Policy Gradient Methods for Off-policy Control

Learning to predict by the methods of temporal differences

Richard S. Sutton · 1988

Earlier work this paper cites.

Q-learning

ChristopherJ.C.H. Watkins and Peter Dayan · 1992

Earlier work this paper cites.

Residual algorithms: Reinforcement learning with function approximation

Leemon Baird · 1995

Earlier work this paper cites.

Chattering in sarsa(lambda) - a cmu learning lab internal report

Geoffrey J. Gordon · 1996

Earlier work this paper cites.

Reinforcement Learning: An Introduction

Richard S. Sutton and Andrew G. Barto · 1998

Cited alongside, same era.

Policy gradient methods for reinforcement learning with function approximation

Richard S. Sutton, David McAllester, Satinder Singh, and Yishay Mansour · 2000

Cited alongside, same era.

Reinforcement learning with function approximation converges to a region

Geoffrey J. Gordon · 2001

Cited alongside, same era.

A convergent form of approximate policy iteration

Theodore J. Perkins and Doina Precup · 2003

Cited alongside, same era.

Gq(lambda): A general gradient algorithm for temporal-difference prediction learning with eligibility traces

Sutton R. S. Maei, H. R

Cited in the paper.

Toward off-policy learning control with function approximation

Szepesvari Cs. Bhatnagar S. Sutton R. S. Maei, H. R

Cited in the paper.

A convergent o(n) algorithm for off-policy temporal-difference learning with linear function approximation

Richard S. Sutton, Csaba Szepesvári, and Hamid Reza Maei

Cited in the paper.

Convergent temporal-difference learning with arbitrary smooth function approximation

Szepesvari Cs. Bhatnagar S. Precup D. Silver D. Sutton R. S. Maei, H. R · 2009

Later among the works it cites.

Fast gradient-descent methods for temporal-difference learning with linear function approximation

Richard S. Sutton, Hamid Reza Maei, Doina Precup, Shalabh Bhatnagar, David Silver, Csaba Szepesvári, and Eric Wiewiora · 2009

Later among the works it cites.

Policy evaluation with temporal differences: A survey and comparison

Christoph Dann, Gerhard Neumann, and Jan Peters · 2014

Later among the works it cites.