Intelligent Software Agents Lab
The Robotics Institute
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213-3890 (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
Communication
•Seeking information from all available
sources
•Passing information to the appropriate
persons before being asked
•Providing “big picture” situation updates
•Using proper phraseology
•Providing complete internal and
external reports
•Avoiding excess chatter
•Ensuring communications are audible
and ungarbled
Supporting Behavior
Team Initiative/Leadership
•Correcting team errors
•Providing and requesting backup or
assistance when needed
•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 1
User 2
User u
Goal and Task
Specifications
Results
Interface Agent 1
Interface Agent 2
Interface Agent i
Tasks
Solutions
Task Agent 1
Info & Service
Requests
Task Agent 2
Information Integration
Conflict Resolution
Middle Agent 2
Advertisements
Information
Agent 1
Queries
Task Agent t
Info
Source 1
Replies
Information
Agent n
Answers
Info
Source 2
Info
Source m
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
T SCORE: 1200
I SCORE : 1950
Time : 00:14:25
OPER
A
B
C
Individual Agent
000
*
*
270
*
*
*
* * * *
*
*
*
*
* **
* *
*
**
*
*
090
Agent Window
--TYPESpeed:
27
Climb/Dive : -366
Signal
--CLASSBearing:
Origin:
Range:
Red_Sea
1.4
--INTENTCountermeasures:
None
Electronic Warfare:
*
180
Missile Lock : Clean
Radius : 50 nm
Hooked Target : 35
Individual Memory
CoABS Control of Agent-Based Systems
NEO
Non-combatent Evacuation Operation
TIE3
Technical Integration Experiment 3