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Nitin Kumar Yadav RMIT University, Melbourne nitin.yadav@student.rmit.au

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## Nitin Kumar Yadav RMIT University, Melbourne nitin.yadav@student.rmit.au

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**Implementation and analysis of simulation based techniques**for behavior composition Nitin Kumar Yadav RMIT University, Melbourne nitin.yadav@student.rmit.edu.au Minor thesis for semester 2, 2009, under the supervision of Dr. Sebastian Sardina, RMIT university**Implementation and analysis of simulation based techniques**for behavior composition Behavior Composition Simulation Techniques Implementation Analysis Contents**Behavior Composition**What is a behavior ? • Behavior • Logic of a machine • Web service • Stand alone component • Abstracted as finite transition systems • Available behaviors can be non-deterministic B1 B2**Behavior Composition**Combining available behaviors to realize a target behavior Available behaviors B1 B2 Can we realize T1 by composing B1 and B2 ? Target behavior (virtual) T1**Behavior Composition**Combined finite transition system of available behaviors B1 B2 Asynchronous product of B1 and B2 ‘composed’ transition system of available behaviors**Behavior Composition**Combined finite transition system of available behaviors B1 B2 Asynchronous product of B1 and B2 ‘composed’ transition system of available behaviors**Behavior Composition**Combined finite transition system of available behaviors B1 B2 Asynchronous product of B1 and B2 Can this behave like the target system ?**Simulation**• A transition system T1 simulates another transition system T2 iff T1 can ‘mimic’ all the states of T2 • A state in the available system mimics another state in the target system if: • It can do all the actions that the target state can do • The successor state in the available system as a result of such an action simulates the resulting state in the target system • Simulation is a relation of states of the composed system and the states of the target behavior which can be ‘mimicked’.**Simulation**Example t Simulation Relation {<S1,S1>, <T1>} {<S2,S1>, <T2>} … simulation relation is a solution to the behavior Composition problem ! How to calculate it ? Available behaviors Target System**Techniques**Two approaches for behavior composition • Regression based approach [Sardina,Patrizi & De Giacomo, KR 2008] • Progression based approach [Stroeder & Pagnucco, 2009, IJCAI 2009] Proceedings of Principles of Knowledge Representation and Reasoning (KR), pages 640-650, Sydney, Australia, September 2008. AAAI Press. Accepted for the IJCAI 2009**Techniques**Regression based approach [Sardina, Patrizi, De Giacomo] • Assume each state in the available system simulates each state in the target system • Iteratively remove non-conformant links which don’t’ follow the simulation definition i.e., • Can not perform the actions which can be requested in the matching target state • The successor state of the action does not follow the above rule • Stop when no more links can be removed**Regression based approach**Example t Available behaviors Assume each state from available behaviors simulates each state In the target system {<S1,S1>, <T1>} {<S1,S1>, <T2>} {<S1,S1>, <T3>} {<S2,S1>, <T1>} {<S2,S1>, <T2>} {<S2,S1>, <T3>} {<S2,S2>, <T1>} {<S2,S2>, <T2>} {<S2,S2>, <T3>} {<S1,S2>, <T1>} {<S1,S2>, <T2>} {<S1,S2>, <T3>} Target System**Regression based approach**Example Each Cycle : step 1 – remove the States which can not perform the Actions of the linked target state t Available behaviors {<S1,S1>, <T1>} {<S1,S1>, <T2>} {<S1,S1>, <T3>} {<S2,S1>, <T1>} {<S2,S1>, <T2>} {<S2,S1>, <T3>} {<S2,S2>, <T1>} {<S2,S2>, <T2>} {<S2,S2>, <T3>} {<S1,S2>, <T1>} {<S1,S2>, <T2>} {<S1,S2>, <T3>} Target System**Regression based approach**Example Each Cycle : step 2 – remove the States whose successor states are not in the simulation relation t Available behaviors {<S1,S1>, <T1>} {<S1,S1>, <T2>} {<S2,S1>, <T1>} {<S2,S1>, <T2>} {<S2,S2>, <T1>} {<S2,S2>, <T2>} {<S2,S2>, <T3>} {<S1,S2>, <T1>} {<S1,S2>, <T3>} X Continue till no more links can be removed Target System**Techniques**Progression based approach [Stroder & Pagnucco] • Start from the initial state • Iteratively addconformant links between the states of the composed system and the target system • Stop when no more links can be added**Progression based approach**Example t Available behaviors Start from states those ‘can Mimic the initial state {<S1,S1>, <T1>} {<S2,S1>, <T1>} {<S2,S2>, <T1>} {<S1,S2>, <T1>} Target System**Progression based approach**Example t Available behaviors Iteratively add links {<S1,S1>, <T1>} {<S2,S1>, <T1>} {<S2,S2>, <T1>} {<S1,S2>, <T1>} {<S2,S1>, <T2>} {<S2,S2>, <T2>} Target System**Progression based approach**Example t Available behaviors Iteratively add links {<S1,S1>, <T1>} {<S2,S1>, <T1>} {<S2,S2>, <T1>} {<S1,S2>, <T1>} {<S2,S1>, <T2>} {<S2,S2>, <T2>} {<S2,S2>, <T3>} X Target System**Implementation**Implementation of both the techniques on a common platform • Implement both approaches on a common platform – Java • Prototype implementation available. • TLV implementation for deterministic available behaviors is available, but not for non-deterministic behaviors. Symfony is another system, but Lacks some of the components.**Analysis**Comparing the speed of the techniques • Measure the speed of both the algorithms for the problems • Design benchmark problems • Hand crafted • Problems for which a known solution exists • Problems for which a solution does not exist • Randomly generated problems • Variation in size and number of available behaviors • If time left in minor thesis • Study algorithm’s behavior with respect to • Varying degrees of non determinism in available behaviors**Comparing the speed of the techniques**Questions ?