An Abductive Question-Answer System for the Minimal Logic of Formal Inconsistency $$\mathsf {mbC}$$ mbC

Studia Logica - The aim in this paper is to define an Abductive Question-Answer System for the minimal logic of formal inconsistency $$\mathsf {mbC}$$ . As a proof-theoretical basis we employ the...     

Abductive reasoning in neural-symbolic systems

Abduction is or subsumes a process of inference. It entertains possible hypotheses and it chooses hypotheses for further scrutiny. There is a large literature on various aspects of non-symbolic, subconscious abduction. There is also a very active research community working on the symbolic (logical) characterisation of abduction, which typically treats it as a form of hypothetico-deductive reasoning. In this paper we start to bridge the gap between the symbolic and sub-symbolic approaches to abduction. We are interested in benefiting from developments made by each community. In particular, we are interested in the ability of non-symbolic systems (neural networks) to learn from experience using efficient algorithms and to perform massively parallel computations of alternative abductive explanations. At the same time, we would like to benefit from the rigour and semantic clarity of symbolic logic. We present two approaches to dealing with abduction in neural networks. One of them uses Connectionist Modal Logic and a translation of Horn clauses into modal clauses to come up with a neural network ensemble that computes abductive explanations in a top-down fashion. The other combines neural-symbolic systems and abductive logic programming and proposes a neural architecture which performs a more systematic, bottom-up computation of alternative abductive explanations. Both approaches employ standard neural network architectures which are already known to be highly effective in practical learning applications. Differently from previous work in the area, our aim is to promote the integration of reasoning and learning in a way that the neural network provides the machinery for cognitive computation, inductive learning and hypothetical reasoning, while logic provides the rigour and explanation capability to the systems, facilitating the interaction with the outside world. Although it is left as future work to determine whether the structure of one of the proposed approaches is more amenable to learning than the other, we hope to have contributed to the development of the area by approaching it from the perspective of symbolic and sub-symbolic integration.

The Effect of Intuitive Advice Justification on Advice Taking

How do you respond when receiving advice from somebody with the argumentation “my gut tells me so” or “this is what my intuition says”? Most likely, you would find this justification insufficient and disregard the advice. Are there also situations where people do appreciate such intuitive advice and change their opinion accordingly? A growing number of authors write about the power of intuition in solving problems, showing that intuitively made decisions can be of higher quality than decisions based on analytical reasoning. We want to know if decision makers, when receiving advice based on an intuitive cognitive process, also recognize the value of such advice. Is advice justified by intuition necessarily followed to a lesser extent than an advice justified by analysis? Furthermore, what are the important factors influencing the effect of intuitive justification on advice taking? Participants across three studies show that utilization of intuitive advice varies depending on advisor seniority and type of task for which the advice is given. Summarizing, the results suggest that decision makers a priori doubt the value of intuitive advice and only assess it as accurate if other cues in the advice setting corroborate this. Intuitively justified advice is utilized more if it comes from a senior advisor. In decision tasks with experiential products, intuitively justified advice can even have more impact than analytically justified advice. Copyright © 2013 John Wiley & Sons, Ltd.     

Resentment of Advice and Norms of Advice

Advice-giving is an important means of supporting others to act well. It inspires gratitude, indifference and resentment in equal measure. Although we can often predict a resentful reception for advice, its normative implications may be unclear. Should advice that is likely to be resented be withheld or modified because of its resentability, or delivered despite it? The norms that underwrite advice-giving, and which inform justified resentment, have thus far evaded systematic philosophical analysis. Using a case proposed by Edward Hinchman, the first part of this paper develops three lines of reasoning that explain why advice might be resented. The second part explores three norms of advice suggested by the case. Together they cast light upon the role of advice in our moral and social lives, and offer a starting point for practical reasoning about when to give resentable advice, and how to be a good advisor.     

语境交流导向与建议方式对建议采纳的影响

研究以JAS（决策者-建议者系统）为范式,通过2个实验探讨了语境交流导向（高/低）与建议方式（直白/隐晦）对个体建议采纳的影响以及其中的作用机制。实验1通过问卷测量个体的特质性语境交流导向;实验2则通过操纵材料启动个体的状态性语境交流导向。结果发现,高特质或状态语境交流导向的个体倾向于采纳隐晦型建议,而低特质或状态语境交流导向的个体则倾向于采纳直白型建议,并且个体对建议内容的加工流畅性在这一过程中起到了中介作用。     

Reliabilism and the Abductive Defence of Scientific Realism

According to the “no-miracles argument” (NMA), truth is the best explanation of the predictive-instrumental success of scientific theories. A standard objection against NMA is that it is viciously circular. In Scientific Realism: How Science Tracks Truth Stathis Psillos has claimed that the circularity objection can be met when NMA is supplemented with a reliabilist approach to justification. I will try to show, however, that scientific realists cannot take much comfort from this policy: if reliabilism makes no qualifications about the domain where inference to the best explanation is reliable, scientific realists flagrantly beg the question. A qualified version of reliabilism, on the other side, does not entitle us to infer the realist conclusion. I conclude, then, that Psillos’s proposal does not make any significant progress for scientific realism.

Good Advice

Advice is interesting because it is a relationship that is built upon two asymmetries. Advice concerns what the advisee ought to do. For that reason, considerations of autonomy suggest that the advisee has a greater claim on what matters in deliberation. However, the advisor is wiser than the advisee. That suggests that the advisor has a greater insight into what matters in deliberation. These are the asymmetry of autonomy and the asymmetry of wisdom. To account for both, I argue for informed subjectivism. Informed subjectivism is the view that the quality of advice is determined by the likelihood that the advisee would consistently prefer acting on the advice to not acting the advice. The theory captures the asymmetry of autonomy by making the quality of advice based on the advisee’s judgment. It captures the asymmetry of wisdom by making the relevant judgments of the advisee be ones that are informed by experience.     

Advice for Noncognitivists

Metaethical noncognitivists have trouble arriving at a respectable semantic theory for moral language. The goal of this article is to make substantial progress toward demonstrating that these problems may be overcome. Replacing the predominant expressivist semantic agenda in metaethics with a dynamic perspective on meaning and communication allows noncognitivists to provide a satisfying analysis of negation and other constructions that have been argued to be problematic for metaethical noncognitivism, including disjunctions. The resulting proposal preserves some of the key insights from recent work on the semantics of expressivism while highlighting the widely neglected early noncognitivists' sympathies to the kind of dynamic story I intend to tell here. A comparison between the advertised dynamic semantic story and current proposals that treat expressivism as a pragmatic rather than semantic theory about moral language is provided.