Accession Number:
AD1017108
Title:
Stochastic Online Learning in Dynamic Networks under Unknown Models
Descriptive Note:
[Technical Report, Final Report]
Corporate Author:
University of California - Davis
Personal Author(s):
Report Date:
2016-08-02
Pagination or Media Count:
15
Abstract:
This research aims to develop fundamental theories and practical algorithms for distributed, robust, and real-time learning in dynamic tactical networks. The overall objective is to significantly move the frontiers of knowledge in stochastic learning in the classic multi-armed bandit by systematically relaxing traditionally adopted restrictive assumptions.
Descriptors:
- mesh networks
- signal processing
- information theory
- stochastic processes
- algorithms
- random variables
- ad hoc networks
- communication networks
- communication systems
- engineering
- information exchange
- information processing
- network topology
- networks
- computers
- department of defense
- dimensionality reduction
- mathematics
- probability
- spine
Subject Categories:
- Operations Research
- Cybernetics