and the nature of belief, an argument is made to the effect that revision of extant beliefs is impossible even in the light of new perceptual experience. The argument turns on the ability of a cognitive system to recognize conflict among its thoughts and perceptions. A number of models of the mechanics of perceptual interpretation are explored, all of which are revealed to share a susceptibility to the problem as posed. Certain objections are taken up, the responses to which modify the scope of the original argument; although the problem may yet be said to arise in a number of crucial contexts where its presence is undesirable, some situations are found in which the problem can be dissolved. The problem is then reexamined in light of the epistemological position called fallibilism, with an eye to demonstrating that it arises notwithstanding the highly cautious perspective embodied in that position. A solution to the problem is then offered in the form of a family of model cognitive systems with certain properties. Because the problem is a feature of belief-based cognitive systems, the family of systems offered in arguing for a resolution of the problem is constructed on the notion that cognition, construed as information processing, normally proceeds without any epistemic evaluations being attached either to perceptions in particular or thoughts in general. The non-evaluative propositional attitude employed in normal cognition should, I argue, be what I call acceptance. The propositional attitude of belief, traditionally conceived of as occupying the role now given to acceptance, is accorded an extremely limited scope of application. Epistemic evaluation in general is itself restricted to contexts of decision only, its application arising only

In this thesis, I explore a number of epistemological issues concerning the relations between knowledge, belief and practical matters. In particular, I defend a view, which I call credal pragmatism. This view is compatible with moderate invariantism, a view that takes knowledge to depend exclusively on truth-relevant factors and to require an invariant epistemic standard of knowledge that can be quite easily met. The thesis includes a negative and a positive part. In the negative part (Ch. 1-4) I do two things: i) I critically examine some moderate invariantist accounts of the intuitive influence of practical factors on knowledge ascriptions, and ii) I provide a criticism of the idea that knowledge is the norm of practical reasoning. In Chapter 1, I provide a general overview of the issues that constitute the background for the views and arguments defended in my thesis. In particular, I provide a thorough discussion of two aspects of the relation between knowledge and practical matters: one is constituted by the practical factors' effects on knowledge ascriptions; the other is the intuitive normative role of knowledge in the regulation and assessments of action and practical reasoning. In Chapter 2, I consider and criticize Timothy Williamson's account according to which an alleged failure to acknowledge the distinction between knowing and knowing that one knows generates the intuition that knowledge ascriptions are sensitive to practical factors. In Chapter 3, I argue against the idea that practical reasoning is governed by a knowledge norm. The argument generalizes to other candidate epistemic norms of practical reasoning. In Chapter 4, I criticise a number of accounts which explain effects of practical factors on knowledge ascriptions in terms of the influence of practical factors on belief. These include the accounts of Brain Weatherson, Dorit Ganson, Kent Bach and Jennifer Nagel. In the positive part of the thesis (Ch. 5-6), I develop and argue for credal pragmatism, an original account of the nature and interaction of different doxastic attitudes and the role of practical factors in their rational regulation. On this view, given a certain fixed amount of evidence, the degree of credence of an adaptively rational agent varies in different circumstances depending on practical factors, while the threshold on the degree of credence necessary for outright belief remains fixed across contexts. This account distinguishes between two kinds of outright belief: occurrent belief, which depends on the actual degree of credence, and dispositional belief, which depends on the degree of credence in normal circumstances. In Chapter 5, I present the view and I show how credal pragmatism can explain the practical factors' effects on knowledge ascriptions. In Chapter 6, I develop a fallibilist account of several features about knowledge ascriptions including i) why in folk epistemological practices knowledge is often taken to be a necessary and sufficient epistemic condition for relying on a proposition in practical reasoning; ii) concessive knowledge attributions and related data; and iii) the infallibilist intuition that knowledge excludes error possibilities.

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.
Includes bibliographical references (leaf 53).
by Marina Zhurakhinskaya.
M.Eng.

In this thesis, we explore the question: What is a belief? We do so by considering the folk psychological concept of belief and attempting to unearth some constitutive features of it. We argue that, according to this concept, there is a significant relationship between belief and reasons: one which reveals that beliefs aim at truth, as Bernard Williams (1973) once famously put it. We argue for a particular interpretation of this claim, according to which it is to be understood as follows: (R): It is constitutive of belief that if it is consciously regulated, it is so-regulated solely for truth; and (C): It is constitutive of belief that it is correct if and only if its contents are true. We maintain that (C) explains why it is that (R) is true. So, belief is at base a normative concept: the question as to why one holds a particular belief can always be raised. We then explore two irrational phenomena – self-deception and delusion – and further unravel what (R) and (C) involve, as well as shedding some light on the phenomena themselves. We argue for a position we call doxastic minimalism about self-deception, according to which, in the paradigm case, the self-deceiver holds neither their undesired belief that p nor their desired belief that ~p. This is because they do not have attitudes to these contents that meet conditions (R) and (C). Similarly, we argue that although cases of delusion vary significantly, in some extreme cases, the subject does not seem to relate to the content of their delusion in a manner that meets (R) and (C), and hence ought not to be attributed a belief in such contents.

