Nitin Kumar Yadav

1
Implementation and analysis of simulation based
techniques for behavior composition

• Nitin Kumar Yadav
• RMIT University, Melbourne
• nitin.yadav_at_student.rmit.edu.au

Minor thesis for semester 2, 2009, under the
supervision of Dr. Sebastian Sardina, RMIT
university
2
Implementation and analysis of simulation based
techniques for behavior composition

• Behavior Composition
• Simulation
• Techniques
• Implementation
• Analysis

Contents
3
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
4
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
5
Behavior Composition
Combined finite transition system of available
behaviors
B1
B2
Asynchronous product of B1 and B2
composed transition system of available
behaviors
6
Behavior Composition
Combined finite transition system of available
behaviors
B1
B2
Asynchronous product of B1 and B2
composed transition system of available
behaviors
7
Behavior Composition
Combined finite transition system of available
behaviors
B1
B2
Asynchronous product of B1 and B2
Can this behave like the target system ?
8
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.

9
Simulation
Example
t
Simulation Relation
ltS1,S1gt, ltT1gt ltS2,S1gt, ltT2gt
simulation relation is a solution to the
behavior Composition problem ! How to calculate
it ?
Available behaviors
Target System
10
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
11
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
  dont 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

12
Regression based approach
Example
t
Available behaviors
Assume each state from available behaviors
simulates each state In the target system
ltS1,S1gt, ltT1gt ltS1,S1gt, ltT2gt ltS1,S1gt,
ltT3gt ltS2,S1gt, ltT1gt ltS2,S1gt, ltT2gt ltS2,S1gt,
ltT3gt ltS2,S2gt, ltT1gt ltS2,S2gt, ltT2gt ltS2,S2gt,
ltT3gt ltS1,S2gt, ltT1gt ltS1,S2gt, ltT2gt ltS1,S2gt,
ltT3gt
Target System
13
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
ltS1,S1gt, ltT1gt ltS1,S1gt, ltT2gt ltS1,S1gt,
ltT3gt ltS2,S1gt, ltT1gt ltS2,S1gt, ltT2gt ltS2,S1gt,
ltT3gt ltS2,S2gt, ltT1gt ltS2,S2gt, ltT2gt ltS2,S2gt,
ltT3gt ltS1,S2gt, ltT1gt ltS1,S2gt, ltT2gt ltS1,S2gt,
ltT3gt
Target System
14
Regression based approach
Example
Each Cycle step 2 remove the States whose
successor states are not in the simulation
relation
t
Available behaviors
ltS1,S1gt, ltT1gt ltS1,S1gt, ltT2gt ltS2,S1gt,
ltT1gt ltS2,S1gt, ltT2gt ltS2,S2gt, ltT1gt ltS2,S2gt,
ltT2gt ltS2,S2gt, ltT3gt ltS1,S2gt, ltT1gt ltS1,S2gt,
ltT3gt
X
Continue till no more links can be removed
Target System
15
Techniques
Progression based approach Stroder Pagnucco

• Start from the initial state
• Iteratively add conformant links between the
  states of the composed system and the target
  system
• Stop when no more links can be added

16
Progression based approach
Example
t
Available behaviors
Start from states those can Mimic the initial
state
ltS1,S1gt, ltT1gt ltS2,S1gt, ltT1gt ltS2,S2gt,
ltT1gt ltS1,S2gt, ltT1gt
Target System
17
Progression based approach
Example
t
Available behaviors
Iteratively add links
ltS1,S1gt, ltT1gt ltS2,S1gt, ltT1gt ltS2,S2gt,
ltT1gt ltS1,S2gt, ltT1gt ltS2,S1gt, ltT2gt ltS2,S2gt,
ltT2gt
Target System
18
Progression based approach
Example
t
Available behaviors
Iteratively add links
ltS1,S1gt, ltT1gt ltS2,S1gt, ltT1gt ltS2,S2gt,
ltT1gt ltS1,S2gt, ltT1gt ltS2,S1gt, ltT2gt ltS2,S2gt,
ltT2gt ltS2,S2gt, ltT3gt
X
Target System
19
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.

20
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 algorithms behavior with respect to
• Varying degrees of non determinism in available
  behaviors

21
Questions ?
Comparing the speed of the techniques