An Online Optimization Approach for Multi-Agent Tracking of Dynamic Parameters in the Presence of Adversarial Noise.
Shahin ShahrampourAli JadbabaiePublished in: CoRR (2017)
Keyphrases
- multi agent
- dynamically updated
- real time
- online learning
- highly non linear
- noise level
- global optimization
- random noise
- fine tuning
- signal to noise ratio
- cooperative
- multi agent systems
- input data
- maximum likelihood
- parameter estimation
- parameter optimization
- particle filter
- multiagent systems
- dynamic optimization
- image statistics
- multiple agents
- sensitivity analysis
- appearance model
- object tracking
- motion analysis
- parameter space
- noisy data
- dynamic environments
- optimization criteria
- website