Behavioral Dynamics in the Cooperative Control of Mixed Human/Robotic Teams
Abstract
Results are reported on new methods to capture, model, represent, and ultimately understand human behavior in complex and possibly adversarial scenarios involving autonomous and semi-autonomous machine agents. Principles and models of cognitive and social psychology play a major role in the work. A particular objective is to develop a fundamental understanding of how humans and autonomous machine agents can operate as teams to efficiently accomplish mission objectives. An important focus of the research is on how human behavior differs from ideal decision makers due to social factors including pressure to conform, competitiveness, and other aspects of group dynamics. In addition to exploring cognitive and social psychological aspects of decision making, research is focused on formal approaches to communication through action. Understanding how gestures and structured motions can be used to communicate is essential to involving mobile smart machines as team members. An overarching goal is an understanding of how nuanced changes in collective motions of group of mobile agent serve to signal intentions of actions to come. The third major component of the research being reported discusses new results in task partitioning between humans and machines. The three research foci support a paradigm shift that supports the study of teams in which humans operate on parity with automatons.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 05, 2015
- Accession Number
- ADA612736
Entities
People
- David A. Castañón
- Debora Prentice
- Francesco Bullo
- John Baillieul
- Jonathan D. Cohen
- Juris Vagners
- Kristi Morgansen
- Naomi Ehrich Leonard
- Philip Holmes
Organizations
- Boston University