1
Agents for collaboration in coalition environments
The Intelligent Software Agents LabKatia Sycara,
Principal Investigator
Ready-to-use software-integration-web technologies
CoABS Effective Coordination of Multiple
Intelligent Agents for Command and Control
Information Fusion for Command and Control from
Data to Actionable Knowledge and Decision AFOSR
PRET F49640-01-1-0542

• Technical Approach
• Develop new methods for high level information
  fusion
• Level 2 force recognition (recognizing groups)
• Level 3 inferring intent and threat
• Level 4 identifying acquiring needed
  information
• Developing simulation, display, and
  infrastructure for human-system interaction
  research
• Conducting verification and validation studies
  with human users

Operational Capability We have developed a suite
of interacting tools using the OTB military
simulation and the Unreal engine that allow us to
simulate the warfighters environment anywhere on
the battlefield. By combining ISR data, human
communications, and realistic tasks we can test
and evaluate conops and technologies for network
centric warfare. Without the complexity allowed
by these networked tools it would be impossible
to test our research hypotheses involving active
annunciation and information filtering and
distribution. Simulation tools developed in
this project have already been transitioned to
AFRL and ARL laboratories and are in use at
universities here and in Europe.
Automatically generated by CMUs terrain analysis
software
Subject Matter Experts MCOO (Modified Combined
Obstacle Overlay)
Agents construct and evaluate plans based on
multi-dimensional effects and interactions among
effects.
USARUrban Search and Rescue

• The RETSINA MAS Provides
• Dynamic team coordination, supporting teamwork
  between entities of varying capabilities
• Adjustable Autonomy for adaptively sharing
  control, responsibilities, and commitments at all
  task abstraction levels and by all types of team
  members (agents, robots, people)
• Abstraction-based tiered robot architecture that
  consists of incremental functional abstractions
  with real-time behavior based controllers at the
  lowest level, executive near-term explicit
  reasoning and scheduling at the middle level, and
  declarative planning and communication at the top
  level
• Scalability to larger or smaller numbers of
  robotic and software agents without affecting the
  team goal through loss of coordination, etc.

 
Project Goal To develop hybrid teams of
autonomous heterogeneous agentsincluding cyber
agents, robots, and humansthat intelligently
coordinate and plan to accomplish urban search
and rescue in disaster situations. We envision a
Multi-Agent System (MAS) in which humans, agents,
and robots work together seamlessly to provide
aid as quickly and safely as possible in the
event of an urban disaster.
http//www-2.cs.cmu.edu/softagents/project_grants
_NSF.html