rmax

Rmax is a term used in different domains. In computer science, R-MAX is a model-based reinforcement learning algorithm proposed by Brafman and Tennenholtz. The core idea is optimistic initialization: all unknown state-action pairs are assumed to have the maximum possible reward and transition probability, encouraging exploration. The agent builds a model of the environment and plans with that model to derive a policy. R-MAX has theoretical guarantees: it achieves near-optimal performance with high probability and has polynomial sample complexity in the size of the state and action spaces.

In construction and building materials, Rmax is a brand name used for insulation products, including spray polyurethane foam and related solutions, aimed at improving energy efficiency in buildings. Products marketed under this name vary by region and supplier, but they are generally intended for applications in building envelopes and insulation systems.

Other uses: the acronym may appear in various technical contexts; as with many product or algorithm names, the meaning of "Rmax" depends on context. Because there is no single universal definition, it is best interpreted from the surrounding material or documentation.