We propose sparse-matrix belief propagation, which executes loopy belief propagation in Markov random fields by replacing indexing over graph neighborhoods with sparse-matrix operations. This abstraction allows for seamless integration with optimized sparse linear algebra libraries, including those that perform matrix and tensor operations on modern hardware such as graphical processing units (GPUs). The sparse-matrix abstraction allows the implementation of belief propagation in a high-level language (e.g., Python) that is also able to leverage the power of GPU parallelization. We demonstrate sparse-matrix belief propagation by implementing it in a modern deep learning framework (PyTorch), measuring the resulting massive improvement in running time, and facilitating future integration into deep learning models.
Master of Science

Modern philosophy is often said to privilege rationality over received wisdom, but to some extent this is an ideal which we pursue under a measure of uncertainty. It is not always obvious what rationality requires. Nor is it clear how rationality is to be traded against other ideals. This dissertation seeks to clarify both questions as they pertain to the rationality of belief. The choice of topic is apposite, since many argue that the case of belief illustrates that what is rational and what there is most reason to do is one and the same thing. In particular, so-called evidentialists often argue that to believe what the evidence indicates is both to believe rationally and to believe what one has most reason to believe, since (i) rationality consists in responding to reasons, and (ii) only evidence that p can be a reason to believe that p. My first objective is to challenge this thesis. I do so by arguing that the class of reasons that rationalise a belief does not coincide with the class of reasons there are to have the belief all things considered. To equate the two classes would be to conflate the psychological issue of how we respond to reasons with the ontological issue of what reasons there are. My case against evidentialism does not depend on pragmatism being true, however. Even if Pascal was wrong to claim that the expected benefit of believing can be a reason to believe, it does not follow that evidentialism is true. Some non-pragmatic form of anti-evidentialism may still be true. The latter half of the dissertation explores this possibility in greater detail. There I argue that there is at least one class of beliefs which is not subject to common evidentiary strictures. When we use practical reasoning to form intentions about what to do in the future, we typically also form beliefs about what we will do. Yet, those beliefs are not based on evidence about what we will do, I argue. Typically, we do not predict what we do based on what we intend to do. Nor should we. When it is up to us whether we will perform an action, our intentions do to not carry enough weight as evidence that we must use them to predict what we will do. In the last part of the dissertation, I use this point to elucidate how we acquire self-knowledge and how belief relates to truth.

This project examined, by qualitative investigation, the actual content and mechanics of ghost beliefs in Britain today. Through questionnaire, personal interview, and email correspondence, the beliefs and experiences of 227 people were assessed, and considered against historical and international analogous material. The research began with some basic questions: who believes; what do they believe; how do they narrate their stories; and how do they understand this in the context of other beliefs? This research found a broad social spread of ghost belief. The circulation of ghost narratives takes place within social groups defined in part by their seriousness about the discussion. This does not preclude jokes, disagreements or the discrediting of specific events, so long as the discussion considers ghosts attentively and seriously. Informants brought a sophisticated range of influences to bear on narratives and their interpretation, including some scientific knowledge and understanding. Informants discussed a broad range of phenomena within a consideration of ‘ghosts’: there is no easy correlation of a narrator’s interpretation and the kind of manifestation being described. Some accounts were related as polished stories, but this did not impact directly on their belief content. The interrelationship between oral narrative and artistic representation highlights the shaping and exchange of stories to accommodate belief content. This ability to adjust between apparently different registers of discussion also illustrates how ghost beliefs fit the structures of other, more institutional, belief systems held by informants. A key finding, considering sociological discussions of secularisation and historiographical associations of heterodox beliefs with political radicalism, is that personal folk beliefs are slower developing and more conservative than institutional forms, which respond more quickly to socio-economic changes. Immediate institutional responses to changed conditions may not, therefore, correlate directly with a corresponding change in ghost belief.

