Modeling human function learning with Gaussian processes. - Thomas L. Griffiths 001; Christopher G. Lucas; Joseph Jay Williams; Michael L. Kalish (NIPS, 2008)

A rational model of preference learning and choice prediction by children. - Christopher G. Lucas; Thomas L. Griffiths 001; Fei Xu; Christine Fawcett (NIPS, 2008)

Inferring Hidden Causal Structure. - Tamar Kushnir; Alison Gopnik; Christopher G. Lucas; Laura Schulz (Cogn. Sci., 2010)

Learning the Form of Causal Relationships Using Hierarchical Bayesian Models. - Christopher G. Lucas; Thomas L. Griffiths 001 (Cogn. Sci., 2010)

Young Toddlers' Understanding of Graded Preferences. - Jane C. Hu; Christopher G. Lucas; Thomas L. Griffiths 001; Fei Xu (CogSci, 2011)

From preferences to choices and back again: evidence for human inconsistency and its implications. - Christopher G. Lucas; Charles Kemp; Thomas L. Griffiths 001 (CogSci, 2011)

A Bayesian model of navigation in squirrels. - Anna Waisman; Christopher G. Lucas; Thomas L. Griffiths 001; Lucia Jacobs (CogSci, 2011)

Evaluating the inverse decision-making approach to preference learning. - Alan Jern; Christopher G. Lucas; Charles Kemp (NIPS, 2011)

A unified theory of counterfactual reasoning. - Christopher G. Lucas; Charles Kemp (CogSci, 2012)

Superspace extrapolation reveals inductive biases in function learning. - Christopher G. Lucas; Douglas Sterling; Charles Kemp (CogSci, 2012)

Determining people's expectations about the form of causal relationships. - Saiwing Yeung; Christopher G. Lucas; Thomas L. Griffiths 001 (CogSci, 2012)

Non-Bayesian Inference: Causal Structure Trumps Correlation. - Bénédicte Bes; Steven A. Sloman; Christopher G. Lucas; Eric Raufaste (Cogn. Sci., 2012)

What if? Counterfactual reasoning, pretense, and the role of possible worlds. - Daphna Buchsbaum; Caren M. Walker; Alison Gopnik; Nick Chater; David Danks; Christopher G. Lucas; Charles Kemp; Eva Rafetseder; Josef Perner (CogSci, 2013)

Discovering hidden causes using statistical evidence. - Christopher G. Lucas; Kenneth Holstein; Charles Kemp (CogSci, 2014)

Learning to reason about desires: An infant training study. - Tiffany Doan; Stephanie Denison; Christopher G. Lucas; Alison Gopnik (CogSci, 2015)

Inferring causal structure and hidden causes from event sequences. - Christopher G. Lucas; Kenneth Holstein; Michael Pacer (CogSci, 2015)

The Human Kernel. - Andrew Gordon Wilson; Christoph Dann; Christopher G. Lucas; Eric P. Xing (NIPS, 2015)

The construction of function representations. - Brian Montambault; Christopher Lucas 001; Joseph L. Austerweil (CogSci, 2016)

Functional Inferences over Heterogeneous Data. - Kwabena Nuamah; Alan Bundy; Christopher Lucas 001 (RR, 2016)

Finding Periodic Discrete Events in Noisy Streams. - Abhirup Ghosh; Christopher Lucas 001; Rik Sarkar (CIKM, 2017)

Investigating the Explore/Exploit Trade-off in Adult Causal Inferences. - Erik Herbst; Christopher G. Lucas; Daphna Buchsbaum (CogSci, 2017)

Identifying Causal Direction in the Two-Variable Case. - Pablo León-Villagrá; Christopher Lucas 001 (CogSci, 2017)

Automated Reasoning in the Age of the Internet. - Alan Bundy; Kwabena Nuamah; Christopher Lucas 001 (AISC, 2018)

Data Availability and Function Extrapolation. - Pablo León-Villagrá; Irina Preda; Christopher Lucas 001 (CogSci, 2018)

Does Ability Affect Alignment in Second Language Tutorial Dialogue? - Arabella Sinclair; Adam Lopez; Christopher G. Lucas; Dragan Gasevic (SIGDIAL Conference, 2018)

