Download - Architecture of Incident Management Systems
Architecture of Incident Management Systems.
Ir. R. van der Krogt
Ir. J. Zutt
Contents
• Architecture
• Replanning techniques
• Simulation (Mars)
Architecture (I)Planner
Real World
PlanPlanPlanPlan
Creates
Execute in
Architecture (II)Planner
Real World Diagnosis
Replanner
PlanPlanPlanPlan
Creates
Execute in
Adapts
Calls
Watches
Strategic and Tactical level
Planner Replanner
Observations Diagnose
StrategicDrive(truck1, Adam, Rdam)Load(truck1,cargo1)Drive(truck1, Rdam, Utrecht)
...
Planner Replanner
Observations Diagnose
TacticalAccelerate(truck1,20)TurnDirection(truck1, 20°)TurnDirection(truck1, 0°)
...
Real World
Example Plans:
Architecture (revisited)
Planner
Real World Diagnosis
Replanner
PlanPlanPlanPlan
• Planner creates a plan for each agent (possibly optimized using merging).
• Diagnosis module monitors the execu-tion and starts the replanner when it detects faults.
Replanner (I)
• Is started by the diagnosis module when it detects a contingency.
• Uses specialized algorithms to adapt the current (failing) plan to one that satisfies the goals.
• Tries to make as few changes as possible to the plan to avoid breaking existing commitments.
Replanner (II)
• Add actions
Replanner (II)
• Add actions
• Remove actions
Replanner (II)
• Add actions
• Remove actions
• Replace actions
Adding skills to a graph
• Extending a plan with a plan fragment.
P la nfra gm e nt
Resource oftype “pink”
Resource oftype “blue”
Adding skills to a graph
• Extending a plan with a plan fragment.
1 Find resources that are already available in the plan.
P la nfra gm e nt
Adding skills to a graph
• Extending a plan with a plan fragment.
2 Remove skills from the plan fragment that are obsolete.
P la nfra gm e nt
Adding skills to a graph
• Extending a plan with a plan fragment.
3 Link the plan fragment to the plan.
Adding skills to a graph
• Extending a plan with a plan fragment.
4 Final result: the extended plan.
Simulation
Real-world Simulation world.
Why do we need simulation?
• Validation of new techniques.
• Possibility to introduce faults for testing.
Multi-Agent Real-Time Simulator (MARS)
• Designed by TNO-TPD.
• Written in Java, interface to Matlab/Simulink.
• Multi-Agent future: support for multiple hosts / distributed simulation.
• Principally two parts: Base simulator + Experiment.
MARS experiment (1)
Entitybehavioral
model
Behavior represented using(Timed) Finite State Machines
MARS experiment (1)
Entitybehavioral
model
Infrastructure:
Behavior represented using(Timed) Finite State Machines
Used by the mobile entities
MARS experiment (1)
Entitybehavioral
model
Infrastructure:
Scenario
Behavior represented using(Timed) Finite State Machines
Used by the mobile entities
Initial setting, simulation goals and introducting faults
MARS experiment (1)
Entitybehavioral
model
Infrastructure:
Scenario
Visual Model
Behavior represented using(Timed) Finite State Machines
Used by the mobile entities
Initial setting, simulation goals and introducting faults
Visual information to display
MARS experiment (2)
Entitybehavioral
model
Infrastructure:
Scenario (initial,goals, faults)
Visual Model
Diagnosis
Replanner
Strategic observations
Planner
Tactical observations
Real World
MARS experiment (3)
Entitybehavioral
model
Infrastructure:
Scenario (initial,goals, faults)
Visual Model
Diagnosis
Replanner
Simulation step:- t time elapses.- Update entities.- Visualisation.
Strategic observations
Planner
Tactical observations
Real World
MARS demonstration
1. Taxi-cab simulator.
MARS demonstration
1. Taxi-cab simulator.
2. Transport Planning.
MARS demonstration
1. Taxi-cab simulator.
2. Transport Planning.
Support both layers(strategic and tactical).
Incident Management techniqueswill be applied.
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Behavioral models represented with Finite State Machines