In the United States, Christmastime has become a time of tension between the holy ideals of family togetherness, childhood innocence, and goodwill towards men and commercial idolatry. Christ and Santa Claus are pitted against each other in the war on Christmas between religion and secularism instead of feasting together on ham and figgy pudding in the traditional fashion. While many would agree that the everyday realities of the Christmas season do not often live up to the ideals imposed upon the holiday, few are able to tell why this is so or even trace the roots of their discontent. In an exploration of the unique anomaly of the hierosecular American Christmas, I propose that the unique systems of Christmas belief extend beyond the usual boundaries of sacred and secular to create a complex web of different beliefs that are performed together to create the unique feeling of Christmas. From a performance theory perspective, I use performance as both traditionally theatrical and as a paradigm for understanding and expressing belief in an effort to explore the essential but elusively defined cultural signifiers of the American Christmas. Through a series of case studies focusing on various traditions of Christmas performance, I apply the performance theories of Diana Taylor, Patrice Pavis, Victor Turner and others to such Christmas staples as Charles Dickens' A Christmas Carol and Tchaikovsky's The Nutcracker. In doing so, I propose different points for viewing Christmas and introducing new points of inquiry for questioning the meaning of Christmas, belief, and performance.
M.A.
Masters
Theatre
Arts and Humanities
Theatre

Dans cette thèse, nous proposons des modèles logiques pour la représentation des croyances et leur changement dans un cadre multi-agent, en insistant sur l'importance de se fixer un point de vue particulier pour la modélisation. A cet égard, nous distinguons deux approches différentes: l'approche externe, où le modélisateur est quelqu'un d'externe à la situation; l'approche interne, où le modélisateur est l'un des agents. Nous proposons une version interne de la logique épistémique dynamique (avec des modèles d'événements), ce qui nous permet de généraliser facilement la théorie de la révision des croyances d'AGM au cas multi-agent. Ensuite, nous mod´elisons les dynamismes logiques complexes qui soustendent notre interprétation des événements en introduisant des probabilités et des infinitésimaux. Finalement, nous proposons un formalisme alternatif qui n'utilise pas de modèle d'événement mais qui introduit à la place un opérateur d'événement inverse.

The capability of changing beliefs upon new information in a rational and efficient way is crucial for an intelligent agent. Belief change therefore is one of the central research fields in Artificial Intelligence (AI) for over two decades. In the AI literature, two different kinds of belief change operations have been intensively investigated: belief update, which deal with situations where the new information describes changes of the world; and belief revision, which assumes the world is static. As another important research area in AI, reasoning about actions mainly studies the problem of representing and reasoning about effects of actions. These two research fields are closely related and apply a common underlying principle, that is, an agent should change its beliefs (knowledge) as little as possible whenever an adjustment is necessary. This lays down the possibility of reusing the ideas and results of one field in the other, and vice verse. This thesis aims to develop a general framework and devise computational models that are applicable in reasoning about actions. Firstly, I shall propose a new framework for iterated belief revision by introducing a new postulate to the existing AGM/DP postulates, which provides general criteria for the design of iterated revision operators. Secondly, based on the new framework, a concrete iterated revision operator is devised. The semantic model of the operator gives nice intuitions and helps to show its satisfiability of desirable postulates. I also show that the computational model of the operator is almost optimal in time and space-complexity. In order to deal with the belief change problem in multi-agent systems, I introduce a concept of mutual belief revision which is concerned with information exchange among agents. A concrete mutual revision operator is devised by generalizing the iterated revision operator. Likewise, a semantic model is used to show the intuition and many nice properties of the mutual revision operator, and the complexity of its computational model is formally analyzed. Finally, I present a belief update operator, which takes into account two important problems of reasoning about action, i.e., disjunctive updates and domain constraints. Again, the updated operator is presented with both a semantic model and a computational model.

The aim of this dissertation is to provide a non-Fregean account of the functioning of belief attributions (BA's), specifically those of the form 'B believes that Fa' where 'a' is a proper name, which provides a satisfactory account of the phenomena associated with the substitution of co-referential names and with the use of vacuous names. After an intitial study of non-Fregean theories of reference, specifically those of Kripke, Kaplan and Donnellan in which Kaplan's introduction of content, of the singular proposition, is found to be necessary, an examination of certain proposed solutions for BA's, compatable with direct reference, is carried out. These proposals, namely those of Quine, Perry and Nathan Salmon, are all found wanting, the latter two due to their being, ultimately, Fregean. A non-Fregean approach is initiated beginning with an examination of our actual practices in using BA's. It is found that very different information can be conveyed by the use of the same sentence in the same context. While this differing information cannot be captured by means of the proposition expressed, it can be captured by treating the BA as an answer to a question. Belnap's logic of questions and answers is then developed to encompass vacuous terms and, with this in place, two distinct uses of BA's emerge. In one, the BA is used to provide a direct answer to the question; in the other it is used in order to modify the claim to truth of the embedded proposition, to provide a tentative answer. Problematic cases of BA's are then examined. It is found that substitution in all cases is permissible. Supposed difficulties with this position in the area of belief itself and with the explanation of action are discussed and resolved, the latter partly by means of the development and application of an account of 'why' questions and answers. The use of vacuous names is then investigated and a difference noted between cases in which the BA is used to provide a tentative answer and those in which it constitutes a direct answer. In the former case, the use of a vacuous name results in no answer being given. However, given the nature of tentative answers, no problems specific to belief attributions are generated in such cases. In order to deal with cases where the vacuous name occurs in a BA asserted as a direct answer, Evans' account of pretend games is invoked, though modified to permit a possible world account of counterfactuals.
Arts, Faculty of
Philosophy, Department of
Graduate

