Editing Algorithmic probability (section)

===Background===
Inductive reasoning, the process of predicting future events based on past observations, is central to intelligent behavior. Hutter formalized this process using Occam’s razor and algorithmic probability. The framework is rooted in Kolmogorov complexity, which measures the simplicity of data by the length of its shortest descriptive program. This concept underpins the universal distribution MM, as introduced by Ray Solomonoff, which assigns higher probabilities to simpler hypotheses.
Hutter extended the universal distribution to include actions, creating a framework capable of addressing problems such as prediction, optimization, and reinforcement learning in environments with unknown structures.