MICANTS

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MICANTS

• Gabor Karsai
• Benoit Dawant
• Greg Nordstrom
• Chris vanBuskirk
• Karlkim Suwanmongkol
• Patrick Norris
• Jonathan Sprinkle
• (Vanderbilt/ISIS)

Jon Doyle Robert Laddaga Vera Ketelboeter (MIT)
George Bloor (Boeing) Russ Currer (Idea Services)
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MICANTS Research Goals

• How to use
• Model-Integrated Computing, and
• Agent/Negotiation technology
• to solve complex resource management problems
  in (Autonomic) Logistics
• To demonstrate the feasibility of the technology
  through real-life example(s)

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Roles

• Vanderbilt/ISIS
• MIC, implementation, and demonstration
• MIT
• Concepts, algorithms
• Boeing
• Modeling, domain knowledge
• Idea Services
• Domain expertise and scenarios, customer
  interface
• http//www.isis.vanderbilt.edu/Projects/micants/mi
  cants.htm

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MIC for ANTSSupport for negotiation protocols
The MIC solution
The problem Complex agents that participate in
multiple, simultaneous negotiations are hard to
write
Status working prototype is in use on the project
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MIC for ANTSSupport for legacy system integration
The MIC solution
The problem Negotiating agents have to access
legacy databases,writing access code is tedious
and error-prone.
Model legacy database schema and agent ontology
Synthesize code for agent database interface
Generator
Negotiating Agent
Legacy DBase
Database Interface
Status modeling environment prototype has been
built. Note This approach is beneficial for
systems without a data warehouse.
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Agents/Negotiation Technology
CONFLICT
manages
manages
negotiation
Mutually acceptable, Negotiated solution
satisfies
satisfies
Objective Good enough solutions/soon enough
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Demonstration domainMaintenance logistics
(simplified) Unscheduled aircraft repair
Current practiceManual process
MMCO (sister squadron)
MMCO
negotiate
discrepancy
report
Negotiate/barter
negotiate
Assign mechanic
negotiate
W/C OIC
Flight Schedule
Shop Maintenance Schedule
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Vision Agent-supported Maintenance Process
MAPLANT MAintenance PLanning AgeNTs
GoalAssistance through offering negotiated
options
Commanders Intent
negotiate
report
W/C OIC
discrepancy
report
Assign mechanic
negotiate
Autonomic response

• Agents
• Helpers for the users
• Implement COs intent, business rules, and user
  guidance
• Negotiate solutions autonomically
• Offer options for approval

negotiate
Flight Schedule
Shop Maintenance Schedule
CAUTION Simplified picture
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MAPLANT Prototype

• Agents to support users
• Schedule generated mechanics time
• Create schedules based on constraints
• Task starts after, ends before, requires
  resource (mechanic)
• Number of resources qualifications
• Planning window size
• Incrementally schedule new tasks and assign
  mechanics to them based on constraints

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Agents for the users
Current prototype

• Maintenance Control Chiefs Agent
• Receives and logs gripes
• Negotiates with MALS and W/C-s
• Barters with sister squadron
• Shows canni options
• Event status display
• Event/AC assignments
• AC status over time
• What-ifs

• Work Center Supervisors Agent
• Schedules calendar-based MAs
• Proposes schedule(s)
• Schedule displays (with options)

• Helper agents
• Aircraft (health status)
• Mission (events, flight schedule)
• Jobs (maintenance actions)
• Workers (maintainers)
• MALS

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Agent operations
Current prototype

• M/C Startup
• Event Status Board (M/C)
• Event times
• EVT/AC assignment
• A/C status (OK, down, repair)

• Constraint-based scheduling
• Task start-afters, ends-before-s, and
  durations
• Task precedence
• Resource constraints
• Alternatives/flex assignments

• W/C Startup
• Schedules calendar-based MAs
• Input
• Job list with time and MOS requirements
• Worker pool with qualifications
• Output
• Jobs scheduled and assigned to workers

• Helper startup
• Aircraft (health status)
• Mission (events, flight schedule)
• Jobs (maintenance actions)
• Workers (maintainers)

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Agent operations
Current prototype

• MALS
• Reply with time for part availability

• M/C receives gripe/diagnosis
• Status Board shows conflicts
• Selection A/C Gripe
• Options
• Standard procedure (MALS)
• Barter (with other M/C)
• Canni (if possible)
• Evaluation
• Comparison of options
• Check effects on flight schedule
• Changes
• Accept/refuse proposed MA
• AC to event assignment

• Sister squadron M/C
• Reply with time for part availability

• A/C in maintenance
• Reply with time parameters

• W/C operation
• Reactive (re-)scheduling
• Input
• New job with time and MOS requirements
• All old jobs
• Output (for approval)
• Multiple schedule options for new job

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Agent operations
Current prototype

• M/C smarts
• Shows/warns about conflicts with flight schedule
• Keeps track of current/pending MAs
• Displays available options when repairing
  AC/EVT allocations
• Detects A/C in repair that can be utilized in
  canni
• Can arrange barter with other M/Cs agent
• What-if
• Effect of the selected MA on the flight schedule
• Suggests possible optimizations
• Swaps (possibly with other squadron)
• Milking

• W/C smarts
• Rapid schedule generation
• Multiple schedule options
• Options are evaluated/ranked
• Flexible schedule choices
• Tentative scheduling choice, confirmed later

• Initial data from warehouse
• Aircraft (health status)
• Mission (events, flight schedule)
• Jobs (maintenance actions)
• Workers (maintainers)

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MAPLANT MAintenance PLanning AgeNTs
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ApproachScheduling and negotiation as CSP
Explicit management of constraints during
negotiation/scheduling
Negotiating agent
Messaging
Coordination Engine
High-performance encoding techniques
Data structures representing domain constraints
Domain-independent SAT techniques
Schedule
Domain-specific API to the scheduler
Constraint SAT mapper (encoding)
Standard SAT Interface (CNF, etc.)

