Intelligent Software Agents Lab The Robotics Institute Carnegie Mellon University 5000 Forbes Avenue Pittsburgh, PA (U.S.A.)

Agents helping Teams Our research goals have been to create mixed initiative systems to aid not only single users but also human teams Teams of agents help teams of users Reduce time for human teams to arrive at a decision Allow teams to consider a broader range of alternatives Enable teams to flexibly manage contingencies (replan, repair) Reduce individual and team errors Increase overall team performance

Task allocation and adjustable control Humans and agents have different competencies Difficulty of putting knowledge in the system Availability of robust representation schemes Performance requirements Shared mental model between humans and agents (could be learned through interaction) User Intent inferencing Reactive and proactive assistance Ignorance or failure can act as impetus to initiative

NAWCTSD TeamWork Dimensions Information Exchange Seeking information from all available sources Passing information to the appropriate persons before being asked Providing “big picture” situation updates Communication Using proper phraseology Providing complete internal and external reports Avoiding excess chatter Ensuring communications are audible and ungarbled Supporting Behavior Correcting team errors Providing and requesting backup or assistance when needed Team Initiative/Leadership Providing guidance or suggestions to team members Stating clear team and individual priorities.

Aiding & Cognitive Resources We might improve team performance by: 1.Making individual tasks easier freeing cognitive resources for team coordination tasks (supporting the task directly) 2.Aiding aspects of individual task exercised in coordination activities 3.Supporting team coordination tasks directly 4.Acting as a Team mate

RETSINA Functional Architecture User 1User 2User u Info Source 1 Info Source 1 Interface Agent 1 Interface Agent 2 Interface Agent i Task Agent 1 Task Agent 2 Task Agent t Middle Agent 2 Information Agent n Information Agent n Info Source 2 Info Source 2 Info Source m Info Source m Goal and Task Specifications Results SolutionsTasks Info & Service Requests Information Integration Conflict Resolution Replies Advertisements Information Agent 1 Information Agent 1 Queries Answers

MORSE: Aiding Nasa Teams Range Operations Tasks Range operations is about safe launches Humans in different stations around the world Agents coordinate with humans as team members and as team coordinators Agents monitor the environment and the activity of the humans and make: proactive problem solving suggestions (gather and present information about incursions) critiques of human activity (you want to handle incursion X instead of Y) calculations and projections (plume models) Experiments with human subjects Experiments with cognitive models

TANDEM Synthetic Radar Task Lab Simulation : moderate fidelity Aegis-based simulation Characteristics : Real-time, reactive & inflexible Task : Forced Pace, High Workload, Highly Dependent on Cooperation, Shared Information, Individual Action Cognitive Demands: High working memory load.. –Subjects must access from menus or obtain from teammates five parameter values and their classifications in order to reach each of their individual targeting decisions Studies : contrasted agent aiding for reducing memory load with assistance in communication and cooperation

Individual Agent * * * * * * * * * * * * * Time : 00:14:25 Agent Window --TYPE- Speed: 27 Climb/Dive : -366 Signal --CLASS- Bearing: Origin: Red_Sea Range: INTENT- Countermeasures: None Electronic Warfare: Missile Lock : Clean Hooked Target : 35Radius : 50 nm OPER A B C * * * * * * * * * * * Individual Memory T SCORE: 1200 I SCORE : 1950

CoABSControl of Agent-Based Systems NEONon-combatent Evacuation Operation TIE3Technical Integration Experiment 3