Bayesian Reasoning

Bas van Fraassen has argued that explanatory reasoning does not provide confirmation for explanatory hypotheses because explanatory reasoning increases information and increasing information does not provide confirmation. We compare this argument with a skeptical argument that one should never add any beliefs because adding beliefs increases information and increasing information does not provide confirmation. We discuss the similarities between these two arguments and identify several problems with van Fraassen’s argument.

This article reviews and develops an epistemological tradition in philosophy of science, called convergentism, which holds that inference methods should be assessed in terms of their abilities to converge to the truth. This tradition is compared with three competing ones: (1) explanationism, which holds that theory choice should be guided by a theory's overall balance of explanatory virtues, such as simplicity and fit with data; (2) instrumentalism, according to which scientific inference should be driven by the goal of obtaining useful (...) models, rather than true theories; (3) Bayesianism, which features a shift of focus from all-or-nothing beliefs to degrees of belief. (shrink)

The material conditional and the suppositional analysis of the indicative conditional are based on different philosophical foundations and they leave important successes of their competitor unexplained. This paper unifies both accounts within a truth-functional, trivalent model of the suppositional analysis. In this model, we observe that the material and the suppositional conditional exhibit the same logical behavior while they have different truth conditions and different probabilities. The result is a unified semantic analysis that closes an important gap in the suppositional (...) story and explains the persistent appeal of the material conditional analysis for philosophers and psychologists of reasoning. (shrink)

Standard arguments for Bayesian conditionalizing rely on assumptions that many epistemologists have criticized as being too strong: (i) that conditionalizers must be logically infallible, which rules out the possibility of rational logical learning, and (ii) that what is learned with certainty must be true (factivity). In this paper, we give a new factivity-free argument for the superconditionalization norm in a personal possibility framework that allows agents to learn empirical and logical falsehoods. We then discuss how the resulting framework should be (...) interpreted. Does it still model norms of rationality, or something else, or nothing useful at all? We discuss five ways of interpreting our results, three that embrace them and two that reject them. We find one of each kind wanting, and leave readers to choose among the remaining three. (shrink)

Ambiguity occurs insofar as a reasoner lacks information about the relevant physical probabilities. There are objections to the application of standard Bayesian inductive logic and decision theory in contexts of significant ambiguity. A variety of alternative frameworks for reasoning under ambiguity have been proposed. Two of the most prominent are Imprecise Bayesianism and Dempster–Shafer theory. We compare these inductive logics with respect to the Ambiguity Dilemma, which is a problem that has been raised for Imprecise Bayesianism. We develop an agent-based (...) model comparison that isolates the difference between the two inductive logics in their updating methods. We find that Dempster–Shafer theory does not avoid the Ambiguity Dilemma. We discuss the implications of this result. (shrink)

We give a Bayesian argument showing that, even if your total empirical evidence confirms that you have zillions of duplicate Boltzmann Brains, that evidence does not confirm that you are a Boltzmann Brain. We also try to explain what goes wrong with several of the sources of the temptation for thinking that such evidence does have skeptical implications.

Many philosophers have been attracted to a restricted version of the principle of indifference in the case of self‐locating belief. Roughly speaking, this principle states that, within any given possible world, one should be indifferent between different hypotheses concerning who one is within that possible world, so long as those hypotheses are compatible with one's evidence. My first goal is to defend a more precise version of this principle. After responding to several existing criticisms of such a principle, I argue (...) that existing formulations of the principle are crucially ambiguous, and I go on to defend a particular disambiguation of the principle. According to the disambiguation I defend, how we should apply this restricted principle of indifference sensitively depends on our background metaphysical beliefs. My second goal is to apply this disambiguated principle to classical skeptical problems in epistemology. In particular, I argue that Eternalism threatens to lead us to external world skepticism, and Modal Realism threatens to lead us to inductive skepticism. (shrink)

Mới đây, phương pháp phân tích BMF (Bayesian Mindsponge Framework) do các nhà khoa học Việt Nam phát triển đang được triển khai ở Đại học Pretoria (Nam Phi). Đáng chú ý, việc phát triển tiếp các ứng dụng của phương pháp có xuất xứ từ Việt Nam lại được thực hiện bởi một nhà nghiên cứu trẻ tại Đại học Công giáo Widya Mandala Surabaya của Indonesia, tên là Ni Putu Wulan Purnama Sari.

