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

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

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

Natural science: Active learning in dynamic physical microworlds. - Neil Bramley; Tobias Gerstenberg; Joshua B. Tenenbaum (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)

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

Beliefs about sparsity affect causal experimentation. - Anna Coenen; Neil Bramley; Azzurra Ruggeri; Todd M. Gureckis (CogSci, 2017)

Strategic exploration in human adaptive control. - Eric Schulz; Edgar D. Klenske; Neil Bramley; Maarten Speekenbrink (CogSci, 2017)

Grounding Compositional Hypothesis Generation in Specific Instances. - Neil Bramley; Anselm Rothe; Josh Tenenbaum 001; Fei Xu; Todd M. Gureckis (CogSci, 2018)

Learning as program induction. - Neil Bramley; Eric Schulz; Fei Xu; Josh Tenenbaum 001 (CogSci, 2018)

Causal Structure Learning with Continuous Variables in Continuous Time. - Zachary Davis 001; Neil Bramley; Bob Rehder (CogSci, 2018)

A Causal Model Approach to Dynamic Control. - Zachary Davis 001; Neil Bramley; Bob Rehder; Todd M. Gureckis (CogSci, 2018)

Modeling dynamics of suspense and surprise. - Zhiwei Li; Neil Bramley; Todd M. Gureckis (CogSci, 2018)

Children's Causal Interventions Combine Discrimination and Confirmation. - Yuan Meng; Neil Bramley; Fei Xu (CogSci, 2018)

The critical moment is coming: Modeling the dynamics of suspense. - Zhiwei Li; Neil Bramley; Todd M. Gureckis (CogSci, 2019)

Active physical inference via reinforcement learning. - Shuaiji Li; Yu Sun; Sijia Liu; Tianyu Wang; Todd M. Gureckis; Neil Bramley (CogSci, 2019)

Limits on the Use of Simulation in Physical Reasoning. - Ethan Ludwin-Peery; Neil Bramley; Ernest Davis; Todd M. Gureckis (CogSci, 2019)

Dynamic Control Under Changing Goals. - Zachary Davis 001; Neil Bramley; Bob Rehder; Todd M. Gureckis (CogSci, 2020)

Belief revision in a micro-social network: Modeling sensitivity to statistical dependencies in social learning. - Jan-Philipp Fränken; Nikolas Theodoropoulos; Adam Moore; Neil Bramley (CogSci, 2020)

What you didn't see: Prevention and generation in continuous time causal induction. - Tianwei Gong; Neil Bramley (CogSci, 2020)

A Generalization Test of Conjunction Errors in Physical Reasoning. - Ethan Ludwin-Peery; Neil Bramley; Ernest Davis; Todd M. Gureckis (CogSci, 2020)

Contrasting RNN-based and simulation-based models of human physical parameter inference. - Héctor Otero Mediero; Neil Bramley (CogSci, 2020)

Learning Hidden Causal Structure from Temporal Data. - Simon Valentin; Neil Bramley; Christopher Lucas 001 (CogSci, 2020)

Order Effects in One-shot Causal Generalization. - Bonan Zhao 001; Neil Bramley (CogSci, 2020)

Know your network: Sensitivity to structure in social learning. - Jan-Philipp Fränken; Simon Valentin; Chris Lucas 001; Neil R. Bramley (CogSci, 2021)

Bayesian Experimental Design for Intractable Models of Cognition. - Simon Valentin; Steven Kleinegesse; Neil R. Bramley; Michael U. Gutmann; Chris Lucas 001 (CogSci, 2021)

Symbolic and Sub-Symbolic Systems in People and Machines. - Simon Valentin; Bonan Zhao 001; Chentian Jiang; Neil Bramley; Chris Lucas 001 (CogSci, 2021)

Bayesian Optimal Experimental Design for Simulator Models of Cognition. - Simon Valentin; Steven Kleinegesse; Neil R. Bramley; Michael U. Gutmann; Christopher G. Lucas (CoRR, 2021)

Building Object-based Causal Programs for Human-like Generalization. - Bonan Zhao 001; Christopher G. Lucas; Neil R. Bramley (CoRR, 2021)

Inferring epistemic intention in simulated physical microworlds. - Stephanie Droop; Neil R. Bramley (CogSci, 2022)

Intuitions and Perceptual Constraints on Causal Learning from Dynamics. - Tianwei Gong; Neil R. Bramley (CogSci, 2022)

Categorizing perceived causal events. - Nicolas Marchant; Bonan Zhao 001; Neil R. Bramley; Diego Morales; Sergio E. Chaigneau (CogSci, 2022)

Generating and evaluating hypothesis testing strategies. - Aba Szollosi; Neil R. Bramley (CogSci, 2022)

Powering up causal generalization: A model of human conceptual bootstrapping with adaptor grammars. - Bonan Zhao 001; Neil R. Bramley; Chris Lucas 001 (CogSci, 2022)

The Paradox of Time in Dynamic Causal Systems. - Bob Rehder; Zachary J. Davis 001; Neil Bramley (Entropy, 2022)

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

People seek easily interpretable information. - Samuel J. Cheyette; Frederick Callaway; Neil R. Bramley; Jonathan D. Nelson; Josh Tenenbaum 001 (CogSci, 2023)

Extending counterfactual reasoning models to unconstrained social explanations. - Stephanie Droop; Neil R. Bramley (CogSci, 2023)

Causal inference shapes counterfactual plausibility. - Tadeg Quillien; Aba Szollosi; Neil R. Bramley; Chris Lucas 001 (CogSci, 2023)

How do instructions, examples, and testing shape task representations? - Aba Szollosi; Vlad Grigoras; Tadeg Quillien; Chris Lucas 001; Neil R. Bramley (CogSci, 2023)

Designing Optimal Behavioral Experiments Using Machine Learning. - Simon Valentin; Steven Kleinegesse; Neil R. Bramley; Peggy Seriès; Michael U. Gutmann; Christopher G. Lucas (CoRR, 2023)

Constructing Deep Concepts through Shallow Search. - Bonan Zhao 001; Christopher G. Lucas; Neil R. Bramley (AAAI Spring Symposia, 2024)

People Attribute Purpose to Autonomous Vehicles When Explaining Their Behavior: Insights from Cognitive Science for Explainable AI. - Balint Gyevnar; Stephanie Droop; Tadeg Quillien; Shay B. Cohen; Neil R. Bramley; Christopher G. Lucas; Stefano V. Albrecht (CHI, 2025)

Predicting Multi-Agent Specialization via Task Parallelizability. - Elizabeth Mieczkowski; Ruaridh Mon-Williams; Neil Bramley; Christopher G. Lucas; Natalia Vélez; Thomas L. Griffiths 001 (CoRR, 2025)

Partner Modelling Emerges in Recurrent Agents (But Only When It Matters). - Ruaridh Mon-Williams; Max Taylor-Davies; Elizabeth Mieczkowski; Natalia Vélez; Neil R. Bramley; Yanwei Wang; Thomas L. Griffiths 001; Christopher G. Lucas (CoRR, 2025)