Christian Straßer

Scientific disagreements sometimes persist even if scientists fully share results of their research. In this paper we develop an agent-based model to study the impact of diverging diagnostic values scientists may assign to the evidence, given their different background assumptions, on the emergence of polarization in the scientific community. Scientists are represented as Bayesian updaters for whom the diagnosticity of evidence is given by the Bayes factor. Our results suggest that an initial disagreement on the diagnostic value of evidence can, but does not necessarily, lead to polarization, depending on the sample size of the performed studies and the confidence interval within which scientists share their opinions. In particular, the more data scientists share,the more likely it is that the community will end up polarized.

This paper considers various aspects of representing arguments and logical argumentation frameworks. We investigate different approaches to address consistency and minimality within such frameworks, arguing that these properties can, and in some cases should, be omitted from the definition of an argument. We analyze the relationship between how consistency is verified and the selection of attack rules, showing that this choice should align with the underlying logic. Based on these results, we propose compact representations of logical argumentation frameworks and examine methods for transforming one framework into another (e.g., a more concise version) without losing logical entailments.

This paper introduces a new format for reasoning with prioritized standards of normality. It is applicable in a broad variety of contexts, e.g. dealing with (possibly conflicting) prioritized belief bases or combining different reasoning methods in a prioritized way. The format is a generalization of the standard format of adaptive logics (see [4]). Every logic that is formulated within it has a straightforward semantics in the style of Shoham's selection semantics (see [22]) and a dynamic proof theory. Furthermore, it can count on a rich meta-theory that inherits the attractive features of the standard format, such as soundness and completeness, reflexivity, idempo-tence, cautious monotonicity, and many other properties. © 2013 Elsevier B.V., All rights reserved.

The standard format for adaptive logics offers a generic and unifying formal framework for defeasible reasoning forms. One of its main distinguishing features is a dynamic proof theory by means of which it is able to explicate actual reasoning. In many applications it has proven very useful to superpose sequences of adaptive logics, such that each logic treats the consequence set of its predecessor as premise set. Although attempts have been made to define dynamic proof theories for some of the resulting logics, no generic proof theory is available yet. Moreover, the existing proof theories for concrete superpositions are sub-optimal in various respects: the derivability relations characterized by these proposals are often not adequate with respect to the consequence relation of the superposed adaptive logics and in some cases they even trivialize premise sets. An adequate and generic proof theory is needed in order to meet the requirement of explicating defeasible reasoning in terms of superpositions of adaptive logics. This paper presents two equivalent generic proof theories for superpositions of adaptive logics in standard format. By means of simple examples, the basic ideas behind these proof theories are illustrated and it is shown how the older proposals are inadequate. © 2016 Elsevier B.V., All rights reserved.

Disjunctive reasoning, or reasoning by cases, plays a central role in defeasible frameworks and normative systems. This paper adopts a cautious approach, suggesting that rebutting disjunctive paths may render the inference defeasible, particularly in the context of default-based reasoning. To formalize this, we introduce explicit hypotheses to track reasoning paths. Building on prior work, we refine a class of Argument Calculi into a robust method for disjunctive reasoning in nonmonotonic logics, for both normative and doxastic interpretations of our system. We propose meta-theoretical properties tailored to disjunctive reasoning: disjunctive consistency and hypothetical consistency, which constrain argument behavior involving disjunction. By systematically comparing Argument Calculi against several properties, we analyze their implications for consistency and nonmonotonic inference in default-based frameworks.

What is the rational response to a scientific disagreement? Many epistemologists argue that disagreement with an epistemic peer should generally lead to conciliation by lowering confidence in the disputed belief or even suspending judgment altogether. Although this conciliatory approach is widely regarded as a norm of individual rationality, its value in the context of collective scientific inquiry is less clear. Some have even raised concerns that conciliating in scientific disagreements may slow progress or reduce the efficiency of inquiry. In this paper, we introduce a novel agent-based model that captures key aspects of scientific disagreement by incorporating both epistemic norms, which govern belief revision, and zetetic norms, which guide how scientists pursue inquiry. Our results indicate that the effects of conciliating in the face of disagreement---whether detrimental or beneficial---depend on the zetetic norms that scientists follow. When they focus on exploiting the hypothesis that they believe is most likely to succeed, remaining steadfast is more effective. However, with exploratory scientists, conciliation does not negatively affect group performance. These findings highlight the critical role of zetetic norms in determining the rational response to disagreement in scientific practice.