Katie Steele and H. Orri Stefánsson argue that, to reflect an agent’s limited awareness, the algebra of propositions on which that agent’s credences are defined should be relativised to their awareness state. I argue that this produces insurmountable difficulties. But the project of relativising the agent’s algebra to reflect their partial perspective need not be abandoned: the algebra can be relativised, not to the agent’s awareness state, but to what we might call their subjective modality.

Our universe seems to be miraculously fine-tuned for life. Multiverse theories have been proposed as an explanation for this on the basis of probabilistic arguments, but various authors have objected that we should consider our total evidence that this universe in particular has life in our inference, which would block the argument. The debate thus crucially hinges on how Bayesian background and evidence are distinguished and on how indexical or demonstrative terms are analysed. The aim of this article is to (...) take a step back and examine these various aspects of Bayesian reasoning and how they affect the arguments. The upshot is that there are reasons to resist the fine-tuning argument for the multiverse, but the “this-universe-objection” is not one of them. (shrink)

Chỉ còn một vài ngày nữa cả nước ta sẽ đón chào ngày lễ Quốc tế Lao động 1/5. Sẽ thật ý nghĩa khi ta kiểm đếm và nhìn lại các tác động và giá trị của thành quả lao động trước đây, để từ đó tạo động lực cùng hướng tới tương lai hăng say lao động.

Many philosophers of theistic religions claim (1) that there are powerful a posteriori arguments for God’s existence that make it rational to believe that He exists and at the same time maintain (2) that God always has the freedom to do otherwise. In this article, I argue that these two positions are inconsistent because the empirical evidence on which the a posteriori arguments for God’s existence rest can be explained better by positing the existence of a God-like being without the (...) freedom to do otherwise. (shrink)

Many philosophers in the field of meta-ethics believe that rational degrees of confidence in moral judgments should have a probabilistic structure, in the same way as do rational degrees of belief. The current paper examines this position, termed “moral Bayesianism,” from an empirical point of view. To this end, we assessed the extent to which degrees of moral judgments obey the third axiom of the probability calculus, ifP(A∩B)=0thenP(A∪B)=P(A)+P(B), known as finite additivity, as compared to degrees of beliefs on the one (...) hand and degrees of desires on the other. Results generally converged to show that degrees of moral judgment are more similar to degrees of belief than to degrees of desire in this respect. This supports the adoption of a Bayesian approach to the study of moral judgments. To further support moral Bayesianism, we also demonstrated its predictive power. Finally, we discuss the relevancy of our results to the meta-ethical debate between moral cognitivists and moral non-cognitivists. (shrink)

My dissertation is about Bayesian rationality for non-ideal agents. I show how to derive subjective probabilities from preferences using much weaker rationality assumptions than other standard representation theorems. I argue that non-ideal agents might be uncertain about how they will update on new information and consider two consequences of this uncertainty: such agents should sometimes reject free information and make choices which, taken together, yield sure loss. The upshot is that Bayesian rationality for non-ideal agents makes very different normative demands (...) than ideal Bayesian rationality. (shrink)

This article aims to provide an a posteriori argument for the veracity of the Christian conception of the Abrahamic religion that centres on God’s action of sending a divine and atoning prophet—the ‘Messianic Prophet’—into the world, who we can identify as the person of Jesus of Nazareth. This specific argument will be presented through Richard Swinburne’s (modified) explanatory framework, which focuses on assessing the prior and posterior evidence in support of this identification. This, however, will be done in light of (...) the work of Historical Jesus and NT scholars John P. Meier, N.T. Wright, Richard Bauckham and Larry Hurtado—which, in combination, will provide a means to ward off two important objections against Swinburne's methodology, and ultimately allow one to establish the veracity of the ‘Christian Position’, on firm historical grounds. (shrink)

