1. Electric Elves: Towards Multi-Agents-Facilitated Human Organizations
Milind Tambe Craig Knoblock Yolanda Gil
Hans Chalupsky David Pynadath Tom Russ
Funded by DARPA COABS

2. Electric Elves
Agents revolution: agents have proliferated in human organizations
Personal assistants: Gather information, manage , shopping…
Control resources: Building temp, software tools, …
Next step: Dynamic agent teams facilitate entire organizations
Teams function 24/7
Agent proxies for humans, helping:
Routine coordination in organizations
Coherent/robust actions to attain organizational goals
Swift reaction to crises
E.g., Coordinate move of personnel, equipment to crisis site
Results applicable to many organizations: military, business,…

3. Illustrative Tasks from USC/ISI
Demonstration in Washington, DC:
Rapid team formation: People flying out, support at ISI
Team planning: Travel arrangements, shipping equipment
Team plan monitor/repair: Team member becomes ill, flights delayed, equipment breakdown
Hosting visitors at ISI
Team plans/repair: Schedule visit; monitor/reschedule
Help at conferences/technical meetings
Team formation/monitor: Arrange meeting with other researchers
Facilitate routine organizational activities

4. Potential Elves Applications
Military crisis response
Teaming/coordination of military units/equipment
NIMA & MITRE
MITRE has suggested deployment of Elves, for transitions to NIMA, others…
Fits well with NIMA scenario requirements
IDA “PSYOP” analysis
IDA proposed Elves for coordinating analysts & tools
Interest from NASA (e.g., space station)

5. Current Focus: Elves in One Research Group
Mixed ~15 agent team:
Agent proxies for 9 researchers (called “Friday”)
Interfaces: PDA/GPS, WAP phones, workstation, fax, speech
Agent proxy for a project assistant
Information agents, schedulers, matchers…
Agent proxies run 24/7
First deployment in a real organization
Help us with real tasks
Coordinate meetings (reschedule if delays, cancel)
Decide presenters at research meetings (via auctions)
Track people (
Order our meals

6. Research Challenges
Teamwork and adjustable autonomy in teams [Teamcore]
Data source verification and reinduction [Ariadne]
Hybrid logic and topic-based matching [Loom]
Matchmaking for complex agents [Expect]
Dynamic team formation (e.g., via auctions)
Human organization norms: authorities, permissions etc
Scale up complexity, number, and heterogeneity
Rapid incorporation of new agents
Robustness and adaptability of agents
Widespread substitutability of agents

7. Focusing on One Research Topic: Adjustable Autonomy in Teams
Proxies for users: Teamwork with others, while serving human users
Adjustable autonomy: “Dynamically adjust agent’s autonomy”
Autonomous action on behalf of humans reduces burden, but…
Proxies face significant uncertainty, e.g., how hungry?
Errors in autonomous actions may be costly
Reduce autonomy, transfer control to humans in critical situations
Teams raise novel challenges for adjust autonomy!
Previous work: Individual agent/user interactions
With teams, an agent must serve the user AND the team
E.g., Cannot wait for user input: causes team miscoordination
Pursuing an approach based on Markov Decision Processes

8. Elves Architecture Overview: Agents Running on Agent Grid
Flight Monitor
Schedule
Extractor
Flight
info
Interest
Matcher
Meet
maker
Scheduler
agent
Capability
Matcher
Teamcore
Interest
Finder
Ariadne
Paper
Titles
abstract
Research
Publication
agent
Loom
Expect

9. Elves Architecture Overview: Teamcore Proxies on Agent Grid
Bids for Auctions:
Tambe: Capable, Willing
Pynadath: Capable, ….
AGENT GRID
Flight Monitor
Teamcore
proxy
Teamcore
proxy
Teamcore
proxy
Schedule
Extractor
Flight
info
Interest
Matcher
Teamcore
proxy
Teamcore
proxy
Teamcore
proxy
Meet
maker
Scheduler
agent
Capability
Matcher
Teamcore
Interest
Finder
Ariadne
Paper
Titles
abstract
Research
Publication
agent
Loom
Expect

10. Elves in Use: Reschedule Meetings
Personalize

11. Friday Ordering Dinner
“ More & More computers are ordering food,…
we need to think about marketing” Subway owner

12. Elves in Use: Wireless Devices
WAP Phone
PALM VII
+ GPS

13. Elves Results
Teamcore proxies 24/7, 6 month deployment in a real organization
Use of Elves virtually eliminated in group about delays, …
Use of Elves also eliminted about scheduling talks
Elves used to order 54 meals, 1.4 people served on avg per order
Num meetgs
Total reschedule
Auto reschedule
Human reschedule
1128
285
235 50
# meet
Auto decisions
Max bids
Avg bids
Auto winner bids 8 6 9
6.2
<capable,willing>
<not capable,willing>

14. Electric Elves: 24/7 Run in a Real Organization

15. USA Today Article

16. Summary
Unique experiment: 24/7 agent teams deployed in a real organization
Help in daily organization activities, relevant to other organizations
Some lessons:
Real-world application critical: Provided real data & challenges
Agent grid: Allows interoperation despite different platforms/language
Adaptability: Critical to dealing with a changing environment
Working together: Elves collaboration accomplished more

17. Future Work
Research:
Scale-up to ~100 agents (ISI’s Intelligent Systems Division)
Versatile interfaces with humans for tasking
Human organizations and norms
Automated team self-repair and learning
Privacy
Security
Future collaborations:
NIMA/MITRE
IDA for PSYOPS
NASA…

