Solomonoff's theory of inductive inference is a foundational concept in the field of machine learning and artificial intelligence, specifically dealing with how to make predictions about future observations based on past data. Proposed by Ray Solomonoff in the 1960s, the theory is grounded in algorithmic probability and establishes a formal framework for inductive reasoning.
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