In this paper we explore the absentminded driver problem using two different scenarios. In the first scenario we assume that the driver is capable of reasoning about his degree of absentmindedness before he hits the highway. This leads to a Savage-style model where the states are mutually exclusive and the act-state independence is in place. In the second we employ centred possibilities, by modelling the states (i.e. the events about which the driver is uncertain) as the possible final destinations indexed (...) by a time period. The optimal probability we find for continuing at an exit is different from almost all papers in the literature. In this scenario, act-state independence is still violated, but states are mutually exclusive and the driver arrives at his optimal choice probability via Bayesian updating. We show that our solution is the only one guaranteeing immunity from sure loss via a Dutch strategy, and that – despite initial appearances – it is time consistent. This raises important implications for the rationality of commitment in such scenarios. (shrink)

In situations where we ignore everything but the space of possibilities, we ought to suspend judgment—that is, remain agnostic—about which of these possibilities is the case. This means that we cannot sum our degrees of belief in different possibilities, something that has been formalized as an axiom of non-additivity. Consistent with this way of representing our ignorance, I defend a doxastic norm that recommends that we should nevertheless follow a certain additivity of possibilities: even if we cannot sum degrees of (...) belief in different possibilities, we should be more confident in larger groups of possibilities. It is thus shown that, in the type of situation considered (in so-called ‘classical ignorance’, i.e. “behind a thin veil of ignorance”), it is epistemically rational for advocates of suspending judgment to endorse this comparative confidence; while on the other hand it is shown that, even in classical ignorance, no stronger belief—such as a precise uniform probability distribution—is warranted. (shrink)

Cuốn tài liệu học thuật trình bày phương pháp “BMF analytics” hiện đã bước sang năm thứ ba phục vụ cộng đồng nghiên cứu. Cuốn sách đã góp phần hỗ trợ nhiều nhà nghiên cứu trẻ triển khai và hoàn thành công việc.

The methodology title on BMF analytics is now in its third year of service to our research community, enabling many researchers to implement their research pursuits.

Đến khúc này, 3 ông bói cá cũng bí nên chuyển chủ đề. Hướng sang vấn đề ăn cá vậy. Đây là vấn đề truyền thống lâu đời. Có chuyện gì lớn?

This paper generalizes the preface paradox beyond the conjunctive aggregation of beliefs and constructs an analogous paradox for deontic reasoning. The analysis of the deontic case suggests a systematic restriction of intuitive rules for reasoning with obligations. This proposal can be transferred to the epistemic case: it avoids the preface and the lottery paradox and saves one of the two directions of the Lockean Thesis (i.e., high credence is sufficient, but not necessary for rational belief). The resulting account compares favorably (...) to competing proposals; in particular, we can formulate the rules of correct doxastic reasoning without reference to probabilistic features of the involved propositions. (shrink)

The persistence of “stargazing,” p-hacking and HARKing4 are among the main causes for the severity of the irreproducibility problem in social sciences.

The gambler’s fallacy is the tendency to expect random processes to switch more often than they actually do—for example, to think that after a string of tails, a heads is more likely. It’s often taken to be evidence for irrationality. It isn’t. Rather, it’s to be expected from a group of Bayesians who begin with causal uncertainty, and then observe unbiased data from an (in fact) statistically independent process. Although they converge toward the truth, they do so in an asymmetric (...) way—ruling out “streaky” hypotheses more quickly than “switchy” ones. As a result, the majority (and the average) exhibit the gambler’s fallacy. If they have limited memory, this tendency persists even with arbitrarily-large amounts of data. Indeed, such Bayesians exhibit a variety of the empirical trends found in studies of the gambler’s fallacy: they expect switches after short streaks but continuations after long ones; these nonlinear expectations vary with their familiarity with the causal system; their predictions depend on the sequence they’ve just seen; they produce sequences that are too switchy; and they exhibit greater rates of gambler’s reasoning when forming binary predictions than when forming probability estimates. In short: what’s been thought to be evidence for irrationality may instead be rational responses to limited data and memory. (shrink)

Trưa ngày 1-1 năm mới, R Documentation cho biết mức downloads tạm tính của chương trình bayesvl trong tháng 12-2023. Hiện đang đứng ở mức 157, tháng thấp nhất trong năm.

