Reinforcement learning for autonomic network repair

Proceedings - International Conference on Autonomic Computing

Volumn , Issue , 2004, Pages 284-285

  Littman, Michael L ^a   Ravi, Nishkam ^a   Fenson, Eitan ^b   Howard, Rich ^b  

^a RUTGERS UNIVERSITY   (United States)

^b PnP Networks Inc   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTONOMIC NETWORKS; COST-SENSITIVE FAULT REMEDIATION (CSFR); REINFORCEMENT-LEARNING FORMULATION; WINDOWS XP;

COMPUTER NETWORKS; COMPUTER PROGRAMMING; COSTS; DECISION MAKING; FAULT TOLERANT COMPUTER SYSTEMS; GATEWAYS (COMPUTER NETWORKS); INFORMATION ANALYSIS; LEARNING ALGORITHMS; MATHEMATICAL MODELS; PERSONNEL; PROBABILITY; PROBLEM SOLVING; SERVERS; WORLD WIDE WEB;

LEARNING SYSTEMS;

EID: 4544266153     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICAC.2004.1301380     Document Type: Conference Paper

References (4)

1. [Bohra et al. 2004] Bohra, A.; Neamtiu, I.; Gallard, P.; Sultan, F.; and Iftode, L. 2004. Remote repair of OS state using backdoors. Technical Report DCS-TR-543, Rutgers Univ.
2. [Li et al. 2002] Li, X.; Martin, R.; Nagaraja, K.; Nguyen, T. D.; and Zhang, B. 2002. Mendosus: A SAN-based fault-injection test-bed for the construction of highly available network services. In First Workshop on Novel Uses of System Area Networks (SAN-1).
3. [Littman et al. 2004] Littman, M. L.; Ravi, N.; Fenson, E.; and Howard, R. 2004. An instance-based state representation for network repair. To appear in the Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI).
4. [Sutton & Barto 1998] Sutton, R. S., and Barto, A. C. 1998. Reinforcement Learning: An Introduction. The MIT Press.