This thesis is about logical models of belief (and knowledge) representation and belief change. This means that we propose logical systems which are intended to represent how agents perceive a situation and reason about it, and how they update their beliefs about this situation when events occur. These agents can be machines, robots, human beings. . . but they are assumed to be somehow autonomous. The way a fixed situation is perceived by agents can be represented by statements about the agents� beliefs: for example �agent A believes that the door of the room is open� or �agent A believes that her colleague is busy this afternoon�. �Logical systems� means that agents can reason about the situation and their beliefs about it: if agent A believes that her colleague is busy this afternoon then agent A infers that he will not visit her this afternoon. We moreover often assume that our situations involve several agents which interact between each other. So these agents have beliefs about the situation (such as �the door is open�) but also about the other agents� beliefs: for example agent A might believe that agent B believes that the door is open. These kinds of beliefs are called higher-order beliefs. Epistemic logic [Hintikka, 1962; Fagin et al., 1995; Meyer and van der Hoek, 1995], the logic of belief and knowledge, can capture all these phenomena and will be our main starting point to model such fixed (�static�) situations. Uncertainty can of course be expressed by beliefs and knowledge: for example agent A being uncertain whether her colleague is busy this afternoon can be expressed by �agent A does not know whether her colleague is busy this afternoon�. But we sometimes need to enrich and refine the representation of uncertainty: for example, even if agent A does not know whether her colleague is busy this afternoon, she might consider it more probable that he is actually busy. So other logics have been developed to deal more adequately with the representation of uncertainty, such as probabilistic logic, fuzzy logic or possibilistic logic, and we will refer to some of them in this thesis (see [Halpern, 2003] for a survey on reasoning about uncertainty). But things become more complex when we introduce events and change in the picture. Issues arise even if we assume that there is a single agent. Indeed, if the incoming information conveyed by the event is coherent with the agent�s beliefs then the agent can just add it to her beliefs. But if the incoming information contradicts the agent�s beliefs then the agent has somehow to revise her beliefs, and as it turns out there is no obvious way to decide what should be her resulting beliefs. Solving this problem was the goal of the logic-based belief revision theory developed by Alchourrón, Gärdenfors and Makinson (to which we will refer by the term AGM) [Alchourrón et al., 1985; Gärdenfors, 1988; Gärdenfors and Rott, 1995]. Their idea is to introduce �rationality postulates� that specify which belief revision operations can be considered as being �rational� or reasonable, and then to propose specific revision operations that fulfill these postulates. However, AGM does not consider situations where the agent might also have some uncertainty about the incoming information: for example agent A might be uncertain due to some noise whether her colleague told her that he would visit her on Tuesday or on Thursday. In this thesis we also investigate this kind of phenomenon. Things are even more complex in a multi-agent setting because the way agents update their beliefs depends not only on their beliefs about the event itself but also on their beliefs about the way the other agents perceived the event (and so about the other agents� beliefs about the event). For example, during a private announcement of a piece of information to agent A the beliefs of the other agents actually do not change because they believe nothing is actually happening; but during a public announcement all the agents� beliefs might change because they all believe that an announcement has been made. Such kind of subtleties have been dealt with in a field called dynamic epistemic logic (Gerbrandy and Groeneveld, 1997; Baltag et al., 1998; van Ditmarsch et al., 2007b]. The idea is to represent by an event model how the event is perceived by the agents and then to define a formal update mechanism that specifies how the agents update their beliefs according to this event model and their previous representaton of the situation. Finally, the issues concerning belief revision that we raised in the single agent case are still present in the multi-agent case. So this thesis is more generally about information and information change. However, we will not deal with problems of how to store information in machines or how to actually communicate information. Such problems have been dealt with in information theory [Cover and Thomas, 1991] and Kolmogorov complexity theory [Li and Vitányi, 1993]. We will just assume that such mechanisms are already available and start our investigations from there. Studying and proposing logical models for belief change and belief representation has applications in several areas. First in artificial intelligence, where machines or robots need to have a formal representation of the surrounding world (which might involve other agents), and formal mechanisms to update this representation when they receive incoming information. Such formalisms are crucial if we want to design autonomous agents, able to act autonomously in the real world or in a virtual world (such as on