There are two distinct approaches to Bayesian modelling in cognitive science. Black-box approaches use Bayesian theory to model the relationship between the inputs and outputs of a cognitive system without reference to the mediating causal processes; while mechanistic approaches make claims about the neural mechanisms which generate the outputs from the inputs. This paper concerns the relationship between these two approaches. We argue that the dominant trend in the philosophical literature, which characterizes the relationship between black-box and mechanistic approaches to (...) Bayesian cognitive science in terms of the dichotomy between instrumentalism and realism, is misguided. We propose that the two distinctions are orthogonal: black-box and mechanistic approaches to Bayesian modelling can each be given either an instrumentalist or a realist interpretation. We argue that the current tendency to conflate black-box approaches with instrumentalism and mechanistic approaches with realism stems from unwarranted assumptions about the nature of scientific explanation, the ontological commitments of scientific theories, and the role of abstraction and idealization in scientific models. We challenge each of these assumptions to reframe the debates over Bayesian modelling in cognitive science. (shrink)

Từ thực tế dữ liệu, có thể thấy nếu như mức độ quan tâm ứng dụng thực sự của BMF analytics cho công việc trở nên phổ biến, thì khả năng bayesvl sẽ được tải về và sử dụng sẽ có nhiều cơ hội để cải thiện.

On November 3 and 4, 2023, Dr. Nguyen Minh Hoang (Phenikaa University), co-author of the BMF Analytics [1], gave a lecture on computational approaches using bayesvl and BMF application for social science research.

TS. Nguyễn Minh Hoàng (ĐH Phenikaa), đã giảng bài về tiếp cận tính toán sử dụng bayesvl và ứng dụng BMF cho công việc nghiên cứu KHXH.

Slurs’ meaning is highly unstable. A slurring utterance like ‘Hey, F, where have you been?’ (where F is a slur) may receive a wide array of interpretations depending on various contextual factors such as the speaker’s social identity, their relationship to the target group, tone of voice, and more. Standard semantic, pragmatic, and non-content theories of slurs have proposed different mechanisms to account for some or all types of variability observed, but without providing a unified framework that allows us to (...) understand how different contextual factors simultaneously influence slurs’ interpretation. To address this issue, I argue that slurs convey dimensional qualities such as, e.g., ‘negative valence, neutral arousal, high dominance’ instead of discrete emotional categories such as ‘contempt’. Then, I translate this hypothesis into a game-theoretic model of slurs’ interpretation inspired by Heather Burnett’s pioneering work on identity construction. This new model, called ‘Affective Meaning Games’ (AMG), captures the variability of slurs and integrates pragmatic reasoning within an independently motivated psychological understanding of emotional states. (shrink)

This paper presents a unified theory of the truth conditions and probability of indicative conditionals and their compounds in a trivalent framework. The semantics validates a Reduction Theorem: any compound of conditionals is semantically equivalent to a simple conditional. This allows us to validate Stalnaker's Thesis in full generality and to use Adams's notion of $p$-validity as a criterion for valid inference. Finally, this gives us an elegant account of Bayesian update with indicative conditionals, establishing that despite differences in meaning, (...) it is tantamount to learning a material conditional. (shrink)

Is more information always better? Or are there some situations in which more information can make us worse off? Good (1967) argues that expected utility maximizers should always accept more information if the information is cost-free and relevant. But Good's argument presupposes that you are certain you will update by conditionalization. If we relax this assumption and allow agents to be uncertain about updating, these agents can be rationally required to reject free and relevant information. Since there are good reasons (...) to be uncertain about updating, rationality can require you to prefer ignorance. (shrink)

