Visual Specification and Design of Component-based Slow Intelligence Systems

1. Visual Specification and Design of Component-basedSlow Intelligence Systems

2. Outline • Why Slow Intelligence Systems • Introduction to SIS • Visual Specification of SIS • Incremental Design • SIS Framework and Test Bed • User Interface • Applications

3. Outline • Why Slow Intelligence Systems • Introduction to SIS • Visual Specification of SIS • Incremental Design • SIS Framework and Test Bed • User Interface • Applications

4. Why Slow Intelligence Systems The slow intelligence system (SIS) technology is a novel technology for the design and/or improvement of complex information systems.

5. Characteristics ofComplex Information Systems • Connected • Multiple sourced • Knowledge-based • Personalized • Hybrid • Prodigious

6. Smarter Planet We are all now connected - economically, technically and socially. Our planet is becoming smarter via integration of information scattered in many different data sources: from the sensors, on the web, in our personal devices, in documents and in databases, or hidden within application programs. Often we need to get information from several of these sources to complete a task. Examples include healthcare, science, the business world and our personal lives. (Quoted from Josephine M. Cheng, IBM Fellow and Vice President of IBM Research)

7. (courtesy of IBM)

8. Hybrid Intelligence While processor speed and storage capacity have grown remarkably, the geometric growth in user communities, online computer usage, and the availability of data is in some ways even more remarkable. Hybrid Intelligence offers great opportunities. We have to harness this data availability to build systems of immense potential. While today s large scale systems are evolutionarily based on the distributed computing technologies envisioned in the 70 s and 80 s, sheer scaling has led to many unanticipated challenges. (quoted from Alfred Z. Spector, Vice President, Research and Special Initiatives, Google, USA)

9. Prodigious Hybrid Intelligence Systems Users and computers doing more than either could individually (quoted from Alfred Z. Spector, Google).

10. Characteristics ofComplex Information Systems • Connected • Multiple sourced • Knowledge-based • Personalized • Hybrid • Prodigious => CONSTANTLY CHANGING

11. Challenges in the Design of Complex Information Systems • The operating environment, individual/collective user behavior and underlying technology base of such complex information systems are constantly changing. • There is never a stable and static solution for an “optimal” complex information system. • There are no general techniques for the design of a complex information system that can gradually improve and/or optimize its performance over time in a changing environment.

12. What is a Slow Intelligence System A Slow Intelligence System (SIS) is a general-purpose system characterized by being able to improve performance over time through a process involving enumeration, propagation, adaptation, elimination and concentration. A SIS is characterized by employing super components, i.e., multiple components that can be activated either sequentially or in parallel to search for better solutions. A SIS continuously learns, searches for new solutions and propagates and shares its experience with peers. 12

13. The SIS Technology This SIS technology consists of the visual specification of SIS as a system of super components, design principles of the timing controller, techniques for incremental application system design, SIS development framework and the SIS experimental test bed.

14. How can SIS technology help? The SIS technology can be applied to design and/or modify a complex information system capable of improving its performance over time in a changing environment. In this presentation we will concentrate on visual specification, incremental design, development framework, user interface, and application to social influence analysis.

15. Outline • Why Slow Intelligence Systems • Introduction to SIS • Visual Specification of SIS • Incremental Design • SIS Framework and Test Bed • User Interface • Application to Social Influence Analysis

16. Slow Intelligence Systems • Slow Intelligence Systems are general-purpose systems characterized by being able to improve performance over time. • A slow intelligence system is • a system that (i) solves • problems by trying different • solutions, (ii) is context- • aware to adapt to different • situations and to propagate • knowledge, and (iii) may • not perform well in the • short run but continuously • learns to improve its • performance over time.

17. Slow Intelligence Systems • Slow Intelligence Systems are general-purpose systems characterized by being able to improve performance over time through a process involving • Enumeration

18. Slow Intelligence Systems • Slow Intelligence Systems are general-purpose systems characterized by being able to improve performance over time through a process involving • Enumeration • Propagation

19. Slow Intelligence Systems • Slow Intelligence Systems are general-purpose systems characterized by being able to improve performance over time through a process involving • Enumeration • Propagation • Adaptation

20. Slow Intelligence Systems • Slow Intelligence Systems are general-purpose systems characterized by being able to improve performance over time through a process involving • Enumeration • Propagation • Adaptation • Elimination

21. Slow Intelligence Systems • Slow Intelligence Systems are general-purpose systems characterized by being able to improve performance over time through a process involving • Enumeration • Propagation • Adaptation • Elimination • Concentration

22. Slow Intelligence Systems • Slow Intelligence Systems are general-purpose systems characterized by being able to improve performance over time through a process involving • Enumeration • Propagation • Adaptation • Elimination • Concentration • Slow Decision Cycle • to complement Fast • Decision Cycle

23. Slow Intelligence Systems • A SIS continuously learns, searches for new solutions and propagates and shares its experience with other peers. • From the structural point of view, a SIS is a system with multiple decision cycles such that actions of slow decision cycle(s) may override actions of quick decision cycle(s), resulting in poorer performance in the short run but better performance in the long-run. • Timing Controller: What decision cycle to take is determined by the timing controller.