I Wanna Talk Like You: Speaker Adaptation to Dialogue Style in L2 Practice Conversation. - Arabella J. Sinclair; Rafael Ferreira 002; Dragan Gasevic; Christopher G. Lucas; Adam Lopez (AIED (2), 2019)

Epistemic drive and memory manipulations in explore-exploit problems. - Nicolas Collignon; Chris Lucas 001 (CogSci, 2019)

Exploring the Representation of Linear Functions. - Pablo León-Villagrá; Verena Klar; Adam Sanborn; Chris Lucas 001 (CogSci, 2019)

Generalizing Functions in Sparse Domains. - Pablo León-Villagrá; Chris Lucas 001 (CogSci, 2019)

Reward Function Complexity and Goals in Exploration-Exploitation Tasks. - Brian Montambault; Chris Lucas 001 (CogSci, 2019)

Inattentional Blindness in Visual Search. - Matt Rounds; Chris Lucas 001; Frank Keller (CogSci, 2019)

Tutorbot Corpus: Evidence of Human-Agent Verbal Alignment in Second Language Learner Dialogues. - Arabella Sinclair; Kate McCurdy; Christopher G. Lucas; Adam Lopez; Dragan Gasevic (EDM, 2019)

Incremental Hypothesis Revision in Causal Reasoning Across Development. - Rebekah Gelpi; Ben Prystawski; Christopher Lucas 001; Daphna Buchsbaum (CogSci, 2020)

Exploring Category Structure in Children and Adults. - Pablo León-Villagrá; Isaac Ehrlich; Chris Lucas 001; Daphna Buchsbaum (CogSci, 2020)

Uncovering Category Representations with Linked MCMC with People. - Pablo León-Villagrá; Kay Otsubo; Chris Lucas 001; Daphna Buchsbaum (CogSci, 2020)

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

Optimising Placement of Pollution Sensors in Windy Environments. - Sigrid Passano Hellan; Christopher G. Lucas; Nigel H. Goddard (CoRR, 2020)

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

Sampling Heuristics for Active Function Learning. - Rebekah Gelpi; Nayan Saxena; George Lifchits; Daphna Buchsbaum; Chris Lucas 001 (CogSci, 2021)

Exploring Causal Overhypotheses in Active Learning. - Chentian Jiang; Chris Lucas 001 (CogSci, 2021)

Recovering human category structure across development using sparse judgments. - Pablo León-Villagrá; Isaac Ehrlich; Chris Lucas 001; Daphna Buchsbaum (CogSci, 2021)

Modelling Recognition in Human Puzzle Solving. - Ben Prystawski; Rebekah Gelpi; Chris Lucas 001; Daphna Buchsbaum (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)

Flower Detection Using Object Analysis: New Ways to Quantify Plant Phenology in a Warming Tundra Biome. - Karol Stanski; Isla H. Myers-Smith; Christopher G. Lucas (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021)

Bayesian Optimisation for Active Monitoring of Air Pollution. - Sigrid Passano Hellan; Christopher G. Lucas; Nigel H. Goddard (AAAI, 2022)

Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation. - Verna Dankers; Christopher G. Lucas; Ivan Titov 001 (ACL (1), 2022)

Uncovering children's concepts and conceptual change. - Pablo León-Villagrá; Isaac Ehrlich; Chris Lucas 001; Daphna Buchsbaum (CogSci, 2022)

Uncovering Childrens' Category Representations with MCMCP. - Pablo León-Villagrá; Isaac Ehrlich; Chris Lucas 001; Daphna Buchsbaum (CogSci, 2022)

The logic of guesses: how people communicate probabilistic information. - Tadeg Quillien; Chris Lucas 001 (CogSci, 2022)

Dynamic Strategy Selection in Active Function Learning. - Nayan Saxena; Rebekah Gelpi; Daphna Buchsbaum; Chris Lucas 001 (CogSci, 2022)

Dissecting causal asymmetries in inductive generalization. - Zeyu Xia; Bonan Zhao 001; Tadeg Quillien; Chris Lucas 001 (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)

A Human-Centric Method for Generating Causal Explanations in Natural Language for Autonomous Vehicle Motion Planning. - Balint Gyevnar; Massimiliano Tamborski; Cheng Wang 023; Christopher G. Lucas; Shay B. Cohen; Stefano V. Albrecht (CoRR, 2022)

