Mayrhofer, Ralf

[["dc.bibliographiccitation.firstpage","789"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Psychonomic Bulletin & Review"],["dc.bibliographiccitation.lastpage","796"],["dc.bibliographiccitation.volume","23"],["dc.contributor.author","Mayrhofer, Ralf"],["dc.contributor.author","Waldmann, M. R."],["dc.date.accessioned","2018-11-07T10:13:01Z"],["dc.date.available","2018-11-07T10:13:01Z"],["dc.date.issued","2016"],["dc.description.abstract","In the Michotte task, a ball (X) moves toward a resting ball (Y). In the moment of contact, X stops und Y starts moving. Previous studies have shown that subjects tend to view X as the causal agent (\"X launches Y\") rather than Y (\"Y stops X\"). Moreover, X tends to be attributed more force than Y (force asymmetry), which contradicts the laws of Newtonian mechanics. Recent theories of force asymmetry try to explain these findings as the result of an asymmetrical identification with either the (stronger) agent or the (weaker) patient of the causal interaction. We directly tested this assumption by manipulating attributions of causal agency while holding the properties of the causal interaction constant across conditions. In contrast to previous accounts, we found that force judgments stayed invariant across conditions in which assignments of causal agency shifted from X to Y and that even those subjects who chose Y as the causal agent gave invariantly higher force ratings to X. These results suggest that causal agency and the perception of force are conceptually independent of each other. Different possible explanations are discussed."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft [Wa 621/22-1, Ma 6545/1-2, SPP 1516]"],["dc.identifier.doi","10.3758/s13423-015-0960-y"],["dc.identifier.isi","000381177400011"],["dc.identifier.pmid","26452375"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/12591"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/40352"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Springer"],["dc.relation.issn","1531-5320"],["dc.relation.issn","1069-9384"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Causal agency and the perception of force"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","3-4"],["dc.bibliographiccitation.journal","International Journal of Psychology"],["dc.bibliographiccitation.volume","43"],["dc.contributor.author","Mayrhofer, Ralf"],["dc.contributor.author","Waldmann, Michael R."],["dc.date.accessioned","2018-11-07T11:14:32Z"],["dc.date.available","2018-11-07T11:14:32Z"],["dc.date.issued","2008"],["dc.identifier.isi","000259264300366"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/54142"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Psychology Press"],["dc.publisher.place","Hove"],["dc.title","Mind reading aliens: Inferring causal structure from covariational data"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","2137"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","Cognitive Science"],["dc.bibliographiccitation.lastpage","2150"],["dc.bibliographiccitation.volume","40"],["dc.contributor.author","Mayrhofer, Ralf"],["dc.contributor.author","Waldmann, M. R."],["dc.date.accessioned","2018-11-07T10:06:18Z"],["dc.date.available","2018-11-07T10:06:18Z"],["dc.date.issued","2016"],["dc.description.abstract","Research on human causal induction has shown that people have general prior assumptions about causal strength and about how causes interact with the background. We propose that these prior assumptions about the parameters of causal systems do not only manifest themselves in estimations of causal strength or the selection of causes but also when deciding between alternative causal structures. In three experiments, we requested subjects to choose which of two observable variables was the cause and which the effect. We found strong evidence that learners have interindividually variable but intraindividually stable priors about causal parameters that express a preference for causal determinism (sufficiency or necessity; Experiment 1). These priors predict which structure subjects preferentially select. The priors can be manipulated experimentally (Experiment 2) and appear to be domain-general (Experiment 3). Heuristic strategies of structure induction are suggested that can be viewed as simplified implementations of the priors."],["dc.identifier.doi","10.1111/cogs.12318"],["dc.identifier.isi","000388565700014"],["dc.identifier.pmid","26522238"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/39062"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","1551-6709"],["dc.relation.issn","0364-0213"],["dc.title","Sufficiency and Necessity Assumptions in Causal Structure Induction"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","277"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Psychological