Asynchronous Interaction Patterns for Mining Multi-Agent System Models from Event Logs

MACSPro'2019 - Modeling and Analysis of Complex Systems and Processes, Vienna
21 - 23 March 2019

Roman Nesterov, Irina Lomazova

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Transcript

1. Asynchronous Interaction Patterns for Mining Multi-Agent System Models from Event Logs Roman A. Nesterov1,2, Irina A. Lomazova1
 1 National Research University Higher School Of Economics (Moscow, Russia) 2 Università degli Studi di Milano-Bicocca (Milano, Italia)
2. Outline • Introduction • Process Discovery for Multi-Agent Systems • Service Interaction Patterns • Modeling and Refining Service Interaction Patterns • Experimental Evaluation • Conclusion and Future Work 2 / 16
3. Process Discovery 3 / 16
4. Process Discovery • Analysis of the observed behavior of information systems
 (ERP, BPM, HRM etc.). • Construction of as-is (executable) process models from event logs. 3 / 16
5. Discovering Process Models From Logs of MAS • Interaction of several independent agents ➝ sophisticated behavior. • Model structure ➝ behavior of agents and their interaction. 4 / 16
6. Discovering Process Models From Logs of MAS t1 t2 s1 t4 t3 r11 r12 t5 t6 t7 t8 t9 q1 q2 r21 r22 s21 s22 q4 q3 q5 q6 q7 q8 4 / 16 N
7. Discovering Process Models From Logs of MAS t1 t2 s1 t4 t3 r11 r12 t5 t6 t7 t8 t9 q1 q2 r21 r22 s21 s22 q4 q3 q5 q6 q7 q8 4 / 16 1. Simulate N and obtain an event log L. 2. Rediscover a model directly from L. N
8. Discovering Process Models From Logs of MAS t1 t2 s1 t4 t3 r11 r12 t5 t6 t7 t8 t9 q1 q2 r21 r22 s21 s22 q4 q3 q5 q6 q7 q8 4 / 16 N N*
9. Discovering Process Models From Logs of MAS t1 t2 s1 t4 t3 r11 r12 t5 t6 t7 t8 t9 q1 q2 r21 r22 s21 s22 q4 q3 q5 q6 q7 q8 Two models of the
 same system 4 / 16 N*
10. Compositional Process Discovery* • System model is composed from agent models guided by a specification of their asynchronous interaction. • System model preserves properties of agent behavior. • System model structure explicitly indicates interaction. • Channel-composition of generalized workflow nets. • Abstraction/refinement via -morphisms on Petri nets. α 5 / 16 * Bernardinello L., Lomazova I., Nesterov R., Pomello L. Compositional Discovery of Workflow Nets from Event Logs Using Morphisms (ATAED 2018).
11. Service Interaction Patterns* • A Systematic approach to the problem of modeling complex interactions. • They describe typical ways of interactions. • They describe agent interactions at the abstract level. 
 6 / 16 * Barros A. et al. Service Interaction Patterns (BPM 2005). * Campagna D. Et al. BPMN 2.0 and the Service Interaction Patterns… (ICSOFT 2014).
12. Service Interaction Patterns • A Systematic approach to the problem of modeling complex interactions. • They describe typical ways of interactions. • They describe agent interactions at the abstract level. • Bilateral/Multilateral interaction patterns. • Single/Multiple transmission patterns. 6 / 16
13. Service Interaction Patterns • A Systematic approach to the problem of modeling complex interactions. • They describe typical ways of interactions. • They describe agent interactions at the abstract level. • Bilateral/Multilateral interaction patterns; • Single/Multiple transmission patterns. 6 / 16
14. Bilateral Asynchronous Service Interaction Patterns 7 / 16
15. Bilateral Asynchronous Service Interaction Patterns Pattern Description Send (Receive) SIP-1 An agent X sends (receives) a message to (from) an agent Y. Concurrent Send (Receive) SIP-2 An agent X concurrently sends (receives) several messages (>1) to (from) an agent Y. Sending (Receiving) Choice SIP-3 An agent X sends (receives) exactly one out of two (or more) alternative message sets to (from) an agent Y. Send+Receive SIP-4 An agent X sends a message to an agent Y. Subsequently, Y sends a response to X. Concurrent Send+Receive SIP-5 An agent X concurrently sends several messages (>1) to an agent Y. Then Y sends a response to each message received from X. Sending+Receiving Choice SIP-6 An agent X sends exactly one out of two (or more) alternative message sets to an agent Y . Subsequently, Y sends a corresponding response to a message received from X. Multiple Send+Receive SIP-7 The iterative implementation of SIP-4, s.t. message exchange process continues till an Agent X does not need responses from an Agent Y. 7 / 16