Bayesianism can be characterized as the following twofold position: (i) rational credences obey the probability calculus; (ii) rational learning, i.e., the updating of credences, is regulated by some form of conditionalization. While the formal aspect of various forms of conditionalization has been explored in detail, the philosophical application to learning from experience is still deeply problematic. Some philosophers have proposed to revise the epistemology of perception; others have provided new formal accounts of conditionalization that are more in line with how (...) we learn from perceptual experience. The current investigation argues that Bayesian epistemology is still incomplete; the epistemology of perception and the epistemology of rational reasoning have not been reconciled. (shrink)

The "myside bias'' in evaluating arguments is an empirically well-confirmed phenomenon that consists of overweighting arguments that endorse one's beliefs or attack alternative beliefs while underweighting arguments that attack one's beliefs or defend alternative beliefs. This paper makes two contributions: First, it proposes a probabilistic model that adequately captures three salient features of myside bias in argument evaluation. Second, it provides a Bayesian justification of this model, thus showing that myside bias has a rational Bayesian explanation under certain conditions.

Alongside science and law, argumentation is also of central importance in everyday life. But what characterizes a good argument? This question has occupied philosophers and psychologists for centuries. The theory of Bayesian argumentation is particularly suitable for clarifying it, because it allows us to take into account in a natural way the role of uncertainty, which is central to much argumentation. Moreover, it offers the possibility of measuring the strength of an argument in probabilistic terms. One way to do this, (...) implicit in much work, is to identify the strength of an argument with the degree to which the premises of the argument confirm the conclusion. We criticize this prima facie plausible proposal and suggest instead that the strength of an argument has something to do with how much the premises and the conclusion of the argument cohere with each other. This leads to a new probabilistic measure whose properties we examine in more detail. (shrink)

Cao điểm bayesvl chỉ có rau... -/- Người ta bẩu, ăn thịt/cá mới đủ protein để phục vụ suy nghĩ.

An untold aspect of the inexpensiveness of bayesvl was that its developers also ate very little, mostly vegetables.

Như vậy, tổng lượng downloads của bayesvl bản 0.8.5 từ các servers CRAN giai đoạn tháng 7-2021 tới tháng 6-2023 đạt 7930. (Số thống kê này không bao gồm lượng downloads từ Github, như đã nêu trên.).

The orgulity objection of Belot (2013) is recast in the form of a decision problem.

We aim to support researchers in social sciences and humanities in conducting and publishing their studies on a global scale, especially Early Career Researchers (ECRs) and those in low-resource settings. For that purpose, AISDL created the Science Portal for the Serendipity-Mindsponge-3D (SM3D) Knowledge Management Theory.

La, V. P., & Vuong, Q. H. (2019). bayesvl: Visually learning the graphical structure of Bayesian networks and performing MCMC with ‘Stan’. The Comprehensive R Archive Network (CRAN).

In this paper, we ask: how should an agent who has incoherent credences update when they learn new evidence? The standard Bayesian answer for coherent agents is that they should conditionalize; however, this updating rule is not defined for incoherent starting credences. We show how one of the main arguments for conditionalization, the Dutch strategy argument, can be extended to devise a target property for updating plans that can apply to them regardless of whether the agent starts out with coherent (...) or incoherent credences. The main idea behind this extension is that the agent should avoid updating plans that increase the possible sure loss from Dutch strategies. This happens to be equivalent to avoiding updating plans that increase incoherence according to a distance-based incoherence measure. (shrink)

In response to two trenchant objections, radical subjective Bayesianism has been widely rejected. In this paper, I seek, if not to rehabilitate subjectivism, at least to show its critic what is attractive about the position. I argue that what is at stake in the subjectivism/anti-subjectivism debate is not, as is commonly thought, which norms of rationality are true, but rather, the conception of rationality that we adopt: there is an alternative approach to the widespread telic approach to rationality, which I (...) call the poric approach, on which subjectivism is an attractive position. I then argue that the poric approach—and therefore subjectivism—cannot be easily dismissed. (shrink)

