A generalizing spatial representation for robot navigation with reinforcement learning

Proceedings of the Twentieth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2007

Volumn , Issue , 2007, Pages 586-591

  Frommberger, Lutz ^a  

^a UNIVERSITY OF BREMEN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS; ROBOT APPLICATIONS;

NAVIGATION STRATEGY; ROBOT NAVIGATION; STRUCTURAL KNOWLEDGE;

REINFORCEMENT LEARNING;

EID: 37349021722     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. Braga, A. P. S., and Araújo, A. F. R. 2003. A topological reinforcement learning agent for navigation. Neural Computing and Applications 12:220-236.
2. Busquets, D.; de Mántaras, R. L.; Sierra, C.; and Dietterich, T. G. 2002. Reinforcement learning for landmark-based robot navigation. In Proc. of AAMAS.
3. Glaubius, R.; Namihira, M.; and Smart, W. D. 2005. Speeding up reinforcement learning using manifold representations: Preliminary results. In Proc. of the IJCAI Workshop "Reasoning with Uncertainty in Robotics".
4. Goyal, R. K., and Egenhofer, M. J. 2000. Consistent queries over cardinal directions across different levels of detail. In Tjoa, A. M.; Wagner, R.; and Al-Zobaidie, A., eds., Proc. Workshop on Database and Expert System Applications.
5. Konidaris, G. D. 2006. A framework for transfer in reinforcement learning. In Proc. of the ICML-06 Workshop on Structural Knowledge Transfer for Machine Learning.
6. Lane, T., and Wilson, A. 2005. Toward a topological theory of relational reinforcement learning for navigation tasks. In Proc. of FLAIRS.
7. Mahadevan, S., and Maggioni, M. 2006. Value function approximation using diffusion wavelets and laplacian eigen-functions. In Neural Information Processing Systems.
8. Mukerjee, A., and Joe, G. 1990. A qualitative model for space. In Proc. of AAAI.
9. Sutton, R. 1996. Generalization in reinforcement learning: Successful examples using sparse tile coding. In Advances in Neural Information Processing Systems, volume 8.
10. Thrun, S., and Schwartz, A. 1995. Finding structure in reinforcement learning. In Advances in Neural Information Processing Systems, volume 7.
11. Watkins, C. 1989. Learning from Delayed Rewards. Ph.D. Dissertation, Cambridge University.