Markov decision process
lastmod 2019-01-10created 2019-01-101 edits
A Markov Decision Process provides a mathematical framework for modeling decision making. The outcomes of decisions depend partly on the decision maker's choices but are also partly random. Markov decision processes are useful tools for a wide range of optimization problems solved by methods such as dynamic programming and reinforcement learning, and are widely used in areas such as robotics, automatic control, economics, and manufacturing. Markov decision processes were first devised at least as early as the 1950s, and the most central work on them is Ronald Howard's book Dynamic Programming and Markov Processes, published in 1960.