the internet). Indeed, the representation of the surrounding world is essential for a robot in order to reason about the world, plan actions in order to achieve goals... and it must be able to update and revise its representation of the world itself in order to cope autonomously with unexpected events. Second in game theory (and consequently in economics), where we need to model games involving several agents (players) having beliefs about the game and about the other agents� beliefs (such as agent A believes that agent B has the ace of spade, or agent A believes that agent B believes that agent A has the ace of heart...), and how they update their representation of the game when events (such as showing privately a card or putting a card on the table) occur. Third in cognitive psychology, where we need to model as accurately as possible epistemic state of human agents and the dynamics of belief and knowledge in order to explain and describe cognitive processes. The thesis is organized as follows. In Chapter 2, we first recall epistemic logic. Then we observe that representing an epistemic situation involving several agents depends very much on the modeling point of view one takes. For example, in a poker game the representation of the game will be different depending on whether the modeler is a poker player playing in the game or the card dealer who knows exactly what the players� cards are. In this thesis, we will carefully distinguish these different modeling approaches and the. different kinds of formalisms they give rise to. In fact, the interpretation of a formalism relies quite a lot on the nature of these modeling points of view. Classically, in epistemic logic, the models built are supposed to be correct and represent the situation from an external and objective point of view. We call this modeling approach the perfect external approach. In Chapter 2, we study the modeling point of view of a particular modeler-agent involved in the situation with other agents (and so having a possibly erroneous perception of the situation). We call this modeling approach the internal approach. We propose a logical formalism based on epistemic logic that this agent uses to represent �for herself� the surrounding world. We then set some formal connections between the internal approach and the (perfect) external approach. Finally we axiomatize our logical formalism and show that the resulting logic is decidable. In Chapter 3, we first recall dynamic epistemic logic as viewed by Baltag, Moss and Solecki (to which we will refer by the term BMS). Then we study in which case seriality of the accessibility relations of epistemic models is preserved during an update, first for the full updated model and then for generated submodels of the full updated model. Finally, observing that the BMS formalism follows the (perfect) external approach, we propose an internal version of it, just as we proposed an internal version of epistemic logic in Chapter 2. In Chapter 4, we still follow the internal approach and study the particular case where the event is a private announcement. We first show, thanks to our study in Chapter 3, that in a multi-agent setting, expanding in the AGM style corresponds to performing a private announcement in the BMS style. This indicates that generalizing AGM belief revision theory to a multi-agent setting amounts to study private announcement. We then generalize the AGM representation theorems to the multi-agent case. Afterwards, in the spirit of the AGM approach, we go beyond the AGM postulates and investigate multi-agent rationality postulates specific to our multi-agent setting inspired from the fact that the kind of phenomenon we study is private announcement. Finally we provide an example of revision operation that we apply to a concrete example. In Chapter 5, we follow the (perfect) external approach and enrich the BMS formalism with probabilities. This enables us to provide a fined-grained account of how human agents interpret events involving uncertainty and how they revise their beliefs. Afterwards, we review different principles for the notion of knowledge that have been proposed in the literature and show how some principles that we argue to be reasonable ones can all be captured in our rich and expressive formalism. Finally, we extend our general formalism to a multi-agent setting. In Chapter 6, we still follow the (perfect) external approach and enrich our dynamic epistemic language with converse events. This language is interpreted on structures with accessibility relations for both beliefs and events, unlike the BMS formalism where events and beliefs are not on the same formal level. Then we propose principles relating events and beliefs and provide a complete characterization, which yields a new logic EDL. Finally, we show that BMS can be translated into our new logic EDL thanks to the converse operator: this device enables us to translate the structure of the event model directly within a particular axiomatization of EDL, without having to refer to a particular event model in the language (as done in BMS). In Chapter 7 we summarize our results and give an overview of remaining technical issues and some desiderata for future directions of research. Parts of this thesis are based on publication, but we emphasize that they have been entirely rewritten in order to make this thesis an integrated whole. Sections 4.2.2 and 4.3 of Chapter 4 are based on [Aucher, 2008]. Sections 5.2, 5.3 and 5.5 of Chapter 5 are based on [Aucher, 2007]. Chapter 6 is based on [Aucher and Herzig, 2007].