Software Agent Testing - FBK | SE - Fondazione Bruno Kessler

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Challenges in testing agents & MASTraditional software• deterministic• observableinputsstate αoutputsAgent• non-deterministic, due to self-*and the instant changes of theenvironmentinputssensorsoutputsself-*MAS• distributed, asynchronous• message passing• cooperative, emergentbehaviours4
Testing phasesn Acceptance: ensure the system meets thestakeholder goalsn System: test for the macroscopic properties andqualities of the systemn Integration: check the collective behaviors andthe interaction of agents with the environmentn Agent: check for the integration of agentcomponents (goal, plan, beliefs, etc.) and agent’sgoal fulfillment.n Unit: testing agent units: blocks of code, agentcomponents (plan, goal, etc.)5
Page 1 and 2: Testing SoftwareAgents & MASCu D. N
Page 3: Software agents and MASSoftware age
Page 7 and 8: Some factsn Many BDI agent dev. lan
Page 9 and 10: Testing agent beliefsn Belief state
Page 11 and 12: Testing agent plansn Plans are trig
Page 13 and 14: Example: testing a cleaning agentn
Page 15 and 16: Example (contd.)n Example of goal$b
Page 18 and 19: Ontology-based oraclesn Interaction
Page 20 and 21: Input space in testing agentsn Test
Page 22 and 23: Mock Agentsn Mock Agents are sample
Page 24 and 25: Continuous Testing ofAutonomous Age
Page 26 and 27: Continuous testingn Consists of inp
Page 28 and 29: Random generation• Messages:‣ s
Page 30 and 31: Quality-function-based evolutionary
Page 32 and 33: Example (contd)n Genetic algorithm,
Page 34 and 35: Conclusionsn Testing software agent

Software Agent Testing - FBK | SE - Fondazione Bruno Kessler

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