• Complexity management
• Encoding strategy
• SAT

Standard SAT Problem Solver (Tableau,WSAT,ISAMP)
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ApproachEncoding a scheduling as binary SAT

• Precedence pr(i,j)
• Starts after sa(i,r_i)
• Ends before eb(i,d_i)
• Coherence
• sa(i,t) -gt sa(i,t-1) starts at or after t-1
• eb(i,t) -gt eb(i,t1) ends at or before t1
• sa(i,t) -gt NOT eb(i,tP-1) requires time P
• sa(I,t) AND pr(i,j) -gt sa(j,tP) conflicting
  task cannot start until first task finishes
• Resource constraints c(i,j) lt Cap

SCALING Polynomial in Tasks, Resources, Slots
Based on Crawford/Blake 1993
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ApproachAddressing timeliness issues
Negotiating agent

• REAL-TIME RESPONSE
• Monitor situation and progress
• If needed, modify process

Messaging
Coordination Engine
SAT Engine
Monitoring Evaluation
Reconfiguration
Reconfigurator

• Technology for achieving time-bounded results
• Flexible negotiation with monitored execution and
  reconfiguration (MIT)
• Schedule generation via constraint-satisfaction
• Explicitly represent current tasks as constraints
• Monitor SAT engine execution for timeout
• Relax constraints when SAT does not converge
• Utilize SAT engine solutions

• DYNAMICS/STABILITY
• SAT Engine (TBD)

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Scalability of the SchedulerFirst and second
approach

• 10hrs window, 1hr/task, Mmechanics, Ttasks, T
  2M
• Memory usage
• WSAT engine

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Scalability of the SchedulerFirst and second
approach

• 10hrs window, 1hr/task, Mmechanics, Ttasks, T
  2M
• Run time
• WSAT engine

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Scalability of the SchedulerImproved approach

• 10hrs window, 1hr/task, Mmechanics, Ttasks
• Memory usage
• WSAT engine

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Scalability of the SchedulerImproved approach

• 10hrs window, 1hr/task, Mmechanics, Ttasks
• Run time
• WSAT engine

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Negotiation Algorithms

• MIT

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Resource management through automated negotiation

• Key concept
• Resolving resource conflicts through negotiation

• Dynamic Negotiation Strategies Scripts for
  negotiation
• Plans specify structure of complex negotiations
• Composing complex strategies from elemental
  methods

• Dynamic Negotiation Goals Changing the
  objectives on-the-fly
• Strategic progression changes goals
• Changing situation changes goals, then strategy

• Dynamic Negotiation Preferences Changing
  priorities
• Invention of preferences to cover new
  situations
• Toughening or liberalizing negotiation position

• Dynamic Negotiation Organization Changing
  partners
• Relation of agent to others depends on strategy,
  situation, and history
• Construct proximity groups along different
  relational dimensions
• Structure strategies to exploit these proximity
  groups

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Resource management through automated negotiation
Addressing timeliness issues Real-time
performance
Negotiating agent
Messaging
Coordination Engine
Monitor situation and progress If needed, modify
negotiation process
Monitoring Evaluation
Reconfiguration
Reconfigurator

• Technology for achieving time-bounded results
• Flexible negotiation plans with monitored
  execution and reconfiguration
• Fast methods for evaluating complex decision
  functions
• Anytime strategies -- incremental, reactive
• Problem decomposition/solving/ and solution
  integration

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Negotiation complexity

• Complexity-aware negotiation monitors expected
  difficulty of solution construction
• Estimates of negotiation time and result quality
  build on estimates from base CSP, preference
  management subsystem, and negotiation strategy
  structure
• Agent adjusts or renegotiates constraints to
  speed solution construction or failure
  determination using preferences about constraints

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Negotiation for options

• Negotiation outcomes represent options to MMCO in
  decision-support activity
• Alternative deals using same preferences or
  making different modifications of preferences
• Simultaneous and serial options from concurrent
  and sequential negotiation stages

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Domain modeling

• Boeing

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The Maintenance Action Form Life Cycle
Open MAF
Closed MAF

• At the Marine Corp Base, in Yuma Arizona, a
  maintenance action form (MAF) is opened when any
  repair or equipment modification is made to a
  Harrier.

• The MAF can be used to trace many of the
  intricate details of the maintenance related
  decisions.

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The Maintenance Action Form Life Cycle
Balance
Open MAF
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Modeling the Decision Support Environment The
Maintenance Action Form Life Cycle
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Modeling the Decision Support Environment The
Maintenance Action Form Life Cycle
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Explicit Business Process Models

• Resource Allocation -
• Allocate Space, Time, Material, Equipment, People

Next Step
Implicit Business Process Models

• Strategies, Decision Making -
• Shift Change MAF Triage

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Plans

• Framework refinements
• Time management
• Optimization engine
• Sophisticated constraint management in scheduler
• Complexity experiments/discussions
• Interface with complexity contractors
• Demonstrations
• Interaction with MAG-13 personnel
• Initial Assessment Milestone (next Summer)
• Integration with ISIs CAMERA
• Plan staged approach
• Leading towards negotiation between the flight
  and maintenance schedulers