16. Generalized Workflow Nets A GWF-net is a quintuple , where: • is a Petri net, • is an initial state and • is a final state. N = (P, T, F, m0 , mf ) m0 ⊆ P (P, T, F) mf ⊆ P 8 / 16
17. Generalized Workflow Nets • a bipartite graph, • an (initial) state is indicated by putting tokens inside places, t1 t5 t2 t6 t4 t3 t8 t7 transition place initial state final state 8 / 16
18. Generalized Workflow Nets • a bipartite graph, • an (initial) state is indicated by putting tokens inside places, • transition firings change a system state. t1 t5 t2 t6 t4 t3 t8 t7 transition place initial state final state 8 / 16
19. Generalized Workflow Nets A GWF-net is a quintuple , where: • is a Petri net, • is an initial state and • is a final state. A GWF-net is sound if and only if: • a final state is reachable from any reachable state (proper termination), • whenever a final state is reached, no tokens are left in other places (clean termination), • every transition has the ability to fire (no "dead" transitions). N = (P, T, F, m0 , mf ) m0 ⊆ P (P, T, F) mf ⊆ P 8 / 16
20. GWF-nets for Bilateral Interaction Patterns s r s1 s2 r1 r2 s1 r2 r1 s2 s11 s12 r21 r22 r11 r12 s21 s22 s11 s12 r21 r22 r11 r12 s21 s22 s12 r22 r11 s11 s21 r21 s1 s2 r1 r2 SIP-1 SIP-2 SIP-3 SIP-4 SIP-5 SIP-6 SIP-7 9 / 16
21. Refining Send+Receive Pattern (SIP-4) s1 r2 r1 s2 10 / 16
22. Refining Send+Receive Pattern (SIP-4) s1 r2 r1 s2 N1 N2 10 / 16
23. Refining Send+Receive Pattern (SIP-4) s1 r2 r1 s2 N1 N2 N1 ⊕C N2 10 / 16
24. Refining Send+Receive Pattern (SIP-4) N1 ⊕C N2 s1 r1 t1 t2 s1 t4 t3 r11 r12 t5 t6 t7 t8 t9 ' <latexit sha1_base64="0f4O9rWzmSyadm2Vpgy8VR6nfx0=">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</latexit> <latexit sha1_base64="0f4O9rWzmSyadm2Vpgy8VR6nfx0=">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</latexit> <latexit sha1_base64="0f4O9rWzmSyadm2Vpgy8VR6nfx0=">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</latexit> <latexit sha1_base64="IVa1UYZnF1m0clwxLmwboWGczdo=">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</latexit> N1 N'1 φ: N′ 1 → N1 s1 r2 r1 s2 N1 N2 10 / 16
25. Refining Send+Receive Pattern (SIP-4) N1 ⊕C N2 s1 r1 t1 t2 s1 t4 t3 r11 r12 t5 t6 t7 t8 t9 ' <latexit sha1_base64="0f4O9rWzmSyadm2Vpgy8VR6nfx0=">AAACynicjVHLSsNAFD2Nr/quunQTLIKrkIigy4IbFy4q2Ae0RSbptB2aF5NJoRR3/oBb/TDxD/QvvDOmoBbRCUnOnHvOnbn3+mkoMuW6ryVraXllda28vrG5tb2zW9nbb2ZJLgPeCJIwkW2fZTwUMW8ooULeTiVnkR/ylj++1PHWhMtMJPGtmqa8F7FhLAYiYIqoVnfCZDoSd5Wq67hm2YvAK0AVxaonlRd00UeCADkicMRQhEMwZPR04MFFSlwPM+IkIWHiHPfYIG9OKk4KRuyYvkPadQo2pr3OmRl3QKeE9Epy2jgmT0I6SVifZpt4bjJr9rfcM5NT321Kf7/IFRGrMCL2L99c+V+frkVhgAtTg6CaUsPo6oIiS266om9uf6lKUYaUOI37FJeEA+Oc99k2nszUrnvLTPzNKDWr90GhzfGub0kD9n6OcxE0Tx3Pdbybs2rNKUZdxiGOcELzPEcNV6ijYap8xBOerWtLWlNr9im1SoXnAN+W9fABFfeSEw==</latexit> <latexit sha1_base64="0f4O9rWzmSyadm2Vpgy8VR6nfx0=">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</latexit> <latexit sha1_base64="0f4O9rWzmSyadm2Vpgy8VR6nfx0=">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</latexit> <latexit sha1_base64="IVa1UYZnF1m0clwxLmwboWGczdo=">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</latexit> N1 N'1 φ: N′ 1 → N1 s1 r2 r1 s2 N1 N2 t1 t2 s1 t4 t3 r11 r12 t5 t6 t7 t8 t9 q1 q2 r21 r22 s21 s22 q4 q3 q5 q6 q7 q8 N'1 N'2 10 / 16
26. Refining Send+Receive Pattern (SIP-4) N1 ⊕C N2 s1 r2 r1 s2 N1 N2 t1 t2 s1 t4 t3 r11 r12 t5 t6 t7 t8 t9 q1 q2 r21 r22 s21 s22 q4 q3 q5 q6 q7 q8 N'1 N'2 N1 ⊕C N2 sound N′ 1 ⊕C N′ 2 sound φi : N′ i → Ni 10 / 16