Awareness growth—coming to entertain propositions of which one was previously unaware—is a crucial aspect of epistemic thriving. And yet, it is widely believed that orthodox Bayesianism cannot accommodate this phenomenon, since that would require employing supposedly defective catch-all propositions. Orthodox Bayesianism, it is concluded, must be amended. In this paper, I show that this argument fails, and that, on the contrary, the orthodox version of Bayesianism is particularly well-suited to accommodate awareness growth. For it entails what I call the refinement (...) view, which allows us to capture that awareness growth consists in the increase of one’s capacity of discernment. (shrink)

In Being You, Anil Seth takes us on a comprehensive tour through the science of consciousness, drawing on the most up-to-date data, lessons and theories in the field. This is a compelling book that will leave readers pondering whether new technologies and smart experimental designs will further deepen our understanding of the mind, writes Manh Tung Ho.

There is a tension for those who want to simultaneously hold that Abraham’s disposition to sacrifice Isaac is epistemically justified and yet hold that a contemporary father would not be justified in believing that God is commanding him to sacrifice his son. This paper attempts to resolve that tension. While some commentators have correctly pointed out that one must take Abraham’s long relationship with God into account when considering Abraham’s readiness to sacrifice his son, they do not entertain the possibility (...) that his hearing this commandment is evidence against the hypothesis that Abraham is speaking to God. I grant this possibility. But I argue that when God commands Abraham to do the unthinkable, Abraham’s previously acquired evidence could still be sufficient to justify his belief that he is speaking with God. And in making this argument, I attempt to show what differentiates Abraham from the contemporary father who thinks that God is commanding him to sacrifice his son. (shrink)

It is a consequence of the theory of imprecise credences that there exist situations in which rational agents inevitably become less opinionated toward some propositions as they gather more evidence. The fact that an agent's imprecise credal state can dilate in this way is often treated as a strike against the imprecise approach to inductive inference. Here, we show that dilation is not a mere artifact of this approach by demonstrating that opinion loss is countenanced as rational by a substantially (...) broader class of normative theories than has been previously recognised. Specifically, we show that dilation-like phenomena arise even when one abandons the basic assumption that agents have (precise or imprecise) credences of any kind, and follows directly from bedrock norms for rational comparative confidence judgements of the form `I am at least as confident in p as I am in q'. We then use the comparative confidence framework to develop a novel understanding of what exactly gives rise to dilation-like phenomena. By considering opinion loss in this more general setting, we are able to provide a novel assessment of the prospects for an account of inductive inference that is not saddled with the inevitability of rational opinion loss. (shrink)

Bayesians often appeal to “merging of opinions” to rebut charges of excessive subjectivity. But what happens in the short run is often of greater interest than what happens in the limit. Seidenfeld and coauthors use this observation as motivation for investigating the counterintuitive short run phenomenon of dilation, since, they allege, dilation is “the opposite” of asymptotic merging of opinions. The measure of uncertainty relevant for dilation, however, is not the one relevant for merging of opinions. We explicitly investigate the (...) short run behavior of the metric relevant for merging, and show that dilation is independent of the opposite of merging. (shrink)

In a recent paper, Pettigrew reports a generalization of the celebrated accuracy-dominance theorem due to Predd et al., but Pettigrew’s proof is incorrect. I will explain the mistakes and provide a correct proof.

We are often justified in acting on the basis of evidential confirmation. I argue that such evidence supports belief in non-quantificational generic generalizations, rather than universally quantified generalizations. I show how this account supports, rather than undermines, a Bayesian account of confirmation. Induction from confirming instances of a generalization to belief in the corresponding generic is part of a reasoning instinct that is typically (but not always) correct, and allows us to approximate the predictions that formal epistemology would make.