dr. Bram Bakker
	IAS, Informatics Institute University of Amsterdam Kruislaan 403 1098 SJ  Amsterdam The Netherlands phone: +31 20 525 7524 fax: +31 20 525 7490	Research Publications Links Back to IAS people

Who am I?

I am a postdoctoral research fellow, working on machine learning. I am affiliated with the University of Amsterdam (UvA), specifically the Intelligent Autonomous Systems (IAS) group of the Informatics Institute.

IK BEN NIET DE PSYCHIATER BRAM BAKKER! Die zit hier.

Teaching

I am teaching the Decision Making in Intelligent Systems (DMIS) course. A website with slides and other information can be found here.

News

Research interests

• Sequential decision making
• Timeseries prediction
• Robotics
• Multi-agent systems
• Hierarchical methods

Publications

• Kok, J. R., 't Hoen, P. J., Bakker, B., and Vlassis, N. (2005). Utile Coordination: Learning interdependencies among cooperative agents. Proceedings of the IEEE Symposium on Computational Intelligence and Games  2005.
• Bakker, B. (2005). The concept of circular causality should be discarded. Commentary on Marc D. Lewis: Bridging emotion theory and neurobiology through dynamic system modeling. Behavioral and Brain Sciences, Vol. 28, p. 195-196. HTML version of my commentary. PDF of target paper + all commentary.
• Bakker, B., Zivkovic, Z, and Kröse, B. (2005). Hierarchical Dynamic Programming for Robot Path Planning. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, p. 3720-3725. PDF.
• Zivkovic, Z, Bakker, B., and Kröse, B. (2005). Hierarchical Map Building Using Visual Landmarks and Geometric Constraints. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, p. 7-12. PDF.
• Bakker, B., and Schmidhuber, J. (2004). Hierarchical Reinforcement Learning Based on Subgoal Discovery and Subpolicy Specialization. In F. Groen, N. Amato, A. Bonarini, E. Yoshida, and B. Kröse (Eds.), Proceedings of the 8-th Conference on Intelligent Autonomous Systems, IAS-8, Amsterdam, The Netherlands, p. 438-445. Abstract. Postscript. Zipped Postscript. PDF.
• Bakker, B., and Schmidhuber, J. (2004). Hierarchical Reinforcement Learning with Subpolicies Specializing for Learned Subgoals. In M. H. Hamza (Ed.), Proceedings of the 2nd IASTED International Conference on Neural Networks and Computational Intelligence, NCI 2004, Grindelwald, Switzerland, p. 125-130. Abstract. Postscript. Zipped Postscript. PDF.
• Bakker, B. (2004). The State of Mind: Reinforcement Learning with Recurrent Neural Networks. PhD thesis, Leiden University, January 2004.  Postscript. Zipped Postscript. PDF.
• Bakker, B., Zhumatiy, V., Gruener, G., and Schmidhuber, J. (2003). A Robot that Reinforcement-Learns to Identify and Memorize Important Previous Observations. In Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS2003, p. 430-435. Abstract. Postscript. Zipped Postscript. PDF.
• Bakker, B., and Schmidhuber, J. (2003). Hierarchical Reinforcement Learning Based on Automatic Discovery of Subgoals and Specialization of Subpolicies. In Proceedings of the 2003 European Workshop on Reinforcement Learning, EWRL 6, Nancy, France. Abstract. Postscript. Zipped Postscript. PDF.
• Bakker, B., Linåker, F., and Schmidhuber, J. (2002). Reinforcement Learning in Partially Observable Mobile Robot Domains Using Unsupervised Event Extraction. In Proceedings of the 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS2002, p. 938-943. Abstract. Postscript. Zipped Postscript. PDF.
• Bakker, B. (2002). Advantage(lambda) learning. Technical Report. Abstract. Postscript. Zipped Postscript. PDF.
• Bakker, B. (2002). Reinforcement Learning with Long Short-Term Memory. In T.G. Dietterich, S. Becker, and Z. Ghahramani (Eds.), Advances in Neural Information Processing Systems, 14. Cambridge, MA: MIT Press, p. 1475-1482. Abstract. Postscript. Zipped Postscript. PDF.
• Bakker, B. (2001). Reinforcement Learning with LSTM in Non-Markovian Tasks with Long-Term Dependencies. Technical Report. Abstract. Postscript. Zipped Postscript. PDF.
• Bakker, B. (2000). The Adaptive Behavior Approach to Psychology. Cognitive Processing, 1, 39-70. Abstract. Postscript. Zipped Postscript. PDF.
• Bakker, B., and de Jong, M. (2000). The Epsilon State Count. In J.-A. Meyer, A. Berthoz, D. Floreano, H. Roitblat, and S.W. Wilson (Eds.), From Animals to Animats 6: Proceedings of The Sixth International Conference on Simulation of Adaptive Behavior, 51-60, Cambridge, MA: MIT Press. Abstract. Postscript. Zipped Postscript. PDF.
• Bakker, B., and van der Voort van der Kleij, G. (2000). Trading off Perception with Internal State: Reinforcement Learning and Analysis of Q-Elman Networks in a Markovian Task. In S.-I. Amari, C.L. Giles, M. Gori, and V. Piuri (Eds.), Proceedings of the International Joint Conference on Neural Networks 2000, Vol. III, 213-218. Abstract. Postscript. Zipped Postscript. PDF.
• Bakker, B., and den Dulk, P. (1999). Causal Relationships and Relationships between Levels: The Modes of Description Perspective. In: M. Hahn and S.C. Stoness (Eds.) Proceedings of the Twenty-First Annual Conference of the Cognitive Science Society, pp. 43-48. Abstract. Postscript. Zipped Postscript. PDF.