Philosophical Foundations for Probabilistic Inference and Probabilistic Prediction

概率推理和概率预测的哲学基础。这一令人兴奋和创新的项目旨在为当代科学哲学奠定新的基础。我们将使用基本的最小消息长度(MML)原则来极大地改进当前对科学推理和科学预测的哲学解释。我们还将利用这一理论为科学哲学中有关归纳、可投射、私人语言、决定论和智力等长期存在的问题找到新的和令人兴奋的答案。基于MML原则的理论将证明相互竞争的经典方法的明显不足，并将完全重塑哲学家对贝叶斯推理理论的思考方式。

Philosophical Foundations for Probabilistic Inference and Probabilistic Prediction. This exciting and innovative project aims to lay new foundations for contemporary philosophy of science. We shall use basic Minimum Message Length (MML) principles to vastly improve on current philosophical accounts of scientific inference and scientific prediction. We shall also use the theory to develop new and exciting answers to longstanding problems in philosophy of science concerning induction, projectability, private languages, determinism and intelligence. A theory based on MML principles will demonstrate the clear inadequacies of competing classical approaches, and will completely reshape the way in which philosophers think about Bayesian theories of inference.