| The diversity effect in inductive reasoning depends on sampling assumptions BK Hayes, DJ Navarro, RG Stephens, K Ransom, N Dilevski Psychonomic Bulletin & Review 26, 1043-1050, 2019 | 34 | 2019 |
| How do people learn from negative evidence? Non-monotonic generalizations and sampling assumptions in inductive reasoning W Voorspoels, DJ Navarro, A Perfors, K Ransom, G Storms Cognitive psychology 81, 1-25, 2015 | 33 | 2015 |
| Sample size, number of categories and sampling assumptions: Exploring some differences between categorization and generalization AT Hendrickson, A Perfors, DJ Navarro, K Ransom Cognitive Psychology 111, 80-102, 2019 | 26 | 2019 |
| Leaping to conclusions: Why premise relevance affects argument strength KJ Ransom, A Perfors, DJ Navarro Cognitive science 40 (7), 1775-1796, 2016 | 23 | 2016 |
| People ignore token frequency when deciding how widely to generalize A Prefors, K Ransom, D Navarro Proceedings of the Annual Meeting of the Cognitive Science Society 36 (36), 2014 | 17 | 2014 |
| A cognitive analysis of deception without lying K Ransom, W Voorspoels, A Perfors, D Navarro Proceedings of the 39th Annual Conference of the Cognitive Science Society …, 2017 | 15 | 2017 |
| Do sequential lineups impair underlying discriminability? M Kaesler, JC Dunn, K Ransom, C Semmler Cognitive research: principles and implications 5, 1-21, 2020 | 12 | 2020 |
| Representational and sampling assumptions drive individual differences in single category generalisation K Ransom, AT Hendrickson, A Perfors, DJ Navarro Proceedings of the 40th annual conference of the cognitive science society, 2018 | 7 | 2018 |
| Where the truth lies: how sampling implications drive deception without lying K Ransom, W Voorspoels, D Navarro, A Perfors PsyArXiv, 2019 | 6 | 2019 |
| Generating an implementation of a parallel programming language from a formal semantic definition MJ Oudshoorn, CD Marlin, KJ Ransom Department of Computer Science, The University of Adelaide, 1993 | 5 | 1993 |
| Human-like property induction is a challenge for large language models SJ Han, KJ Ransom, A Perfors, C Kemp 44th Annual Conference of the Cognitive Science Society, 2022 | 4 | 2022 |
| Social meta-inference and the evidentiary value of consensus KJ Ransom, A Perfors, RG Stephens Proceedings of 43rd Annual Conference of the Cognitive Science Society, 2021 | 4 | 2021 |
| Supporting software reuse within an integrated software development environment (position paper) KJ Ransom, CD Marlin ACM SIGSOFT Software Engineering Notes 20 (SI), 233-237, 1995 | 4 | 1995 |
| What do our sampling assumptions affect: how we encode data or how we reason from it? KJ Ransom, A Perfors, BK Hayes, S Connor Desai Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022 | 3 | 2022 |
| Abstract data types: Converting from sequential to parallel MJ Oudshoorn, KJ Ransom, CD Marlin Australian Software Engineering Conference 1991: Engineering Safe Software …, 1991 | 3 | 1991 |
| Exploring the role that encoding and retrieval play in sampling effects. K Ransom, A Perfors CogSci, 946-952, 2019 | 1 | 2019 |
| Modelling systems that integrate programming language and environment mechanisms KJ Ransom, CD Marlin Proceedings 1995 Asia Pacific Software Engineering Conference, 274-281, 1995 | 1 | 1995 |
| An Integrated Environment for the Development and Analysis of Hard Real-Time Systems KJ Ransom, CD Marlin, W Zhao IFAC Proceedings Volumes 24 (2), 27-32, 1991 | 1 | 1991 |
| Source independence affects argument persuasiveness when the relevance is clear M Alister, A Perfors, KJ Ransom 44th Annual Conference of the Cognitive Science Society, 2022 | | 2022 |
| What interventions can decrease or increase belief polarisation in a population of rational agents? PD Howe, A Perfors, KJ Ransom Proceedings of the Annual Meeting of the Cognitive Science Society 43 (43), 2021 | | 2021 |
Andrew PerforsUniversity of MelbourneDirección de correo verificada de unimelb.edu.au
