DARPA CoABS Project: NEO TIEs March 11, 1999 briefing Onn Shehory Carnegie Mellon University NEO...

DARPA CoABS Project:NEO TIEs

March 11, 1999 briefingOnn Shehory

Carnegie Mellon University

NEO TIEs coordinator: Katia Sycara

D.C. 1999: NEO TIEs Briefing

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Outline

• Goals of the CoABS project

• What NEO TIEs are

• How NEO TIEs address the goals

• The NEO problem domain

• TIEs details:– Participants– Components and interaction– Scientific claims


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CoABS High-level Goals

• Exploit the advantages of agent technology for military goals:

– Information gathering and filtering

– Mission planning

– Execution monitoring

• Develop and standardize infrastructure for agent based systems, to support:– Inter multi-agent-system synergy

– Integration of legacy systems via “agentification”

– Scalability of agent based systems

– Services (aka grid services) for agent activity and interoperation


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What are NEO TIEs?• Non-combatant Evacuation Operation:

– Requires information from multiple, multi-modal sources, may change dynamically, be unreliable

– Requires time-critical (re-) planning under uncertainty

– Collaboration among distributed humans, machines

– Plan execution monitoring

• Agent Technology Integration Experiments aim at:– Demonstrating agent support for NEO activity by

• Exploiting agent technology for information gathering, user interfacing and collaboration

• Automating and speeding up critical planning and monitoring

– Interoperation with legacy components (e.g. military air lift planner such as CAMPS) for NEO


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Do NEO TIEs address goals?

• The 3 NEO TIEs do– Use existing agents, MAS, services, legacy systems

– Make them interoperate: resolve ACL conflicts, build interoperability agents

– Enhance human/MAS collaboration/interfacing

– Integrate agent and legacy (re-) planning

– Demonstrate robustness via agent substitutability

• They do not– Evacuate (but may plan for, monitor and display it)

– Take the critical decisions (but may advise)


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Grid by-products of TIEs

• Translation (e.g. RETSINA - OAA)

• Visualization of multi-agent activity

• Support for different types of simulators

• Networking infrastructure

• Language/tools for use of GRID services

• Service description languages (e.g. LARKS)


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The NEO problem domain• Location: Kuwait city. Time: 2005

• Iraq not a threat, reduced military presence in mideast

• Congress in Kuwait city on ecology & oil conservation

• Unrest:– Night explosion at the conference center - no casualties

– Terrorist group issues threat against attendees, American, etc.

• US activity:– Ambassador orders evacuations (smaller numbers)

– AMC plans large evacuation

– Joint Force Commander involved (plan, secure evacuation routes)


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TIE 1: Helicopter Evacuation

• Technical lead: Milind Tambe (ISI)

• Participants:– AVDS (Khosla/Thrun, CMU)– Ariadne (Minton/Knoblock, USC/ISI)– Helicopter agents (Tambe/Shen, USC/ISI)– Quickset (Phil Cohen, OGI)– RETSINA route planner (Sycara/Payne, CMU)– TEAMCORE (Tambe/Shen, USC/ISI)


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TIE 1: Scenario description

• Joint Forces Commander (JFC) uses Quickset to allocate landing zone (LZ) for helicopters in KWI

• Route planner plans from safe assembly point to LZ

• Helicopter agents simulate transport using MODSAF

• Ariadne posts route facts. Route planner is prompted

• Quickset displays explosion

• Route planner provides new plan

• Helicopter agents modify their plans to the alternative

• Agent Visualization Database Server (AVDS) shows inter-agent connections


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TIE 1: Scientific ClaimsKey Questions

1. Can multi-agents be programmed at the team-level? (Team-Oriented Programming)

2. What are the key requirements for ACLs in team setting?

3. What are the key requirements for distributed monitoring & diagnosis to provide (guaranteed) robustness?


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Team-Oriented Programming(TOP)

Short-Term Goals

• Can TIE team be programmed by:

– Organization Hierarchy

– Team Procedures

– Current team goals and plans

– Automated coordination via TEAMCORE?

Long-Term Goals

• Extract general principles of “TOP” and build tools to facilitate “TOP”


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Distributed Monitoring, Diagnosis & Recovery

Short-Term Goals

• Explore appropriateness of existing techniques in TEAMCORE for distributed monitoring, diagnosis & recovery

• Build primitives for TEAMCORE agents to monitor domain-level agents

• Compile logs of failures

Long-Term Goals

• Extract general principles from compiled logs, add to existing TEAMCORE techniques


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ACLs for TEAMs

Short-Term Goals

• Explore shortcomings of existing ACLs for TEAMWORK

• Explore interoperation of OAA (Quickset) & TEAMCORE (KQML)

Long-Term

• Investigate efficiency of semantics of ACL (particularly for teamwork)

• Development of semantic interpretation bridge between TEAMCORE and OAA


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TIE 2: People finder/mover

• Technical lead: Steve Minton (ISI)

