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Carnegie Mellon
Interactive Resource Management in the COMIREM Planner
Stephen F. Smith, David Hildum, David Crimm
Intelligent Coordination and Logistics LabThe Robotics Institute
Carnegie Mellon UniversityPittsburgh PA 15213
Carnegie MellonIJCAI-03 Workshop on Mixed-Initiative Intelligent Systems - August 9 2003
Carnegie Mellon
Outline of Talk
– Brief Introduction to Comirem– Mixed-Initiative Perspective– Connection to Workshop Themes
Carnegie Mellon
COMIREM
A light-weight, interactive system for resource management in continuous planning domains
Domain: SOF planning Motivating Themes:
– Resource management cannot be considered a separable post-process to plan generation
– Planning is an ill-structured, iterative process that is rarely amenable to total automation and not well supported by batch-oriented solution generators
– Planning involves collaboration among (increasingly) mobile decision making agents
Carnegie Mellon
Embassy Rescue Scenario
HomeAirport
StagingArea
Embassy
Rebel Controlled
Airport
RebelEnclave
250AmCitsTask Force Alpha
(24 Troops)
Task Force Charlie(56 Troops)
Task Force Bravo(64 Troops)
Bridge
Available at Home Airport– 7 MH60s– 5 MH47s– 5 MC-130Hs– 2 C-141s– 1 AC-130U
Carnegie Mellon
Mixed-Initiative Design Goals
Adjustable decision-making autonomy– User will want to make decisions at different levels of detail in
different contexts
Translation of system models and decisions– User should be able to inject decisions without having to understand
system search models and vice-versa be able to effectively interpret system results
Incremental problem solving– Constraints typically become known incrementally– Controlled change facilitates comprehension– Solution stability is crucial in continuous planning domains
Carnegie Mellon
Constraint Management and Search Infra-structure
Comirem is a flexible times scheduler:– Activity start and end times float to the extent that problem constraints
allow– Activities requiring the same resources are sequenced
Simple Temporal Problem (STP) constraint network solver is used to manage temporal constraints– Constraint graph of time points (nodes) and distances (arcs)
Higher-level domain model super-imposed to add reasoning about resource usage constraints– Required and provided capabilities– Resource location (positioning, de-positioning, repositioning)– Resource carrying capacity (manifests and configurations)
Decisions (user and system) are made opportunistically
Carnegie Mellon
Elements of Mixed-Initiative ApproachHighly interactive - spreadsheet metaphor
Levels of automated decision-making– Individual decision expansion and options– Temporal and resource feasibility checking– Automated solution generation -biased by user goals and
preferences– User over-ride of any constraint in system model
Interaction via mutually understood domain model– Translation of domain model edits into internal constraint models– Complementary use of domain model to convey and interpret
resultsVisualization of decision impact
Carnegie Mellon
Generating Options
Deploy(A,B,?Res)Manifest: 120
Light-Transport-ActivityMH-60
Capacity: 14
MH-47Capacity: 40
Resource Reqs.
instance
MH-60-5MH-60-4MH-60-3MH-60-2MH-60-1
MH-60-4MH-60-3MH-60-2MH-47-1
instance
MH-60 Option MH-47 Option
Carnegie Mellon
Generating Conflict Resolution Options
Move1xMH-60
EST
LFTA
B
Dur(MH-60) > LFT(Move) - EST(Move)
Move(A,B,MH-60)
Airdrop-Activity
MH-60Nom. Speed: 150
C130Nom. Speed: 200
Res reqs.
instance
instance
TF-Engage-Time
DueDate-ConstraintTF-Deploy-Time
StartTime-Constraint
instance
Option2: Assign a faster resource
Option1: Override computed duration
Option3: Delay engagement
Option4: Deploy earlier
<dMH-60, dMH-60>
<0,ddMove><relMove,∞ >
CZ Detected CycleMagnitude: m
Carnegie Mellon
Comirem Positions on Workshop Issues
Task - User manipulates goals, constraints and preferences; system solves within specified parameters
Control - User in control; system offers decision options wherever possible and solutions when user delegates
Awareness - Mutually understandable domain model used to bridge user and system models
Communication - Summarization, visualization of decision impact
Evaluation - increased efficiency/effectiveness; system manages complexity; user brings knowledge outside of system models
Architecture - Spreadsheet model of interaction; incremental change
Carnegie Mellon
Functional Capabilities
Interactive Planning and Resource Allocation– Option generation– Visualization of decision impact– Requirements and capabilities editing– Automated assignment and feasibility checking– What-if exploration
Resource Configuration– Construction and allocation of aggregate resources
Execution Management– Resource tracking– Plan tracking– Conflict analysis
Carnegie Mellon
Move11xHMMVV
Move21xHMMVV
A More Complex Conflict Involving Shared Resources
• Resource sequencing constraint in conjunction with the timing constraints of Move1 and Move 2 causes “cycle”
EST
LFT
B
A
Dur(HMMVV) > LFT(Move) - EST(Move)
C
Carnegie Mellon
Comirem User
Interface
Gantt and Vector Activity Views
Resource Usage & Positioning Resource Tracking
Resource Aggregation