Do We "do"? - Steven A. Sloman; David A. Lagnado (Cogn. Sci., 2005)

Blame the Skilled. - Tobias Gerstenberg; Anastasia Ejova; David A. Lagnado (CogSci, 2011)

Rational Order Effects in Responsibility Attributions. - Tobias Gerstenberg; David A. Lagnado; Maarten Speekenbrink; Catherine Cheung (CogSci, 2011)

Beyond Outcomes: The Influence of Intentions and Deception. - Simeon Schaechtele; Tobias Gerstenberg; David A. Lagnado (CogSci, 2011)

Computational Models of Intuitive Physics. - Peter W. Battaglia; Tomer D. Ullman; Joshua B. Tenenbaum; Adam Sanborn; Kenneth D. Forbus; Tobias Gerstenberg; David A. Lagnado (CogSci, 2012)

Noisy Newtons: Unifying process and dependency accounts of causal attribution. - Tobias Gerstenberg; Noah D. Goodman; David A. Lagnado; Joshua B. Tenenbaum (CogSci, 2012)

Are Causal Structure and Intervention Judgments Inextricably Linked? A Developmental Study. - Caren A. Frosch; Teresa McCormack; David A. Lagnado; Patrick Burns (Cogn. Sci., 2012)

Mechanisms of Active Causal Learning. - Neil Bramley; David A. Lagnado; Maarten Speekenbrink (CogSci, 2013)

Time and Causality: Mutual Constraints; Insights from Event and Time Perception, Motor Control, and Gaming. - Marc J. Buehner; David A. Lagnado; Christos Bechlivanidis; Marc O. Ernst; Marieke Rohde; Michael Young (CogSci, 2013)

Back on track: Backtracking in counterfactual reasoning. - Tobias Gerstenberg; Christos Bechlivanidis; David A. Lagnado (CogSci, 2013)

Legal idioms: a framework for evidential reasoning. - David A. Lagnado; Norman E. Fenton; Martin Neil (Argument Comput., 2013)

A General Structure for Legal Arguments About Evidence Using Bayesian Networks. - Norman E. Fenton; Martin Neil; David A. Lagnado (Cogn. Sci., 2013)

Causal Responsibility and Counterfactuals. - David A. Lagnado; Tobias Gerstenberg; Ro'i Zultan (Cogn. Sci., 2013)

The order of things: Inferring causal structure from temporal patterns. - Neil Bramley; Tobias Gerstenberg; David A. Lagnado (CogSci, 2014)

From counterfactual simulation to causal judgment. - Tobias Gerstenberg; Noah D. Goodman; David A. Lagnado; Joshua B. Tenenbaum (CogSci, 2014)

Wins above replacement: Responsibility attributions as counterfactual replacements. - Tobias Gerstenberg; Tomer D. Ullman; Max Kleiman-Weiner; David A. Lagnado; Joshua B. Tenenbaum (CogSci, 2014)

Causal Supersession. - Jonathan F. Kominsky; Jonathan Phillips; Tobias Gerstenberg; David A. Lagnado; Joshua Knobe (CogSci, 2014)

Staying afloat on Neurath's boat - Heuristics for sequential causal learning. - Neil Bramley; Peter Dayan; David A. Lagnado (CogSci, 2015)

That's not the whole story: The role of reliability and credibility in evidential reasoning. - Saoirse Connor Desai; David A. Lagnado (CogSci, 2015)

How, whether, why: Causal judgments as counterfactual contrasts. - Tobias Gerstenberg; Noah D. Goodman; David A. Lagnado; Joshua B. Tenenbaum (CogSci, 2015)

Causal analysis for attributing responsibility in legal cases. - Hana Chockler; Norman E. Fenton; Jeroen Keppens; David A. Lagnado (ICAIL, 2015)

Consistency and credibility in legal reasoning: A Bayesian network approach. - Saoirse Connor Desai; Stian Reimers; David A. Lagnado (CogSci, 2016)

Can a Bayes' Net approach capture intuitive use of sequential testimonies in a legal reasoning paradigm? - Jens Koed Madsen; Saoirse Connor Desai; Adam J. L. Harris; David A. Lagnado (CogSci, 2016)

