Lambda‐Policy Iteration: A Review and a New Implementation

Abstract

In this paper we discuss -policy iteration, a method for exact and approximate dynamic programming. It is intermediate between the classical value iteration (VI) and policy iteration (PI) methods, and it is closely related to optimistic (also known as modied) PI, whereby each policy evaluation is done approximately, using a nite number of VI. We review the theory of the method and associated questions of bias and exploration arising in simulation-based cost function approximation. We then discuss various implementations, which oer advantages over well-established PI methods that use LSPE( ), LSTD( ), or TD( ) for policy evaluation with cost function approximation. One of these implementations is based on a new simulation scheme, called geometric sampling, which uses multiple short trajectories rather than a single innitely long trajectory.