CoAX Stand-alone Contributions DARPA Briefing - November 2000 Dartmouth College, UMichigan, MIT Sloan, Coalition Agents eXperiment (CoAX)

CoAX Stand-alone ContributionsCoAX Stand-alone ContributionsDARPA Briefing - November 2000DARPA Briefing - November 2000

Dartmouth College, UMichigan, MIT Sloan, Dartmouth College, UMichigan, MIT Sloan,

Coalition Agents eXperiment (CoAX)Coalition Agents eXperiment (CoAX)http://www.aiai.ed.ac.uk/project/coax/http://www.aiai.ed.ac.uk/project/coax/

DARPADARPA

CoAX /Tech Briefing - 2

Stand-alone Stand-alone ContributionsContributions

Dartmouth Field Observation Agent Dartmouth Field Observation Agent MIT Robustness ServiceMIT Robustness Service Michigan Coordination Planning AidMichigan Coordination Planning Aid


• ActComm Project

• Dartmouth, Harvard, RPI, Illinois, ALPHATECH, Lockheed Martin

• Department of Defense Multidisciplinary University Research Initiative

• Developing a system to provide network access to soldiers in the field

• CoAX Goal

• Demonstrate the ease with which the large ActComm “legacy” system can be integrated with the rest of CoAX via the DARPA CoABS Grid

Field Observations (Dartmouth)



• Team of soldiers

• PDA’s

• Ad-hoc wireless networking

• Soldiers make observations.

• Ground and air traffic

• Personnel and equipment

• Buildings and other structures

• Observations fed into battle-planning systems (e.g., MBP) through the CoABS Grid.

• In the demo, a team of CoAX soldiers will make observations to correct Gao misinformation.


Observations

ObservationAgent

D’Agents API

GridAPI

I see a tank!

ObservationViewer

MBP

(9-month demo - standalone)

(18-month demo - integrated)

Query/Response

Registration/Update Stream




29-SEP-2012 13:47.56 OBSERVATION 0018 VEHICLE Observer : 16.35 N, 35.28 E, Elevation 530 m Sightline: 270 deg, 0 deg down, 2000 m Vehicle : Gao, flatbed truck, 3 axles, heading: 180, speed: 60 km/h Note : 12 soldiers in flatbed


The Challenge: The Challenge: Robust Agent Robust Agent CoalitionsCoalitions

Coalitions are open systemsCoalitions are open systems Dynamic membership, often novel partnersDynamic membership, often novel partners

Agents in open systems will be unreliableAgents in open systems will be unreliable Intermittent bugs (3 per 1000 lines in the best Intermittent bugs (3 per 1000 lines in the best

crafted code) as well as the possibility of malicecrafted code) as well as the possibility of malice Infrastructures can be unreliableInfrastructures can be unreliable

Current failure tolerance approaches are Current failure tolerance approaches are insufficientinsufficient Assume closed systems (e.g. mirroring)Assume closed systems (e.g. mirroring) Full rollbacks are unnecessarily inefficient for agentsFull rollbacks are unnecessarily inefficient for agents


The MIT Robustness The MIT Robustness ServiceService

Monitors agent ‘health’ via pollingMonitors agent ‘health’ via polling Responds to agent failure via intelligent task Responds to agent failure via intelligent task

cancellation & task re-announcementcancellation & task re-announcement Maintains reliability information (for failure Maintains reliability information (for failure

avoidance)avoidance) Designed for open systems - makes minimal Designed for open systems - makes minimal

assumptions about agentsassumptions about agents


A Working Grid A Working Grid ServiceService

MessageLog

RobustnessService

EH API

Transparently infers Transparently infers commitment structurescommitment structures

Assumes (some) agents Assumes (some) agents support (some of ) EH support (some of ) EH APIAPI Polling (backup: Polling (backup:

existing Grid is-alive? existing Grid is-alive? method)method)

Task re-announceTask re-announce Cancel-taskCancel-task



Benefits Validated Benefits Validated EmpiricallyEmpirically

Up to 3x speedup and 8x reduced variability Up to 3x speedup and 8x reduced variability vs. standard timeout-retry approachvs. standard timeout-retry approach

Benefits increase with task complexity Benefits increase with task complexity (decomposition tree height) and with level of (decomposition tree height) and with level of EH API supportEH API support

http://ccs.mit.edu/klein/papers/ASES-WP-2000-http://ccs.mit.edu/klein/papers/ASES-WP-2000-05.ps05.ps


Michigan Multilevel Michigan Multilevel Coordinator AgentCoordinator Agent

Analyses the alternative plan spaces of coalition functional Analyses the alternative plan spaces of coalition functional teams that plan independently and act asynchronouslyteams that plan independently and act asynchronously

Works top-down with plans chosen by teams to predict Works top-down with plans chosen by teams to predict unintended interactions (resource contentions; friendly fire).unintended interactions (resource contentions; friendly fire).

Identifies candidate resolutions (timing or action Identifies candidate resolutions (timing or action constraints).constraints).

Notifies process panel of possible plan conflicts and Notifies process panel of possible plan conflicts and computed workarounds.computed workarounds.

Operationalizes/enforces coordination decisions selected.Operationalizes/enforces coordination decisions selected. Given more time, isolates and resolves conflicts more Given more time, isolates and resolves conflicts more

precisely and efficiently.precisely and efficiently. Allows planning and coordination decisions to be postponed Allows planning and coordination decisions to be postponed

until runtime conditions become better known.until runtime conditions become better known. Packaged as a Grid-aware component that will be Packaged as a Grid-aware component that will be

proactively executing and will be utilized by the AIAI proactively executing and will be utilized by the AIAI Process Panel.Process Panel.


Potential plan conflicts include friendly fire in TEZ on ArmyDiv2, destruction of roads through E that ArmyDiv2 might need, and contention for sea and rail transport among army divisions and logistics.

Michigan Coalition Michigan Coalition Coordination ExampleCoordination Example

Forces begin at aircraft carrier ACAirforce sorties to C, E, & Q for Total Exclusion Zone (TEZ)Logistics delivers humanitarian aid to refugees at F and RArmyDiv1 occupies X to prevent Agadez forces from reaching and inciting refugees at RArmyDiv2 crosses TEZ to occupy Y to monitor for Gao crossings


Coordinated PlansCoordinated PlansHierarchical plan coordination incrementally Hierarchical plan coordination incrementally

recommends coordinated plans that are recommends coordinated plans that are increasingly detailed and parallelizedincreasingly detailed and parallelized

Fly sorties

Move to X

Time = 6500.02 cpu

sec.

Time = 5000.38 cpu sec.

Time = 4256.04 cpu sec.

Move to Y

LogisticsAirforce

Army Div 1Army Div 2

Move C1 R

Fly sortiesACP

Move to Y

LogisticsAirforce


P P

P Z Z X

Move C1 R, C2 F

Fly sortiesACP

Move to Y

LogisticsAirforce


P P

P Z Z X

Move C2 F

P P Move C1 R, C2 F


Michigan Multilevel Michigan Multilevel Coordinator AgentCoordinator Agent

Documents

CoAX Stand-alone Contributions DARPA Briefing - November 2000 Dartmouth College, UMichigan, MIT Sloan, Coalition Agents eXperiment (CoAX)