Philosophical Foundations for Probabilistic Inference and Probabilistic Prediction

概率推理和概率预测的哲学基础。这个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信息长度（MML）原则来极大地改进当前科学推理和科学预测的哲学解释。我们还将使用该理论来发展新的和令人兴奋的答案，长期存在的问题，在科学哲学有关归纳，投射，私人语言，决定论和情报。基于MML原则的理论将证明竞争经典方法的明显不足，并将完全重塑哲学家思考贝叶斯推理理论的方式。

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.