24. Slow Intelligence Systems • A SIS continuously learns, searches for new solutions and propagates and shares its experience with other peers. • From the structural point of view, a SIS is a system with multiple decision cycles such that actions of slow decision cycle(s) may override actions of quick decision cycle(s), resulting in poorer performance in the short run but better performance in the long-run. • Timing Controller: What decision cycle to take is determined by the timing controller.

25. Slow Intelligence Systems • A SIS continuously learns, searches for new solutions and propagates and shares its experience with other peers. • From the structural point of view, a SIS is a system with multiple decision cycles such that actions of slow decision cycle(s) may override actions of quick decision cycle(s), resulting in poorer performance in the short run but better performance in the long-run. • Timing Controller: What decision cycle to take is determined by the timing controller.

26. Slow Intelligence Systems • . A Slow Intelligence System is constructed from super components, which are the building blocks of SIS. Therefore SIS is an advancement over component based software systems: while a component-based software system is constructed from software components, in SIS some or all of its components are replaced by super components capable of improving their performances over time in a changing environment. • There are two types of super components: the basic building block and advanced building block.

27. Basic Building Block (BBB)

28. Advanced Building Block (ABB)

29. SIS is a component-based systembuilt from BBBs and ABBs

30. Comparison with Other Approaches 30 30

31. Outline • Why Slow Intelligence Systems • Introduction to SIS • Visual Specification of SIS • Incremental Design • SIS Framework and Test Bed • User Interface • Applications

32. Visual Specification of SIS

33. Dual visual representations by components and Petri net

34. Dual visual representations by class diagrams and sequence diagram

35. Super Components

36. Expanded Petri net based upon super components

37. A component generator for super components

38. Outline • Why Slow Intelligence Systems • Introduction to SIS • Visual Specification of SIS • Incremental Design • SIS Framework and Test Bed • User Interface • Applications

39. Partial dual visual representation (I-card1, C-card1) for Product & Service Customization (PSC) system

40. Partial dual visual representation (I-card2, C-card2) and (I-card3, C-card3)

41. Synthesis of partial visual representations (I-card1, C-card1), (I-card2, C-card2) and (I-card3, C-card3) into (I-card1-2-3,C-card1-2-3)

42. Outline Why Slow Intelligence Systems Introduction to SIS Visual Specification of SIS Incremental Design Timing Controller User Interface Application to Topic/Trend Detection Application to High Dimensional Feature Selection 42

43. Timing Controller • Three Types of Timing Controllers: • Basic Timing Controller (using switching circuit) • Advanced Timing Controller (using associative memory) • Recursive Timing Controller (for super components) • Fast Cycle and Slow Cycle: • Any cycle without super component is a fast cycle • Any cycle with super component is a slow cycle 43 43

44. Basic Timing Controller The basic timing controller consists of a latch register and a switching circuit The latch register has as many cells as there are software components. Each cell stores a binary number indicating whether to invoke the corresponding software component (1) or not (0) The latch register outputs this binary vector to the switching circuit, which computes another binary vector as new input to the latch register, to control the next round of software components invocation This computation cycle repeats itself, until the binary vector stored in the latch register becomes (0,…,0) 44 44

45. Advanced Timing Controller • In SIS some or all of the software components may be super-components. In which case, certain cells in the latch register may be associated with super-components. The associative memory also receives the binary vector from the latch register and uses it to search and access an associated binary vector (or vectors) as output The timing controller with non-deterministic associative memory determines the invocation of software components by performing additional computations on Petri net structure, attributes, probability, degree of certainty, fuzzy measures or some other means 45 45

46. Recursive Timing Controller Each cell associated with a super-component can be expanded into another latch register. The secondary latch register is part of another timing controller. In other words, timing controllers can be recursively defined when super components are present in a system The ‘T’ icon adjacent to a cell associated with a super component indicates it can be expanded into another timing controller. An equivalent, but simpler, notation is to write a ‘T’ inside this cell, which can then be expanded into another latch register and its associative memory 46 46

47. Outline • Why Slow Intelligence Systems • Introduction to SIS • Visual Specification of SIS • Incremental Design • SIS Framework and Test Bed • User Interface • Application to Social Influence Analysis

48. SIS Test Bed • Initially, to experiment with an application system under development, the SIS test bed can be employed.

49. SIS Test Bed for Healthcare Systems

50. SIS Framework • The SIS framework is to test and develop the optimized application system based upon the SIS technology.