Carnegie Mellon 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 Carnegie Mellon IJCAI-03 Workshop on Mixed-Initiative Intelligent Systems - August

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 Home Airport Staging Area Embassy Rebel Controlled Airport Rebel Enclave 250 AmCits Task 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 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 Deploy(A,B,?Res) Manifest: 120 Light-Transport-Activity MH-60 Capacity: 14 MH-47 Capacity: 40 Resource Reqs. instance MH-60-5 MH-60-4 MH-60-3 MH-60-2 MH-60-1 MH-60-4 MH-60-3 MH-60-2 MH-47-1 instance MH-60 Option MH-47 Option

Carnegie Mellon Generating Conflict Resolution Options Move 1xMH-60 EST LFT A B Dur(MH-60) > LFT(Move) - EST(Move) Move(A,B,MH-60) Airdrop-Activity MH-60 Nom. Speed: 150 C130 Nom. Speed: 200 Res reqs. instance TF-Engage-Time DueDate-Constraint TF-Deploy-Time StartTime-Constraint instance Option2: Assign a faster resource Option1: Override computed duration Option3: Delay engagement Option4: Deploy earlier CZ Detected Cycle Magnitude: 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

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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 Move1 1xHMMVV Move2 1xHMMVV 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

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