Actively learning to learn causal relationships. - Chentian Jiang; Christopher G. Lucas (CoRR, 2022)

Characterizing Shifts in Strategy in Active Function Learning. - Rebekah Gelpi; Caiqin Zhou; Chris Lucas 001; Daphna Buchsbaum (CogSci, 2023)

A rational model of spatial neglect. - Tianwei Gong; Bonan Zhao 001; Robert D. McIntosh; Chris Lucas 001 (CogSci, 2023)

Charting children's fruit categories with Markov-Chain Monte Carlo with People. - Pablo León-Villagrá; Isaac Ehrlich; Chris Lucas 001; Daphna Buchsbaum (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)

Selective imitation on the basis of reward function similarity. - Max Taylor-Davies; Stephanie Droop; Chris Lucas 001 (CogSci, 2023)

Non-Compositionality in Sentiment: New Data and Analyses. - Verna Dankers; Christopher Lucas 001 (EMNLP (Findings), 2023)

Causal Social Explanations for Stochastic Sequential Multi-Agent Decision-Making. - Balint Gyevnar; Cheng Wang 023; Christopher G. Lucas; Shay B. Cohen; Stefano V. Albrecht (CoRR, 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)

Bayesian Optimisation Against Climate Change: Applications and Benchmarks. - Sigrid Passano Hellan; Christopher G. Lucas; Nigel H. Goddard (CoRR, 2023)

DreamDecompiler: Improved Bayesian Program Learning by Decompiling Amortised Knowledge. - Alessandro B. Palmarini; Christopher G. Lucas; N. Siddharth 001 (CoRR, 2023)

How the level sampling process impacts zero-shot generalisation in deep reinforcement learning. - Samuel Garcin; James Doran; Shangmin Guo; Christopher G. Lucas; Stefano V. Albrecht (CoRR, 2023)

Balancing utility and cognitive cost in social representation. - Max Taylor-Davies; Christopher G. Lucas (CoRR, 2023)

Data-driven Prior Learning for Bayesian Optimisation. - Sigrid Passano Hellan; Christopher G. Lucas; Nigel H. Goddard (CoRR, 2023)

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

Causal Explanations for Sequential Decision-Making in Multi-Agent Systems. - Balint Gyevnar; Cheng Wang 023; Christopher G. Lucas; Shay B. Cohen; Stefano V. Albrecht (AAMAS, 2024)

DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design. - Samuel Garcin; James Doran; Shangmin Guo; Christopher G. Lucas; Stefano V. Albrecht (ICML, 2024)

Bayesian Program Learning by Decompiling Amortized Knowledge. - Alessandro B. Palmarini; Christopher G. Lucas; N. Siddharth 001 (ICML, 2024)

ICED: Zero-Shot Transfer in Reinforcement Learning via In-Context Environment Design. - Samuel Garcin; James Doran; Shangmin Guo; Christopher G. Lucas; Stefano V. Albrecht (CoRR, 2024)

Enabling robots to follow abstract instructions and complete complex dynamic tasks. - Ruaridh Mon-Williams; Gen Li 008; Ran Long; Wenqian Du 004; Chris Lucas 001 (CoRR, 2024)

Automating the Practice of Science - Opportunities, Challenges, and Implications. - Sebastian Musslick; Laura Bartlett; Suyog H. Chandramouli; Marina Dubova; Fernand Gobet; Thomas L. Griffiths 001; Jessica Hullman; Ross D. King; J. Nathan Kutz; Christopher G. Lucas; Suhas Mahesh; Franco Pestilli; et al. (CoRR, 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)

Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning. - Samuel Garcin; Trevor McInroe; Pablo Samuel Castro; Christopher G. Lucas; David Abel; Prakash Panangaden; Stefano V. Albrecht (ICLR, 2025)

Embodied large language models enable robots to complete complex tasks in unpredictable environments. - Ruaridh Mon-Williams; Gen Li 008; Ran Long; Wenqian Du 001; Christopher G. Lucas (Nat. Mac. Intell., 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)

Integrating Counterfactual Simulations with Language Models for Explaining Multi-Agent Behaviour. - Balint Gyevnar; Christopher G. Lucas; Stefano V. Albrecht; Shay B. Cohen (CoRR, 2025)