27. Experimental Evaluation: Layout ABCDG HIJKLNOP QRSTUVW XYZACDEH IJKLMN… System event log ABCILOR TUXYAD EJKLN… DGHJKN PQSVWZ CHIM… Agent 1 event log Agent 2 event log filter B … … … D G … … … discover D B Agent 2 behavior Agent 1 behavior Interface D G … … … B … … … compose Complete system model SIPs S W … … … A … … … System simulate instantiate O G … … … U … … … N … … discover Directly discovered system model Compare quality 11 / 16
28. Experimental Evaluation: Neighboring Transitions Let be a GWF-net and . Two transitions are called neighboring iff there is a path in connecting them, where other transitions along this path are silent. N = (P, T, F, m0 , mf ) λ : T → L ∪ {τ} t1 , t2 (λ(ti ) ≠ τ) N 12 / 16
29. Experimental Evaluation: Neighboring Transitions Let be a GWF-net and . Two transitions are called neighboring iff there is a path in connecting them, where other transitions along this path are silent. Let , s.t. . denotes the number of neighboring transition pairs in . Symmetric pairs are counted as a single one. N = (P, T, F, m0 , mf ) λ : T → L ∪ {τ} t1 , t2 (λ(ti ) ≠ τ) N T = T1 ∪ T2 T1 ∩ T2 = Ø NbN (T1 × T2 ) ∪ (T2 × T1 ) 12 / 16
30. Experimental Evaluation: Neighboring Transitions Let be a GWF-net and . Two transitions are called neighboring iff there is a path in connecting them, where other transitions along this path are silent. N = (P, T, F, m0 , mf ) λ : T → L ∪ {τ} t1 , t2 (λ(ti ) ≠ τ) N t1 t2 t3 q1 q2 q3 q4 t2 t1 q1 q2 q3 t3 12 / 16
31. Experimental Evaluation: Instruments • Agent model discovery and event log filtration:
 ProM and Inductive Miner • Artificial event log generation:
 ProM plug-in GENA (extended with MAS simulation)* In our experiments, artificial event logs contain 5000 traces. 13 / 16 * Nesterov R.A., Mitsyuk A.A., Lomazova I.A. Simulating Behavior of Multi-Agent Systems with Acyclic Interactions of Agents // Proceedings of the ISP RAS. 2018.
32. Experimental Evaluation: Results SIP-1 SIP-2 SIP-3 SIP-4 SIP-5 SIP-6 SIP-7 Direct Discovery Places 35 59 42 49 64 72 29 Transitions 41 60 66 46 69 84 34 Arcs 98 140 112 120 170 198 78 NbN 22 95 25 61 85 117 22 Precision 0,689 0,5646 0,7768 0,6733 0,4554 0,6586 0,6495 Compositional Discovery Places 33 55 35 46 69 66 29 Transitions 32 49 35 39 57 72 28 Arcs 76 133 86 102 155 157 72 NbN 4 6 6 4 7 14 12 Precision 0,8017 0,4477 0,8162 0,6745 0,4342 0,8414 0,8500 14 / 16
33. Experimental Evaluation: Results SIP-1 SIP-2 SIP-3 SIP-4 SIP-5 SIP-6 SIP-7 Direct Discovery Places 35 59 42 49 64 72 29 Transitions 41 60 66 46 69 84 34 Arcs 98 140 112 120 170 198 78 NbN 22 95 25 61 85 117 22 Precision 0,689 0,5646 0,7768 0,6733 0,4554 0,6586 0,6495 Compositional Discovery Places 33 55 35 46 69 66 29 Transitions 32 49 35 39 57 72 28 Arcs 76 133 86 102 155 157 72 NbN 4 6 6 4 7 14 12 Precision 0,8017 0,4477 0,8162 0,6745 0,4342 0,8414 0,8500 14 / 16
34. Experimental Evaluation: Results • Compositionally discovered models are more compact with respect to the number of nodes. • Precision of composed models is mainly higher in comparison with directly discovered models. • The number of neighboring transition pairs are minimized to the number of transition pairs involved in the asynchronous agent interaction. 14 / 16
35. Conclusion and Future Work Directions • Formal models for service interaction patterns (SIPs) — (channel-composed) generalized workflow nets. • The illustration to the formal compositional approach to process discovery — refinement of abstract interaction patterns. • The overall experimental results demonstrates the value of the compositional approach. • Multilateral interaction patterns, • Systematic approach to constructing morphisms, • Improvement of the metric based on the notion of neighboring transitions. 15 / 16
36. Thank you for your attention! Roman A. Nesterov,
 rnesterov@hse.ru; r.nesterov@campus.unimib.it 16 / 16