Effective Coordination of Multiple Intelligent Agents for Command and Control

1. Effective Coordination of Multiple Intelligent Agents for Command and Control The Robotics Institute Carnegie Mellon University PI: Katia Sycara http://www.cs.cmu.edu/~sycara http://www.cs.cmu.edu/~softagents Key Personnel: Onn Shehory Terry Payne

2. Current Situation • Vast amounts of data from distributed and heterogeneous sources • Uncertain and evolving tactical situation • Shrinking decision cycles • Decision makers distributed in space and time Katia Sycara

3. Overall Goal • To develop effective agent-based system technology to support command and control decision making in time stressed and uncertain situations Katia Sycara

4. Innovative Claims • Scalable, robust and adaptive coordination and control multi-agent strategies • Sophisticated individual agent control • Reusable and customizable agent components • Multi-agent infrastructure coordination tools and environment Katia Sycara

5. Research Objectives • Develop an adaptive, self-organizing collection of intelligent agents that interact with the humans and each other to • integrate information management and decision support • anticipate and satisfy human information processing and problem solving needs • perform real-time synchronization of domain activities • notify users and other each other about significant changes in the environment • adapt to user, task and situation Katia Sycara

6. Potential Impacts • Reduce time for commanders to arrive at a decision • Allow commanders to consider a broader range of alternatives • Enable commanders to flexibly manage contingencies (replan, repair) • Improve battle field awareness • Enable in-context information filtering Katia Sycara

7. What is an Agent? • A computational system that • has goals, sensors and effectors • is autonomous • is adaptive • is long lived • lives in a networked infrastructure • interacts with other agents Katia Sycara

8. RETSINA: Testbed for Agent-Based Systems • Continuing development of general purpose multi-agent infrastructure • Agents built from domain-independent, reusable components • Agent behaviors specified in declarative manner • New agent configurations easily built and empirically tested. Katia Sycara

9. Retsina Agent Architecture Katia Sycara

10. Retsina Functional Organization Katia Sycara

11. Technical Challenges • What coordination mechanisms are effective for large numbers of sophisticated agents? • What are the scaling up properties of these coordination mechanisms? • How do they perform with respect to dimensions, such as task complexity, interdependence, agent heterogeneity, solution quality? • What guarantees do these mechanisms provide regarding system stability and predictability of overall system behavior? • Do they mitigate against harmful system behaviors? • How to achieve effective human-agent coordination? Katia Sycara

12. Capability-Based Coordination • Open, uncertain environment: • Agents leave and join unpredictably • Agents have heterogeneous capabilities • Replication increases robustness • Agent location via Middle agents: • Matchmakers match advertised capabilities • Blackboard agents collect requests • Broker agents process both Katia Sycara

13. Capability-Based Coordination (cont) • Advertisement: • Includes agent capability, cost, etc. • Supports interoperability • Agent interface to the agent society independent of agent internal structure • We will test scale-up properties of capability-based coordination Katia Sycara

14. Middle Agent Types Capabilities Initially Known By Katia Sycara

15. Cooperation • Problems with current methods: • Mechanisms not tested in real-world MAS • Simulation size small (~20 agents) • Complex mechanism do not scale up • We will provide algorithms for scalability of cooperation mechanisms • Approach: • Very large systems (millions of agents): • Constant complexity cooperation method • Based on models of multi-particle interaction • Structural organization: • Relation of organization structure and autonomy • Effect on system flexibility, robustness, stability Katia Sycara

16. Cooperation - Solutions (continued) • Communication planning: • Change communication patterns to reduce eavesdropping risk • Bundle small message together • Use networks when less congested Katia Sycara

17. Competition and Markets • Limited resources result in competition • Approach: • Utilize financial option pricing: • Prioritize tasks by dynamic valuation • Allows flexible contingent contracting • Analysis of large MAS via economics methods • Combine our capability-based coordination with market mechanisms • Mechanism design: • Design enforceable mechanisms for self-interested agents • Resolve Tragedy of Commons by pricing schemes • Devise mechanisms to motivate truthful behavior Katia Sycara

18. Process for Experimentation 1. Formulation of the distributed coordination algorithm 2. Development of experimental infrastructure (eg: simulation tools, making appropriate modifications to RETSINA components) 3. Running the experiment and collecting statistics 4. Analysis of the results 5. Inter-mechanism evaluation; the results of the simulations of the various mechanisms will be compared to determine performance landscapes of the different coordination mechanisms Katia Sycara

19. Research Plan • Agent Control • mapping of task model and requirements to the appropriate coordination strategy • mapping of constraints of the environment, other agents and available resources to appropriate coordination strategy • experimental evaluation, analysis and refinement • Agent Coordination • design/refine coordination algorithm • implement appropriate experimental infrastructure • implement the coordination strategy and evaluate along different dimensions • analyze the results and refine algorithm design and experimental process Katia Sycara

20. Research Plan (contd.) • User-Agent Coordination • enhance the functionality of the current agent command language • develop and implement techniques for acquisition and maintenance of user tasks preferences and intentions • develop and implement protocols to enable an agent to accept task-related queries before, during or after task execution and generate natural descriptions of the unfolding execution of its plans • evaluate and refine • Information Management and Decision Support • develop mechanisms for information management (e.g., filtering, integration) in the context of the current problem solving task • develop mechanisms for in-context information monitoring and notification • evaluate and refine Katia Sycara

21. Major Project Deliverables • Prototype multiagent system that aids human military planners to perform effective “in context” information gathering, execution monitoring, and problem solving • reusable “agent shell” that includes domain independent components for representing and controlling agent functionality, so that agents can be easily produced for different types of tasks • effective multiagent coordination protocols, that are scalable, efficient and adaptive to user task and planning context • multi agent coordination infrastructure consisting of a suite of tools for reliable and low cost building and experimenting with flexible multiagent systems Katia Sycara