Review"],["dc.bibliographiccitation.lastpage","301"],["dc.bibliographiccitation.volume","121"],["dc.contributor.author","Meder, Bjoern"],["dc.contributor.author","Mayrhofer, Ralf"],["dc.contributor.author","Waldmann, M. R."],["dc.date.accessioned","2018-11-07T09:37:59Z"],["dc.date.available","2018-11-07T09:37:59Z"],["dc.date.issued","2014"],["dc.description.abstract","Our research examines the normative and descriptive adequacy of alternative computational models of diagnostic reasoning from single effects to single causes. Many theories of diagnostic reasoning are based on the normative assumption that inferences from an effect to its cause should reflect solely the empirically observed conditional probability of cause given effect. We argue against this assumption, as it neglects alternative causal structures that may have generated the sample data. Our structure induction model of diagnostic reasoning takes into account the uncertainty regarding the underlying causal structure. A key prediction of the model is that diagnostic judgments should not only reflect the empirical probability of cause given effect but should also depend on the reasoner's beliefs about the existence and strength of the link between cause and effect. We confirmed this prediction in 2 studies and showed that our theory better accounts for human judgments than alternative theories of diagnostic reasoning. Overall, our findings support the view that in diagnostic reasoning people go \"beyond the information given\" and use the available data to make inferences on the (unobserved) causal rather than on the (observed) data level."],["dc.identifier.doi","10.1037/a0035944"],["dc.identifier.isi","000340470300001"],["dc.identifier.pmid","25090421"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/32963"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Amer Psychological Assoc"],["dc.relation.issn","1939-1471"],["dc.relation.issn","0033-295X"],["dc.title","Structure Induction in Diagnostic Causal Reasoning"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","485"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Cognition"],["dc.bibliographiccitation.lastpage","490"],["dc.bibliographiccitation.volume","132"],["dc.contributor.author","Mayrhofer, Ralf"],["dc.contributor.author","Waldmann, M. R."],["dc.date.accessioned","2018-11-07T09:36:17Z"],["dc.date.available","2018-11-07T09:36:17Z"],["dc.date.issued","2014"],["dc.description.abstract","The question how agent and patient roles are assigned to causal participants has largely been neglected in the psychological literature on force dynamics. Inspired by the linguistic theory of Dowty (1991), we propose that agency attributions are based on a prototype concept of human intervention. We predicted that the number of criteria a participant in a causal interaction shares with this prototype determines the strength of agency intuitions. We showed in two experiments using versions of Michotte's (1963) launching scenarios that agency intuitions were moderated by manipulations of the context prior to the launching event. Altering features, such as relative movement, sequence of visibility, and self-propelled motion, tended to increase agency attributions to the participant that is normally viewed as patient in the standard scenario. (C) 2014 Elsevier B.V. All rights reserved."],["dc.identifier.doi","10.1016/j.cognition.2014.05.013"],["dc.identifier.isi","000340013900020"],["dc.identifier.pmid","24955502"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/32581"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Elsevier Science Bv"],["dc.relation.issn","1873-7838"],["dc.relation.issn","0010-0277"],["dc.title","Indicators of causal agency in physical interactions: The role of the prior context"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","85"],["dc.bibliographiccitation.journal","The Psychology of Learning and Motivation"],["dc.bibliographiccitation.lastpage","127"],["dc.bibliographiccitation.volume","65"],["dc.contributor.author","Waldmann, M. R."],["dc.contributor.author","Mayrhofer, Ralf"],["dc.date.accessioned","2018-11-07T10:20:03Z"],["dc.date.available","2018-11-07T10:20:03Z"],["dc.date.issued","2016"],["dc.description.abstract","The main goal of this chapter is to defend a new view on causal reasoning, a hybrid representation account. In both psychology and philosophy, different frameworks of causal reasoning compete, each endowed with its distinctive strengths and weaknesses and its preferred domains of application. Three frameworks are presented that either focus on dependencies, dispositions, or processes. Our main claim is that despite the beauty of a parsimonious unitary account, there is little reason to assume that people are restricted to one type of representation of causal scenarios. In contrast to causal pluralism, which