Interactive Resource Management in
the COMIREM Planner
Stephen F. Smith, David Hildum, David Crimm
Intelligent Coordination and Logistics Lab
The Robotics Institute
Carnegie Mellon University
Pittsburgh PA 15213
[email protected]
412-268-8811
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IJCAI-03 Workshop on Mixed-Initiative Intelligent Systems - August 9 2003
Outline of Talk
– Brief Introduction to Comirem
– Mixed-Initiative Perspective
– Connection to Workshop Themes
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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
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Embassy Rescue Scenario
Rebel
Enclave
Staging
Area
Task Force Charlie
(56 Troops)
Bridge
Task Force Bravo
(64 Troops)
Task Force Alpha
(24 Troops)
Home
Airport
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Available at Home Airport
–
7 MH60s
–
–
–
–
5 MH47s
5 MC-130Hs
2 C-141s
1 AC-130U
Rebel
Controlled
Airport
Embassy
250
AmCits
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
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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
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Elements of Mixed-Initiative Approach
Highly 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 results
Visualization of decision impact
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Generating Options
Light-Transport-Activity
MH-60
Capacity: 14
Resource Reqs.
instance
Deploy(A,B,?Res)
MH-60-5
MH-60-4
MH-60-3
MH-60-2
MH-60-1
instance
MH-47
Capacity: 40
Manifest: 120
MH-60 Option
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MH-47 Option
MH-60-4
MH-60-3
MH-60-2
MH-47-1
Generating Conflict Resolution Options
LFT
A
Move
1xMH-60
B
EST
Dur(MH-60) > LFT(Move) - EST(Move)
MH-60
Nom. Speed: 150
Option4: Deploy
earlier
Airdrop-Activity
TF-Deploy-Time
<relMove,∞ >
CZ
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C130
Nom. Speed: 200
StartTime-Constraint
instance
Res reqs.
Option1: Override
computed duration
Option2: Assign
a faster resource
instance
Move(A,B,MH-60)
<dMH-60, dMH-60>
DueDate-Constraint
instance
<0,ddMove>
Detected Cycle
Magnitude: m
TF-Engage-Time
Option3: Delay
engagement
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
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END
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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
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A More Complex Conflict Involving
Shared Resources
C
Move2
1xHMMVV
B
A
Move1
1xHMMVV
LFT
EST
Dur(HMMVV) > LFT(Move) - EST(Move)
• Resource sequencing constraint in conjunction
with the timing constraints of Move1 and Move
2 causes “cycle”
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Gantt and Vector Activity Views
Comirem
User
Interface
Resource
Aggregation
Resource Usage & Positioning
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Resource Tracking
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