Formalizing Neurath's Ship: Approximate Algorithms for Online Causal Learning. - Neil R. Bramley; Peter Dayan; Thomas L. Griffiths 001; David A. Lagnado (CoRR, 2016)

How to model mutually exclusive events based on independent causal pathways in Bayesian network models. - Norman E. Fenton; Martin Neil; David A. Lagnado; William Marsh 001; Barbaros Yet; Anthony C. Constantinou (Knowl. Based Syst., 2016)

Causal learning from interventions and dynamics in continuous time. - Neil Bramley; Ralf Mayrhofer; Tobias Gerstenberg; David A. Lagnado (CogSci, 2017)

"Oops, I did it again." The impact of frequent behaviour on causal judgement. - Lara Kirfel; David A. Lagnado (CogSci, 2017)

The opportunity prior: a simple and practical solution to the prior probability problem for legal cases. - Norman E. Fenton; David A. Lagnado; Christian Dahlman; Martin Neil (ICAIL, 2017)

Updating Prior Beliefs Based on Ambiguous Evidence. - Stephen H. Dewitt; David A. Lagnado; Norman E. Fenton (CogSci, 2018)

Statistical norm effects in causal cognition. - Lara Kirfel; David A. Lagnado (CogSci, 2018)

Explaining away: significance of priors, diagnostic reasoning and structural complexity. - Alice Liefgreen; Marko Tesic; David A. Lagnado (CogSci, 2018)

Integrating dependent evidence: naïve reasoning in the face of complexity. - Toby D. Pilditch; Ulrike Hahn; David A. Lagnado (CogSci, 2018)

Ranking the Impact of Different Tests on a Hypothesis in a Bayesian Network. - Leila Schneps; Richard E. Overill; David A. Lagnado (Entropy, 2018)

Nested Sets and Natural Frequencies. - Stephen H. Dewitt; Anne Hsu; David A. Lagnado; Saoirse Connor Desai; Norman E. Fenton (CogSci, 2019)

I know what you did last summer (and how often). Epistemic states and statistical normality in causal judgements. - Lara Kirfel; David A. Lagnado (CogSci, 2019)

Selecting and evaluating evidence: The garden of forking information paths. - Alice Liefgreen; Toby D. Pilditch; David A. Lagnado (CogSci, 2019)

Deception in evidential reasoning: Willful deceit or honest mistake? - Toby D. Pilditch; Alexander Fries; David A. Lagnado (CogSci, 2019)

Shared Evidence: It all depends... - Toby D. Pilditch; Ulrike Hahn; David A. Lagnado (CogSci, 2019)

Zero-sum reasoning in information selection. - Toby D. Pilditch; Alice Liefgreen; David A. Lagnado (CogSci, 2019)

Modelling competing legal arguments using Bayesian model comparison and averaging. - Martin Neil; Norman E. Fenton; David A. Lagnado; Richard David Gill (Artif. Intell. Law, 2019)

I don't know if you did it, but I know why: A 'motive' preference at multiple stages of the legal-investigative process. - Alice Liefgreen; Sami R. Yousif; Frank Keil; David A. Lagnado (CogSci, 2020)

Temporal Binding, Causation, and Agency: Developing a New Theoretical Framework. - Christoph Hoerl; Sara Lorimer; Teresa McCormack; David A. Lagnado; Emma Blakey; Emma Tecwyn; Marc J. Buehner (Cogn. Sci., 2020)

BARD: A structured technique for group elicitation of Bayesian networks to support analytic reasoning. - Ann E. Nicholson; Kevin B. Korb; Erik P. Nyberg; Michael Wybrow; Ingrid Zukerman; Steven Mascaro; Shreshth Thakur; Abraham Oshni Alvandi; Jeff Riley; Ross Pearson; Shane Morris; Matthieu Herrmann; et al. (CoRR, 2020)

Analyzing the Simonshaven Case Using Bayesian Networks. - Norman E. Fenton; Martin Neil; Barbaros Yet; David A. Lagnado (Top. Cogn. Sci., 2020)

Categorical Belief Updating Under Uncertainty. - Stephen H. Dewitt; Carmen Li; Daniel Koh; Norman E. Fenton; David A. Lagnado (CogSci, 2021)

Causation by Ignorance. - Lara Kirfel; David A. Lagnado (CogSci, 2021)