18. Next Steps: Large-scale Virtual Organizations
Virtual community dedicated to a common goal
Brings together specialized skills/resources;
No one organization possesses required skill
Organizations formed from elements from multiple organizations
People, agents, software/computational resources, equipment,.. .
Apply to rescue in large-scale urban disasters, e.g., earthquakes
Collaborate with international efforts on
Robotic Rescue (e.g., simulate Kobe quake)
Collaborate with SCEC
Bring together agent & computational grid

19. THANK YOU

20. Electric Elves Novelty: Teamwork in Teamcore Proxies
Teamcore proxies use a general teamwork model “STEAM”
Domain independent, reusable rules of teamwork
Explicitly outline team member’s responsibility in teamwork
Used in helicopter combat simulations, RoboCup Soccer, …
Now in Teamcore proxies to team up heterogeneous agents
Teamcore: Reduce development cost in building teams
Teams tasked via high-level team-oriented programs (TOP)
TOP specifies team plans to be executed, but not coordination
Teamcore proxies automatically execute required coordination
Maintain coherence in team, but with selective communication
Reorganize roles via substitution if a role fails

21. STEAM Rules in Teamcore: ExampleIf
Agent A1’s private state contains a fact F
AND
Fact F matches an achievement condition AC of a team plan
Fact F is not currently mutually believed…
THEN
Create possible communicative goal to communicate fact F to team
300 rules: Joint Intentions (Cohen/Levesque) & SharedPlans (Grosz)
Actual implementation, with modifications to theories proposed
Continue to push development of general teamwork theories

22. Novel Issues in Adjustable Autonomy
Novel challenge: Serve individual & team simultaneously
Challenge 1: Transferring autonomy control difficult with teams
If agent transfers control & waits for user input: miscoordinate
Unlike individual user-agent systems, cant wait for input
If no transfer control, no user input & act uniformed, then fail
Challenge 2: Ensuring desirable team-level decisions
Despite appropriate individual-level actions, team-level failures
Challenge 3: “Safe learning” for guaranteed behavior

23. Adjustable Autonomy (Cont)
Initially: Use C4.5 decision trees (Inspired by CAP [Mitchell, 94])
Learn user preferences, e.g., if ISI, 5 min to meet, delay 15
Learn whether to transfer autonomy control to user or not
Despite initial success some dramatic failures
Cancelled meeting with division director, automatically volunteered for presentation, meeting delayed to 8 pm or 9 pm…
Now: Autonomy policies using markov decision processes (MDP)
Explicitly reason with cost & uncertainty in transferring control
Not rigidly commit to decisions of transferring autonomy
Don’t take incorrect action if high risk; change coordination
E.g., Delay a meeting to get more time for user input

24. Elves in Use: An MDP Autonomy Policy in Use
Visitor at ISI, picked up at 9:00 AM from LAX for 9:30 meeting (9/11)
09/10/00 21:30: Prefer wait in {Time: 'Early', Location: 'not ISI'}
09/11/00 09:15: Prefer wait in {Time: -15, Location: 'not ISI’}
09/11/00 09:25: Prefer delay_5 in {Time: -5, Location: 'not ISI‘}
Time=9:23:16, Latitude=N ,Longitude=W
09/11/00 09:25: Asking...
09/11/00 09:30: Prefer delay_15 in {Time: 0, Location: 'not ISI‘}
Time=9:27:20, Latitude=N ,Longitude=W
09/11/00 09:25: Asking...
09/11/00 09:35: Prefer delay_15 in {Time: 5, Location: 'not ISI'}
Time=9:33:11, Latitude=N ,Longitude=W …
09/11/00 09:35: Acting to delay meeting 15 minutes

25. Electric Elves in Use: General Observations
Multi-agent 24/7 deployment in a real organization
Assists us in our daily activities
No s have been sent within group about delays, cancels,…
No s about scheduling talks at research meeting recently
Web page locator helps quickly locate individuals
Mobile devices keep us informed about schedule, meet status…
Friday not passive: gets us to the meeting on time
Ordering lunch ahead is time saver, and a nice surprise

26. Electric Elves in Use: Research Talks Auction
Does not require all bids to be in; the highest bid may not be 1,1
Meeting
Date
Num of
bids
Highest
Bid
Autonomous
Decision?
7/6/2000 7
Scerri <1,1> No
7/20/2000 8
Yes
7/27/2000
Kulkarni <0,1>
8/03/2000
Nair <1,1>
8/31/2000 4
Tambe <1,1>
9/21/2000 3
Visitor <-,->
10/31/2000
Tambe<1,1>

27. Electric Elves in Use: Meeting Data

28. Electric Elves: Some Experiments
If likelihood of user response
higher: Agents will ask more
If cost of asking users higher:
Agents will ask less

29. Focusing in on a Month (June)
Number of messages
June, 2000

30. Synergies Teamcore roles assigned using Phosphorus
Teamcore uses capabilities matcher to determine speakers for meetings
Teamcore proxies access on-line sources through Ariadne wrappers
Agents make decisions based on people’s calendars, flight schedules, etc.
Ariadne’s wrappers and IR used in PowerLoom interest matcher
Matcher’s KB identifies people’s interests from publications

31. Agent Organization is Grounded in the Real World
On-line information sources
Flight schedules, restaurants, etc.
Calendar information
“Sensors” and “actuators”
GPS, “finger”, etc.
Postpone/cancel meetings, faxes, etc.
Interaction with people
Communicate through personal portable devices
Support routine tasks

32. Elves in Use: Auctions
PAUL SCERRI
WILL BE THE PRESENTER
FOR TEAMCORE
Meeting on 7/20/2000
If presenter cannot attend the meeting, then substitute