1. 1 18 August 2015 AGV Simulation Tutorial Nelis Boucké Alexander Helleboogh

2. 2 18 August 2015 Overview Introduction Architecture Installation Use Extensions

3. 3 18 August 2015 Simulation is crucial for MAS applications AGVs (Automated Guided Vehicles) oTransport loads in warehouse oComplex network of road segments and crossroads Advantage of using MAS oDecentralized system behavior  Robust & flexible  In dynamic & unpredictable environments Test before deployment! oDecentralized systems oNo risk of damaging AGVs Challenge for simulation oTest robustness & flexibility oDynamic test scenarios needed!

4. 4 18 August 2015 How do we test? Agent software Simulated environment DeployTest Warehouse environment

5. 5 18 August 2015 Overview Introduction Architecture Installation Use Extensions

6. 6 18 August 2015 Java VM Eclipse Platform AGV Simulator GUI Plug-in Architecture AGV Batch Simulator AGV Batch Simulator MAP editor Simulation Runner Simulation Runner AGV Agent Behavior AGV Agent Behavior XML agentwise. agvsimulation agentwise. agvsimulation.ui agentwise. agvsimulation. behaviordemo

7. 7 18 August 2015 AGV batch simulator Interface Deliberation Time Model Simulated Environment Interface

8. 8 18 August 2015 Programming AGV Behavior Class: oAGVRandomWalkBehavior  Specify your behavior here!  Package agentwise.agvsimulation.behaviordemo Classes you can use: oAGVBehavior  The complete set of instructions to steer the AGV robot  package agentwise.agvsimulation.agv Interface

9. 9 18 August 2015 Scenario: decisions of agents A B sendUnicast @ T=1 driveToStation @ T=1 driveToStation @ T=2 Influences

10. 10 18 August 2015 Scenario: decisons result in activities A B Activities Send activity over (1,2) Move activity over (2,6) Move activity over (1,5)

11. 11 18 August 2015 A B Activities interfere! A B A B A B Intended outcome Actual outcome

12. 12 18 August 2015 What does this imply? Specification of AGV programming interface oNo post conditions in terms of what will happen oAll kinds of catastrophes can happen  Not indicated by exceptions oOnly specifies what an agent tries to do Thinking versus acting oAgents can think and act in parallel  Agent have to wait explicitly while their AGV is driving  waitsecond()  Agents can send messages while their AGV is driving oAgents are not notified of anything  have to rely on polling their sensors