Mario Günther

Ludwig-Maximilians-Universität in Munich | LMU · Munich Center for Mathematical Philosophy (MCMP)

We propose a method of learning indicative conditional information. An agent learns conditional information by Jeffrey imaging on the minimally informative proposition expressed by a Stalnaker conditional. We show that the predictions of the proposed method align with the intuitions in Douven (2012)'s benchmark examples. Jeffrey imaging on Stalnake...

Sartorio [4] argues convincingly that disjunctive causes exist. To treat disjunctive causes within Halpern and Pearl [2]'s framework of causal models, we extend their causal model semantics by disjunctive antecedents and propose a refinement of their definition of actual causation.

We impose properties of causation, as assumed in cognitive neuroscience, upon Woodward (2005,2015)'s account of interventionism. Within the resulting framework, we investigate to what extent we are justified to derive causal relations between mental properties and properties of the brain, if certain methods are used in the neuroscientific studies.

We show that the learning of (uncertain) conditional and/or causal information may be modeled by (Jeffrey) imaging on Stalnaker conditionals. We adapt the method of learning uncertain conditional information proposed in Günther (2017) to a method of learning uncertain causal information. The idea behind the adaptation parallels Lewis (1973c)'s anal...

The formal semantics of conditionals by Robert Stalnaker (1968), David Lewis (1973a), and Peter Gärdenfors (1978, 1988) fail to distinguish between trivially and non-trivially true indicative conditionals. This problem has been addressed by Hans Rott (1986) in terms of a strengthened Ramsey Test. In this paper, we refine Rott's variant of a strengt...

In this paper, we develop a non-reductive variant of the regularity theory of causation proposed in Andreas and Günther (Pacific Philosophical Quarterly 105: 2–32, 2024). The variant is motivated as a refinement of Lewis’s (Journal of Philosophy 70:556–567, 1973) regularity theory. We do not pursue a reductive theory here because we found a challen...

In this paper, we propose a regularity theory of causation. The theory aims to be reductive and to align with our pre‐theoretic understanding of the causal relation. We show that our theory can account for a wide range of causal scenarios, including isomorphic scenarios, omissions, and scenarios which suggest that causation is not transitive.

One of the open questions in Bayesian epistemology is how to rationally learn from indicative conditionals (Douven, 2016). Eva et al. ( Mind 129(514):461–508, 2020) propose a strategy to resolve this question. They claim that their strategy provides a “uniquely rational response to any given learning scenario”. We show that their updating strategy...

We put forth an account for when to believe causal and evidential conditionals. The basic idea is to embed a causal model in an agent’s belief state. For the evaluation of conditionals seems to be relative to beliefs about both particular facts and causal relations. Unlike other attempts using causal models, we show that ours can account rather wel...

In this paper, we propose a unified account of conditionals inspired by Frank Ramsey. Most contemporary philosophers agree that Ramsey’s account applies to indicative conditionals only. We observe against this orthodoxy that his account covers subjunctive conditionals as well—including counterfactuals. In light of this observation, we argue that Ra...

Should decision-making algorithms be held to higher standards of transparency than human beings? The way we answer this question directly impacts what we demand from explainable algorithms, how we govern them via regulatory proposals, and how explainable algorithms may help resolve the social problems associated with decision making supported by ar...

In this paper, we propose a unified account of conditionals inspired by Frank Ramsey. Most contemporary philosophers agree that Ramsey's account applies to indicative conditionals only. We observe against this orthodoxy that his account covers subjunctive conditionals as well-including counterfactuals. In light of this observation, we argue that Ra...

We define a formal semantics of conditionals based on normatively ideal worlds. Such worlds are described informally by Armgardt (Gabbay D, Magnani L, Park W, Pietarinen A-V (eds) Natural arguments: a tribute to john woods, College Publications, London, pp 699–708, 2018) to address well-known problems of the counterfactual approach to causation. Dr...

We propose a semantics for a connexive conditional based on the Lewis-Stalnaker conditional. It is a connexive semantics that is both classical and intuitive.

In this paper, we put forth an analysis of sensitivity which aims to discern individual from merely statistical evidence. We argue that sensitivity is not to be understood as a factive concept, but as a purely epistemic one. Our resulting analysis of epistemic sensitivity gives rise to an account of legal proof on which a defendant is only found li...

We put forth an analysis of causation. The analysis centers on the notion of a causal model that provides only partial information as to which events occur, but complete information about the dependences between the events. The basic idea is this: an event causes another just in case there is a causal model that is uninformative on both events and...

In this paper, we analyse actual causation in terms of production. The latter concept is made precise by a strengthened Ramsey Test semantics of conditionals: A≫C\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength...

We aim to devise a Ramsey test analysis of actual causation. Our method is to define a strengthened Ramsey test for causal models. Unlike the accounts of Halpern and Pearl ([2005]) and Halpern ([2015]), the resulting analysis deals satisfactorily with both overdetermination and conjunctive scenarios. 1Introduction2An Extension of Causal Model Seman...

We aim to provide a variant to the definitions of actual causation put forth by Halpern and Pearl (2005) and Halpern (2015). Our method is to define a strengthened Ramsey Test for causal models. Unlike Halpern and Pearl (2005) and Halpern's modification thereof in Halpern (2015), our variant deals satisfactorily with both overdetermination and conj...

Talk delivered at the Workshop on “Learning Conditionals” of the Center for Advanced Studies, LMU Munich

I aim to resolve the philosophical controversy between logical symbolicism and dynamicist connectionism in cognitive science. A prominent philosopher, Timothy van Gelder, holds the view that the fundamental difference between symbolic systems and dynamical systems can be rendered explicit by looking at their computational powers. We argue – against...