The role of causal models in evaluating simple and complex legal explanations. - Alice Liefgreen; David A. Lagnado (CogSci, 2021)

Designing Memory Aids for Dementia Patients using Earables. - Matija Franklin; David A. Lagnado; Chulhong Min; Akhil Mathur; Fahim Kawsar (UbiComp/ISWC Adjunct, 2021)

Argumentative explanations for interactive recommendations. - Antonio Rago 001; Oana Cocarascu; Christos Bechlivanidis; David A. Lagnado; Francesca Toni (Artif. Intell., 2021)

Causal Framework of Artificial Autonomous Agent Responsibility. - Matija Franklin; Hal Ashton; Edmond Awad; David A. Lagnado (AIES, 2022)

Exploring the Richness of Human Causal Reasoning with Think Aloud Data. - Stephen H. Dewitt; Ekaterina Stoilova; David A. Lagnado (CogSci, 2022)

Explanations that backfire: Explainable artificial intelligence can cause information overload. - Aidah Nakakande Ferguson; Matija Franklin; David A. Lagnado (CogSci, 2022)

Human-AI Interaction Paradigm for Evaluating Explainable Artificial Intelligence. - Matija Franklin; David A. Lagnado (HCI (37), 2022)

Swipe and hold: composing interventions in continuous time causal learning. - Victor Btesh; David A. Lagnado; Maarten Speekenbrink; Neil R. Bramley (CogSci, 2023)

Defendant character influences mock juror judgments of blame, guilt, and punishment. - Vanessa Cheung; David A. Lagnado (CogSci, 2023)

How does knowledge of detainment affect juror reasoning? - Stephen H. Dewitt; Sammy Glatzel; David A. Lagnado (CogSci, 2023)

Blame attribution in human-AI and human-only systems: Crowdsourcing judgments from Twitter. - Matija Franklin; Trisevgeni Papakonstantinou; Tianshu Chen; Carlos Fernandez-Basso; David A. Lagnado (CogSci, 2023)

Expectation of temporal delays shapes Judgement of Causal Strength and Causal Structure. - Ziyi Guo; Christos Bechlivanidis; David A. Lagnado (CogSci, 2023)

Do people prefer prediction over accommodation? An empirical study. - Laura Elaine Strittmatter; Stephen H. Dewitt; David A. Lagnado (CogSci, 2023)

Enhancing Wearable Technologies for Dementia Care: A Cognitive Architecture Approach. - Matija Franklin; David A. Lagnado; Chulhong Min; Akhil Mathur; Fahim Kawsar (EXTRAAMAS, 2023)

An Unsupervised Approach to Extracting Knowledge from the Relationships Between Blame Attribution on Twitter. - Matija Franklin; Trisevgeni Papakonstantinou; Tianshu Chen; Carlos Fernandez-Basso; David A. Lagnado (FQAS, 2023)

Who Is to Blame? Responsibility Attribution in AI Systems vs Human Agents in the Field of Air Crashes. - Jesica Gómez-Sánchez; Cristina Gordo; Matija Franklin; Carlos Fernandez-Basso; David A. Lagnado (FQAS, 2023)

Categorical Updating in a Bayesian Propensity Problem. - Stephen H. Dewitt; Nine Adler; Carmen Li; Ekaterina Stoilova; Norman E. Fenton; David A. Lagnado (Cogn. Sci., 2023)

Explainable AI: Definition and attributes of a good explanation for health AI. - Evangelia Kyrimi; Scott McLachlan; Jared M. Wohlgemut; Zane B. Perkins; David A. Lagnado; William Marsh 001; ExAIDSS Expert Group (CoRR, 2024)

Reasoning about Affordances: Causal and Compositional Reasoning in LLMs. - Magnus F. Gjerde; Vanessa Cheung; David A. Lagnado (CoRR, 2025)

Explainable AI: definition and attributes of a good explanation for health AI. - Evangelia Kyrimi; Scott McLachlan; Jared M. Wohlgemut; Zane B. Perkins; David A. Lagnado; William Marsh 001; Alexander Gimson; Ali Shafti; Ari Ercole; Amitava Banerjee; Ben Glocker; Burkhard Schafer 001; et al. (AI Ethics, 2025)