postulates the coexistence of different representations in causal reasoning, our aim is to show that competing representations do not only coexist, they can also actively influence each other. In three empirical case studies, we demonstrate how causal dependency, causal dispositional, and causal process representations mutually interact in generating complex representations driving causal inferences."],["dc.identifier.doi","10.1016/bs.plm.2016.04.001"],["dc.identifier.isi","000383370100003"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/41800"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.isbn","978-0-12-805182-5"],["dc.relation.issn","0079-7421"],["dc.title","Hybrid Causal Representations"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Cognitive Science"],["dc.bibliographiccitation.volume","44"],["dc.contributor.author","Stephan, Simon"],["dc.contributor.author","Mayrhofer, Ralf"],["dc.contributor.author","Waldmann, Michael R."],["dc.date.accessioned","2021-04-14T08:25:27Z"],["dc.date.available","2021-04-14T08:25:27Z"],["dc.date.issued","2020"],["dc.description.abstract","Abstract Causal queries about singular cases, which inquire whether specific events were causally connected, are prevalent in daily life and important in professional disciplines such as the law, medicine, or engineering. Because causal links cannot be directly observed, singular causation judgments require an assessment of whether a co‐occurrence of two events c and e was causal or simply coincidental. How can this decision be made? Building on previous work by Cheng and Novick (2005) and Stephan and Waldmann (2018), we propose a computational model that combines information about the causal strengths of the potential causes with information about their temporal relations to derive answers to singular causation queries. The relative causal strengths of the potential cause factors are relevant because weak causes are more likely to fail to generate effects than strong causes. But even a strong cause factor does not necessarily need to be causal in a singular case because it could have been preempted by an alternative cause. We here show how information about causal strength and about two different temporal parameters, the potential causes' onset times and their causal latencies, can be formalized and integrated into a computational account of singular causation. Four experiments are presented in which we tested the validity of the model. The results showed that people integrate the different types of information as predicted by the new model."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659"],["dc.identifier.doi","10.1111/cogs.12871"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/81635"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","1551-6709"],["dc.relation.issn","0364-0213"],["dc.rights","This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited."],["dc.title","Time and Singular Causation—A Computational Model"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","65"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Cognitive Science"],["dc.bibliographiccitation.lastpage","95"],["dc.bibliographiccitation.volume","39"],["dc.contributor.author","Mayrhofer, Ralf"],["dc.contributor.author","Waldmann, M. R."],["dc.date.accessioned","2018-11-07T10:03:40Z"],["dc.date.available","2018-11-07T10:03:40Z"],["dc.date.issued","2015"],["dc.description.abstract","Currently, two frameworks of causal reasoning compete: Whereas dependency theories focus on dependencies between causes and effects, dispositional theories model causation as an interaction between agents and patients endowed with intrinsic dispositions. One important finding providing a bridge between these two frameworks is that failures of causes to generate their effects tend to be differentially attributed to agents and patients regardless of their location on either the cause or the effect side. To model different types of error attribution, we augmented a causal Bayes net model with separate error sources for causes and effects. In several experiments, we tested this new model using the size of Markov violations as the empirical indicator of differential assumptions about the sources of error. As predicted by the model, the size of Markov violations was influenced by the location of the agents and was moderated by the causal structure and the type of causal variables."],["dc.identifier.doi","10.1111/cogs.12132"],["dc.identifier.isi","000348656300003"],["dc.identifier.pmid","24831193"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/38526"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","1551-6709"],["dc.relation.issn","0364-0213"],["dc.title","Agents and Causes: Dispositional Intuitions As a Guide to Causal Structure"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]