UbiCom Book Slides

1. UbiCom Book Slides Chapter 8 Intelligent Systems (Part A: Basics) Stefan Poslad http://www.eecs.qmul.ac.uk/people/stefan/ubicom Ubiquitous computing: smart devices, environments and interaction

2. Chapter 8: Overview Chapter 8 focuses on: • Internal system properties: intelligence • External interaction with any of three types of environment • Focussing more on ICT and physical environment • These environments tend to be passive Ubiquitous computing: smart devices, environments and interaction

3. Five main properties for UbiCom Ubiquitous computing: smart devices, environments and interaction

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5. Chapter 8: Overview The slides for this chapter in the full pact are expanded and split into several parts • Part A: Basics  • Part B: R-IS, EM-IS • Part C: G-IS, U-IS & H-IS Models • Part D: KB IS Models • Part E: KB Acquisition • Part F: KB Representation: Rule-Based, BB • Part G: KB Representation: Semantic • Part H: Classic Logic KB Models • Part I: Soft Computing KB Models • Part I: Generic IS Operations Ubiquitous computing: smart devices, environments and interaction

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7. Related Chapter Links • There are two AI chapters that are interlinked • This chapter. 8, describes the design of single Intelligent System or IS • These may be simple: use a single models of intelligence • These may be hybrid: use multiple heterogeneous intelligence models • Chapter 9, describes the interaction between multiple ISs Ubiquitous computing: smart devices, environments and interaction

8. Related Chapter Links • Many AI researchers see autonomy as a sub-type of intelligence. • Sometimes their notion of autonomy is not well-defined • In this text we separately autonomy and intelligence as main concepts – both as main types of property for UbiCom • A very rich model for autonomy is given in Chapter 10 • Relates the UbiCom properties of intelligence & autonomy Ubiquitous computing: smart devices, environments and interaction

9. Related Chapter Links • Reflexive Intelligent system models are related to: • Event-based system models (Chapter 3) • Sensor systems for the physical Environment (Chapter 6) • Controller systems for the physical Environment (Chapter 6) • Context-aware system design (Chapter 7) • Hybrid Goal-based environment model: • Based upon used of EDA, BB, pipe-filter interaction design (Chapter 3) • Used in context-aware system design (Chapter 7) • Used in autonomic computing designs (Chapter 10) • Monitoring & analysis of self rather than one’s environment • Self-awareness & Reflection (Chapter 10) Ubiquitous computing: smart devices, environments and interaction

10. Overview • Types of Intelligence and IS Model  • Reflex & Environment Models for IS • Goal and Utility based models for IS • Hybrids IS Models • KB IS Models • KB Management: Creation & Deployment • Knowledge Representations: rules, BB, semantics • Logic reasoning Models for IS • Soft Computing IS • Generic IS Operations Ubiquitous computing: smart devices, environments and interaction

11. Intelligent systems (IS): Introduction • Systems that use AI algorithms. • Also called • Machine intelligence or computational intelligence • Agent-based systems • AI effect ??? Ubiquitous computing: smart devices, environments and interaction

12. IS Introduction • IS Models often use analogies of human problem solving • IS models can be based upon physical organisations • But Machines may not problem solve like humans Ubiquitous computing: smart devices, environments and interaction

13. Human Intelligence vs. Machine Intelligence • Compare & Contrast • What complex tasks are humans good at and machines less so and vice versa? Ubiquitous computing: smart devices, environments and interaction

14. Types of Intelligence Can we define intelligence as any single concept in any single definition? Or is intelligence a multi-dimensional concept Ubiquitous computing: smart devices, environments and interaction

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16. Intelligent Systems (IS) IS vs. distributed system? Ubiquitous computing: smart devices, environments and interaction

17. UbiCom Systems that use an implicit notion of Intelligence Usage of term AI in general computing varies • HCI • Sensor / Context-aware systems • Control system & Robots • Intelligent networks • Network, e.g., SNMP, Agents • AmI • Smart devices Ubiquitous computing: smart devices, environments and interaction

18. Types of IS Model IS models can be classified in terms of: • Type of Model / Architecture • How a model is used to solve some problem • What is being modelled • What types of environment, a system is situated in, and can operate in • How are the models in an IS acquired? Ubiquitous computing: smart devices, environments and interaction

19. Types of IS Model Representations IS models can be classified in terms of: Basic types of IS Representation • Process-driven systemmodels: • Data-driven KB-IS models: • Logic –based KB-IS models: • Soft Computing models: Ubiquitous computing: smart devices, environments and interaction

20. Unilateral System Environment Interaction Models • Generally when ubiquitous system applications are designed, a unilateral model of the environment is used. Explain this? Ubiquitous computing: smart devices, environments and interaction

21. Unilateral versus Bilateral System Environment Models • Generally when ubiquitous system applications are designed, a unilateral model of the environment is used, • system models its environment, not vice-versa • However, as we move to smarter environments • Environments can be designed to contain a model of application systems which are situated in them or pass through them • Environment can be considered itself as an active, smart system Ubiquitous computing: smart devices, environments and interaction

