Accession Number ADA581713
Title Collaborative 20 Questions Model for Target Search with Human-Machine Interaction.
Publication Date May 2013
Media Count 6p
Personal Author B. M. Sadler I. A. Hero T. Tsiligkaridis
Abstract We consider the problem of 20 questions with noise for collaborative players under the minimum entropy criterion in the setting of stochastic search, with application to target localization. First, assuming conditionally independent collaborators, we characterize the structure of the optimal policy for constructing the sequence of questions. This generalizes the single player probabilistic bisection method for stochastic search problems. Second, we prove a separation theorem showing that optimal joint queries achieve the same performance as a greedy sequential scheme. Third, we establish convergence rates of the mean-squared error (MSE). Fourth, we derive upper bounds on the MSE of the sequential scheme. This framework provides a mathematical model for incorporating a human in the loop for active machine learning systems.
Keywords Automated target recognition
Automation
Computerized simulation
Convergence
Convergence rate
Entropy
Entropy reduction
Estimates
Greedy sequential query design
Human gain ratio
Human in the loop
Human-computer interactions
Human-machine interactions
Humans
Interactions
Learning machines
Man computer interface
Man machine systems
Noisy query-response models
Optimal joint query design
Optimal query policy
Position finding
Stochastic processes
Symposia
Target detection
Target localization


 
Source Agency Non Paid ADAS
NTIS Subject Category 72F - Statistical Analysis
62 - Computers, Control & Information Theory
63 - Detection & Countermeasures
95D - Human Factors Engineering
Corporate Author Michigan Univ., Ann Arbor. Dept. of Electrical Engineering and Computer Science.
Document Type Technical report
Title Note Conference paper.
NTIS Issue Number 1325
Contract Number W911NF-11-1-0391

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