Efficient distributed reinforcement learning through agreement

Distributed Autonomous Robotic Systems 8

Volumn , Issue , 2009, Pages 367-378

  Varshavskaya, Paulina ^a   Kaelbling, Leslie Pack ^a   Rus, Daniela ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURAL ROBOTS; MODULAR ROBOTS; ONLINE SYSTEMS; ROBOTICS;

AUTOMATIC CONTROLLERS; DISTRIBUTED IMPLEMENTATION; DISTRIBUTED REINFORCEMENT LEARNING; DISTRIBUTED ROBOTIC SYSTEMS; LEARNING ABILITIES; LOCAL INFORMATION; ON-LINE ADAPTATION; PARTIAL OBSERVABILITY;

REINFORCEMENT LEARNING;

EID: 84878551320     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-642-00644-9_33     Document Type: Conference Paper

References (16)

1. Baxter, J., Bartlett, P.L.: Infinite-horizon gradient-based policy search. J. of Artificial Intelligence Res. 15, 319-350 (2001)
2. Bertsekas, D.P., Tsitsiklis, J.N.: Parallel and Distributed Computation: Numerical Methods. Athena Scientific (1997)
3. Chang, Y.-H., Ho, T., Kaelbling, L.P.: All learning is local: Multi-agent learning in global reward games. In: Advances in Neural Information Processing Systems, Vol. 16 (2004)
4. Fernandez, F., Parker, L.E.: Learning in large cooperative multi-robot domains. Int. J. of Robotics and Automation 16(4), 217-226 (2001)
5. Guestrin, C., Koller, D., Parr, R.: Multiagent planning with factored MDPs. In: Advances in Neural Information Processing Systems, Vol. 14 (2002)
6. Hu, J., Wellman, M.P.: Multiagent reinforcement learning: Theoretical framework and an algorithm. In: Proc. Int. Conf. on Machine Learning, pp. 242-250 (1998)
7. Kok, J.R., Vlassis, N.: Collaborative multiagent reinforcement learning by payoff propagation. J. of Machine Learning Res. 7, 1789-1828 (2006)
8. Lynch, K.M., Schwartz, I.B., Yang, P., Freeman, R.: Decentralized environmental modeling by mobile sensor networks. IEEE Trans. on Robotics 24(3), 710-724 (2008)
9. Matarić, M.J.: Reinforcement learning in the multi-robot domain. Autonomous Robots 4(1), 73-83 (1997)
10. Moallemi, C.C., Van Roy, B.: Distributed optimization in adaptive networks. In: Advances in Neural Information Processing Systems, Vol. 15 (2003)
11. Moallemi, C.C., Van Roy, B.: Consensus propagation. IEEE Trans. on Information Theory 52(11) (2006)
12. Peshkin, L.: Reinforcement Learning by Policy Search. PhD thesis, Brown University (2001)
13. Schneider, J., Wong, W.-K., Moore, A., Riedmiller, M.: Distributed value functions. In: Proc. Int. Conf. on Machine Leanring (1999)
14. Tsitsiklis, J.N., Bertsekas, D.P., Athans, M.: Distributed asynchronous deterministic and stochastic gradient optimization algorithms. IEEE Trans. on Automatic Control AC-31(9), 803-812 (1986)
15. Varshavskaya, P., Kaelbling, L.P., Rus, D.: Distributed learning for modular robots. In: Proc. Int. Conf. on Robots and Systems (2004)
16. Varshavskaya, P., Kaelbling, L.P., Rus, D.: Automated design of adaptive controllers for modular robots using reinforcement learning. Int. J. of Robotics Res. 27(3-4), 505-526 (2008)