Communication plays a pivotal role in social phenomena such as belief polar- ization, scientific inquiry, and collective problem-solving. Agent-Based Models (ABMs) are computational tools that simulate the emergence of macro-level phenomena from micro-level interactions among agents. This paper focuses on Argumentative Agent-Based Models (AABMs), a specialized subset of ABMs that study argumentative communication, where agents provide reasons to sup- port or counter opinions. We present a systematic overview of AABMs, detailing their design, methodologies, and applications across disciplines. Key research questions include understanding the dynamics of consensus versus polarization, the conditions for epistemic reliability in collective decision-making, and the mechanisms that foster efficient collaboration within diverse groups through ar- gumentative exchanges. By synthesizing contributions from computer science, social science, and philosophy, this paper serves as both an entry point for new- comers and a comprehensive resource for researchers advancing the study of AABMs.

In this paper, we present an agent-based model for studying the impact of 'myside bias' on the argumentative dynamics in scientific communities. Recent insights in cognitive science suggest that scientific reasoning is influenced by `myside bias'. This bias manifests as a tendency to prioritize the search and generation of arguments that support one's views rather than arguments that undermine them. Additionally, individuals tend to apply more critical scrutiny to opposing stances than to their own. Although myside bias may pull individual scientists away from the truth, its effects on communities of reasoners remain unclear. The aim of our model is two-fold: first, to study the argumentative dynamics generated by myside bias, and second, to explore which mechanisms may act as a mitigating factor against its pernicious effects. Our results indicate that biased communities are epistemically less successful than non-biased ones, and that they also tend to be less polarized than non-biased ones. Moreover, we find that two socio-epistemic mechanisms help communities to mitigate the effect of the bias: the presence of a common filter on weak arguments, which can be interpreted as shared beliefs, and an equal distribution of agents for each alternative at the beginning.

In order to reason in a non-trivializing way with contradictions, paraconsistent logics reject some classically valid inferences. As a way to recover some of these inferences, Graham Priest proposed to nonmonotonically strengthen the Logic of Paradox by allowing the selection of “less inconsistent” models via a comparison of their respective inconsistent parts. This move recaptures a good portion of classical logic in that it does not block, e.g., disjunctive syllogism, unless it is applied to contradictory assumptions. In Priest’s approach the inconsistent parts of models are compared in an extensional way by consid- ering their inconsistent objects. This distinguishes his system from the standard format of (inconsistency-)adaptive logics pioneered by Diderik Batens, according to which (atomic) contradictions validated in models form the basis of their comparison. A well-known prob- lem for Priest’s extensional approach is its lack of the Strong Reassurance property, i.e., for specific settings there may be infinitely descending chains of less and less inconsistent models, thus never reaching a minimally inconsistent model. In the following paper, we show that Strong Reassurance holds for the extensional ap- proach under a cardinality-based comparison of the inconsistent parts of models. We develop and study the meta-theory of a class of nonmonotonic inconsistency-tolerant logics based on the extensional and the quantitative comparisons of their respective models, including important model-theoretic properties, such as the Löwenheim-Skolem theorems, as well as principles of nonmonotonic inference.

In order to reason in a non-trivializing way with contradictions, para- consistent logics reject some classically valid inferences. As a way of re- covering some of these inferences, Graham Priest ([Priest, 1991]) proposed to nonmonotonically strengthen the Logic of Paradox by allowing the se- lection of “less inconsistent” models via a comparison of their respective inconsistent parts. This move recaptures a good portion of classical logic in that it does not block, e.g., disjunctive syllogism, unless it is applied to contradictory assumptions. In Priest’s approach the inconsistent parts of models are compared in an extensional way by considering their inconsis- tent objects. This distinguishes his system from the standard format of (inconsistency-)adaptive logics pioneered by Diderik Batens, according to which (atomic) contradictions validated in models form the basis of their comparison. A well-known problem for Priest’s extensional approach is its lack of the Strong Reassurance property, i.e., for specific settings there may be infinitely descending chains of less and less inconsistent models, thus never reaching a minimally inconsistent model. In this paper, we demonstrate that Strong Reassurance holds for the extensional approach under a cardinality-based comparison of the incon- sistent parts of models. Furthermore, we introduce and investigate the metatheory of the class of first-order nonmonotonic inconsistency-tolerant construct over the extensional or quantitative comparisons of their respec- tive models. Core model-theoretic properties for these logics, such as the Löwenheim-Skolem theorems, along with other nonmonotonic properties, are further studied.

