THIS GRANT IS A CONTINUATION OF (N00014-13-1-0341) MURI Embedded Humans: Provably Correct Decision Making for Networks of Humans and Unmanned Systems
Abstract
FY13 MURI funding is provided to begin research in: Modeling of Mixed Initiative Systems Stochastic Hybrid Systems (SHS) and Dynamic Bayes Nets (DBN) modeling for mixed initiative systems; common formalism, identification Cognitive models for human inference and analysis, human Interaction Data Clustering and Compression via multi-time and spatial scale action recognition models Modeling and Analysis of Human Behaviors and Activities of recall and precision of human operators for unmanned systems Communication and Control in Embedded Human Systems with models for attention and latencies in decision making, Impact of communication patterns on information diffusion Dynamic Assignment of Commands to Distributed Resources with Scalable Algorithms, State estimation algorithms in (D)BLOG, Multi-agent games and auctions Reduction of Uncertainty Propagation: Dual control tradeoffs between exploration and exploitation costs Distributed Optimization Under Uncertainty: Dual decomposition methods for robust optimization; Measures of stability of solutions to uncertain/varying optimization problems Provably Correct Mixed Initiative Systems - Partial Programs and Controller Synthesis: Scaling Up with solution concepts for POMDPs, POMGs, SHS synthesis, learning by Doing with partially observable POMGs, SHS Task TV Experimental Evaluation on Scenarios with Mixed Initiative Control of UAVs in cluttered urban Environments flying one quadrotor UAV in urban and indoor environments with dynamic obstacles.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 03, 2016
- Source ID
- N000141612206
Entities
People
- S. Shankar Sastry
Organizations
- Office of Naval Research
- United States Navy
- University of California Regents