Gatti, C. J. & Embrechts, M. J. (2014). An application of the temporal difference algorithm to the truck backer-upper problem. In Proceedings of the
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges, Belgium, 23–25 April. Bruges, Belgium: ESANN.
Gatti, C. J., Embrechts, M. J., & Linton, J. D. (2013). An empirical analysis of reinforcement learning using design of experiments. In Proceedings of the
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges, Belgium, 24–26 April (pp. 221–226). Bruges, Belgium: ESANN.
Loeppky, J. L., Sacks, J., & Welch, W. J. (2009). Choosing the sample size of a computer experiment: A practical guide. Technometrics, 51(4), 366–376.
Nguyen, D. & Widrow, B. (1990a). Neural networks for self-learning control systems. IEEE Control Systems Magazine, 10(3), 18–23.
Nguyen, D. & Widrow, B. (1990b). The truck backer-upper: An example of self-learning in neural networks. In Miller, W. T., Sutton, R. S., & Werbos, P. J. (Eds.), Neural Networks for Control. Cambridge, MA: MIT Press.
Patist, J. P. & Wiering, M. (2004). Learning to play draughts using temporal difference learning with neural networks and databases. In Proceedings of the 13th Belgian-Dutch Conference on Machine Learning, Brussels, Belgium, 8–9 January (pp. 87–94). doi: 10.1007/978-3-540-88190-2_13
Schoenauer, M. & Ronald, E. (1994). Neuro-genetic truck backer-upper controller. In Proceedings of the IEEE Conference on Computational Intelligence, Orlando, FL, 27 June–2 July (Vol. 2, pp. 720–723). doi: 10.1109/ICEC.1994.349969
Tesauro, G. (1992). Practical issues in temporal difference learning. Machine Learning, 8(3–4), 257–277.
Thrun, S. (1995). Learning to play the game of Chess. In Advances in Neural Information Processing Systems 7 (pp. 1069–1076). Cambridge, MA: MIT Press.
Thrun, S. & Schwartz, A. (1993). Issues in using function approximation for reinforcement learning. In Mozer, M., Smokensky, P., Touretzky, D., Elman, J., & Weigand, A. (Eds.), Proceedings of the 4th Connectionist Models Summer School, Pittsburgh, PA, 2–5 August (pp. 255–263). Hillsdale, NJ: Lawrence Erlbaum.
Vollbrecht, H. (2003). Hierarchical reinforcement learning in continuous state spaces. Unpublished PhD dissertation, University of Ulm, Ulm, Germany.
Wiering, M. A. (2010). Self-play and using an expert to learn to play backgammon with temporal difference learning. Journal of Intelligent Learning Systems & Applications, 2(2), 57–68.
Wiering, M. A., Patist, J. P., & Mannen, H. (2007). Learning to play board games using temporal difference methods (Technical Report UU–CS–2005–048, Institute of Information and Computing Sciences, Utrecht University). Retrieved from http://www.ai.rug.nl/mwiering/group/articles/learning_games_TR.pdf.