The paper challenges a recent attempt by Jouni-Matti Kuukkanen to show that since Thomas Kuhn’s philosophical standpoint can be incorporated into coherentist epistemology, it does not necessarily lead to: an abandonment of rationality and rational interparadigm theory comparison, nor to an abandonment of convergent realism. Leaving aside the interpretation of Kuhn as a coherentist, we will show that Kuukkanen’s first thesis is not sufficiently explicated, while the second one entirely fails. With regard to Thesis 1, we argue that Kuhn’s view on inter-paradigm theory comparison allows only for ‘the weak notion of rationality’, and that Kuukkanen’s argument is thus acceptable only in view of such a notion. With regard to Thesis 2, we show that even if we interpret Kuhn as a coherentist, his philosophical standpoint cannot be seen as compatible with convergent realism since Kuhn’s argument against it is not ‘ultimately empirical’, as Kuukkanen takes it to be.Keywords: Thomas S. Kuhn; Jouni-Matti Kuukkanen; Coherentist epistemology; Rationality; Theory choice; Convergent realism.

The aim of this paper is to offer an account of epistemic justification suitable for the context of theory pursuit, that is, for the context in which new scientific ideas, possibly incompatible with the already established theories, emerge and are pursued by scientists. We will frame our account paradigmatically on the basis of one of the influential systems of epistemic justification: Laurence Bonjour’s coherence theory of justification. The idea underlying our approach is to develop a set of criteria which indicate that the pursued system is promising of contributing to the epistemic goal of robustness of scientific knowledge and of developing into a candidate for acceptance. In order to realize this we will (a) adjust the scope of Bonjour’s standards—consistency, inferential density, and explanatory power, and (b) complement them by the requirement of a programmatic character. In this way we allow for the evaluation of the “potential coherence” of the given epistemic system.

Throughout the first half of the twentieth century the research on peptic ulcer disease focused on two rivaling hypothesis: the “acidity” and the “bacterial” one. According to the received view, the latter was dismissed during the 1950s only to be revived with Warren’s and Marshall’s discovery of Helicobacter pylori in the 1980s. In this paper we investigate why the bacterial hypothesis was largely abandoned in the 1950s, and whether there were good epistemic reasons for its dismissal. Of special interest for our research question is Palmer’s 1954 large-scale study, which challenged the bacterial hypothesis with serious counter-evidence, and which by many scholars is considered as the shifting point in the research on PUD. However, we show that: The perceived refutatory impact of Palmer’s study was disproportionate to its methodological rigor. This undermines its perceived status as a crucial experiment against the bacterial hypothesis. In view of this and other considerations we argue that the bacterial hypothesis was worthy of pursuit in the 1950s.

The aim of this paper is, on the one hand, to critically investigate Kuhn’s stance on the assessment of the pursuit worthiness of scientific theories, and, on the other hand, to show the actuality of some of Kuhn’s points on this issue, in view of their critical analysis. To this end we show that Kuhn presents certain tools, which may help scientists to overcome communication breakdowns when engaging in the process of rational deliberation regarding the question whether a theory is worthy of further pursuit. These tools are persuasion, translation and interpretation. However, we argue that the perspective of epistemic semantic monism present in Kuhn’s work obstructs the full applicability of these tools. We show that dropping this perspective makes the notions of persuasion and interpretation more fruitful, and moreover, allows for a pluralism of scientific theories and practices that complements the pluralism based on disagreement among scientists, emphasized by Kuhn.

argumentation has been shown to be a powerful tool within many fields such as artificial intelligence, logic and legal reasoning. In this paper we enhance Dung’s well-known abstract argumentation framework with explanatory capabilities. We show that an explanatory argumentation framework (EAF) obtained in this way is a useful tool for the modeling of scientific debates. On the one hand, EAFs allow for the representation of explanatory and justificatory arguments constituting rivaling scientific views. On the other hand, different procedures for selecting arguments, corresponding to different methodological and epistemic requirements of theory evaluation, can be formulated in view of our framework

Recent studies of scientific interaction based on agent-based models suggest that a crucial factor conducive to efficient inquiry is what Zollman has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories lasting sufficiently long for the community to identify the best theory and to converge on it. But what exactly generates transient diversity? And is transient diversity a decisive factor when it comes to the efficiency of inquiry? In this paper we examine the impact of different conditions on the efficiency of inquiry, as well as the relation between diversity and efficiency. This includes certain diversity-generating mechanisms previously proposed in the literature, as well as some factors that have so far been neglected. This study is obtained via an argumentation-based ABM. Our results suggest that cautious decision-making does not always have a significant impact on the efficiency of inquiry while different evaluations underlying theory-choice and different social networks do. Moreover, we find a correlation between diversity and a successful performance of agents only under specific conditions, which indicates that transient diversity is sometimes not the primary factor responsible for efficiency. Altogether, when comparing our results to those obtained by structurally different ABMs based on Zollman’s work, the impact of specific factors on efficiency of inquiry, as well as the role of transient diversity in achieving efficiency, appear to be highly dependent on the underlying model.