The dog that didn't bark: a Bayesian account of reasoning from censored data

这个项目旨在开发和测试一种新的归纳推理计算理论。归纳推理涉及将知识从已知实例扩展到新实例，是智能行为的核心组成部分。这个项目将解决认知机制，使人们能够根据观察到的和审查过的证据进行推断。该项目打算通过一项广泛的实验研究和计算建模计划来测试该模型。预期的好处包括加强对人类推理的理解，特别是在法医或金融证据评估等领域，在这些领域，数据审查很常见。

This project aims to develop and test a new computational theory of inductive reasoning. Inductive reasoning involves extending knowledge from known to novel instances, and is a central component of intelligent behaviour. This project will address the cognitive mechanisms that allow people to draw inferences based on both observed and censored evidence. The project intends to test the model through an extensive program of experimental investigation and computational modelling. The anticipated benefits include an enhanced understanding of human inference, especially in domains such as the evaluation of forensic or financial evidence, where data censoring is common.