• Participants:– Ariadne (Minton/Knoblock, USC/ISI)– CTF (Paul Cohen, UMASS)– OAA & MMMap (Cheyer/Martin, SRI)– Prodigy & simulator (Veloso/Tucker, CMU)– WebTrader (Pazandak/Bannon, OBJS)


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TIE 2: Scenario description• JFC uses Assistant agent to order evacuation • OAA Multi-Modal Map (MMM) displays Kuwait city• Ariadne finds number/location of evacuees• WebTrader locates URLs of relevant info. for Ariadne• Prodigy plans routes for gathering evacuees• JFC sets assembly point, displayed by MMM• Evacuees’ locations are displayed on MMM• Assistant agent displays list of unlocated evacuees• Ariadne goes to Geocoder - converts addresses to lat/long• Capture The Flag (CTF) generates traffic obstructions• Ariadne monitors roads, posts status changes, Prodigy replans,

MMM re-displays updates


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Scientific Claims Technical ChallengesTIE 2

1. Coherent Communication

– Webtrader brokers information sources for Adriadne, it dynamically incorporates request “Address in Kuwait for conference attendees”

– Multiple translators glued together (e.g., speech (MMM) Menus)

2. Control

– Planner controls multiple simulated physical agents

– Planner responds to outside events

– Posting goals

3. Human in the loop


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TIE 3: Interoperability of MAS to support escalating NEO

• Technical lead: Katia Sycara (CMU)

• Participants:– CAMPS (Burstein, BBN)– OAA (Cheyer/Martin, SRI)– RETSINA (Sycara/Shehory, CMU)


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TIE 3: Overview

• Focus: flexibility, support of human collaboration during crisis

• Means: Interoperation and substitutability among distributed heterogeneous agents

• Human actors:– US ambassador to Kuwait

– JFC

– AMC


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TIE 3: Scenario• Ambassador, JFC discuss evacuation via Retsina UI

Messenger (UIM) and OAA MMM• JFC’s UIM monitors content, requests relevant info • WebMate provides text news, Maestro - video• Retsina flights agent begins providing schedules• OAA flights agent takes over when Retsina’s fails• UIM receives flights’ schedule and displays• OAA weather agent begins providing weather• Retsina weather agent takes over when OAA’s fails• Retsina route planner plans evacuation to KWI


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TIE 3: Scenario (continued)

• OAA phone agent provides info about roadblocks• Route planner replans to KWI airport• AMC rep uses a UIM to request CAMPS to

provide airlift plan from KWI• Retsina Visual Sensor Agent (VSA) reports an

explosion near KWI, displays it on MMM• JFC designate alternative abandoned airfield• Route planner replans to new destination• AMC via UIM requests a new plan from CAMPS• CAMPS returns a plan, presented by UIM


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1. Coherent communication of meaning between two heterogeneous MAS

2. Functional substitutability of agents

3. “Agentification” of legacy systems

4. Adaptivity at different levels:

– Interfaces

– MAS organization

– Single Agent

5. Collaboration

– human-human

– human-agent

– MAS

Scientific Claims Technical ChallengesTIE 3


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1. Coherent Communication of Meaning

Short-Term Goals

– Structure of interop agent

– Protocols of interop agent

Long-Term Goals

– Interoperation services for the GRID?

– ACL’s for the GRID

2. Functional Agent Substitutability

Short-Term Goals

– Provide languages and protocols for capability advertisement

Long-Term Goals

– Mechanisms for resolving mismatches of substitutable agent tasking and results

Scientific Claims - TIE 3


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3. “Agentification” of legacy systems

Short-Term Goals

– Providing wrapping mechanisms

Long-Term Goals

– Explore different mechanisms for agentification

4. Adaptivity/Robustness

Short-Term Goals

– Adaptive interface to user resources

– Organizational adaptivity through middle agents

Long-Term Goals

– Explore additional mechanisms for organizational adaptivity

Scientific Claims - TIE 3 (continued)


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5. Collaboration

– Human-Agent

Short-Term Goals

• Giving tasks to agents

Long-Term Goals

• Principles for functional role allocation between human and agent

– MAS

Short-Term Goals

• dynamic team formation

Long-Term Goals

• tradeoffs of different organizational structures (eg. Teams, hierarchies, heterarchies)

Scientific Claims - TIE 3 (continued)


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Closing remarks

• NEO TIEs are based on existing systems but– Add new functionality

– Require standardization (so far only partly achieved)

– Require interoperation (OAA, TEAMCORE, RETSINA lead this and already provide)

– Need communication infrastructure/protocol/language (RETSINA communicator, KQML, LARKS)

• The need for working, fielded MAS stimulates research, solutions (interop, visualization, etc)

DARPA CoABS Project: NEO TIEs March 11, 1999 briefing Onn Shehory Carnegie Mellon University NEO...

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