22. Unilateral versus Bilateral System Environment Models Ubiquitous computing: smart devices, environments and interaction

23. Bilateral System Environment Models • A system that models an active environment • And in turn, the active environment has a model of the systems which use it • Designers of systems may to take into the account the degree of intelligence of environments Ubiquitous computing: smart devices, environments and interaction

24. IS Environment Types • It is a challenge for any system to act in open system environments. • Russell and Norvig (2003) have categorised open system environments along several dimensions . • Simplest types of system environments are those that are fully-observable, episodic and static. • More complex designs for intelligent systems are needed to think and act in environments that: are uncertain and non-deterministic etc. Ubiquitous computing: smart devices, environments and interaction

25. IS System Environment Types Ubiquitous computing: smart devices, environments and interaction

26. IS Environment Types • Open system environment are often stochastic. Why? Ubiquitous computing: smart devices, environments and interaction

27. IS Environment Types • Discuss examples of these System Environment Types: Ubiquitous computing: smart devices, environments and interaction

28. What is Modelled and How the Model is Acquired • What is Modelled? • Different ways to acquire the model? Ubiquitous computing: smart devices, environments and interaction

29. When Models are Acquired: At Design Time Contrast acquiring the model itself versus acquiring the content to populate the model 2 main ways to design how the model a acquired? • Models can be built into system at design time & modified at run-time • Models can be built at design time so that they can modify themselves at run-time Ubiquitous computing: smart devices, environments and interaction

30. When Models are Acquired • Models can be created by a human designer & built into system at design time & upgraded later. • What are benefits? • ?? • What are the limitations? • ?? • Systems/ environment can acquire their models themselves, automatically • Hybrid model acquisition systems Ubiquitous computing: smart devices, environments and interaction

31. Overview • Types of Intelligence and IS Model • Reflex & Environment Models for IS  • Goal and Utility based models for IS • Hybrids IS Models • KB IS Models • KB Management: Creation & Deployment • Knowledge Representations: rules, BB, semantics • Logic reasoning Models for IS • Soft Computing IS • Generic IS Operations Ubiquitous computing: smart devices, environments and interaction

32. Should a UbiCom System be an IS? • Depends upon the nature of the application. • Depends upon the specific model of AI being used • Specific IS models can be used to build systems which support other UbiCom system properties such as context-awareness, autonomy and iHCI Ubiquitous computing: smart devices, environments and interaction

33. Basic Types of IS Model • (From Russel & Norvig 2002) • Reflex Based • Environment Model based • Goal based, Proactive • Utility based • Learning • Multi-IS, Hybrid IS Ubiquitous computing: smart devices, environments and interaction

34. Basic Types of IS Model Note also they can classify the types of IS model by the knowledge representation they use for their model • Rule-based • Light-weight Ontology • Heavy-weight Ontology • Active user versus active service processes Ubiquitous computing: smart devices, environments and interaction

35. Types of IS Model & Types of Environment They Suit Ubiquitous computing: smart devices, environments and interaction

36. Reactive IS Models (R-IS) • Intelligent behaviour arises out of system’s interaction with environment rather than as result of complex internal knowledge representation or reasoning about events. • Action selection is at heart of the intelligent system. • in the simple case is driven by current state of environment. • R-IS is strongly situated in its environment and is highly responsive to changes in the environment. Ubiquitous computing: smart devices, environments and interaction

37. Pure versus Hybrid R-IS Models • R-IS tend to be designed as event-based systems • Pure reactive type of IS works best when? • In practice many systems are designed not to be purely reactive • These represent hybrid reactive systems. Ubiquitous computing: smart devices, environments and interaction

38. (Pure) R-IS Model Ubiquitous computing: smart devices, environments and interaction

39. R-IS Design: Present action Rule-based actions • Preset actions may be directly triggered from sensor input without any conditions • Alternatively events can be filtered by conditions / rules in order to trigger actions Ubiquitous computing: smart devices, environments and interaction

40. R-IS Design: handling multiple concurrent & heterogeneous events 3 possible designs: • Discard events • Event persistence • Concurrent Event Handling Ubiquitous computing: smart devices, environments and interaction

41. R-IS Design: handling multiple concurrent & heterogeneous events Ubiquitous computing: smart devices, environments and interaction

42. UbiCom Systems based upon R-IS • R-IS design is good design for minimum context-aware C-A) system Ubiquitous computing: smart devices, environments and interaction

43. Environment Model based IS (EM-IS) • EM-IS ~ KB system: knowledge about world & its actions. • EM-IS models historical behaviour of its environment. • System environment may be partially observable. Why? Ubiquitous computing: smart devices, environments and interaction

44. EM-IS • How to handle partial observability of environment? Ubiquitous computing: smart devices, environments and interaction

45. EM-IS Ubiquitous computing: smart devices, environments and interaction

46. EM-IS • IS’s actions depend upon current environment state, past environment states & on knowing effect of system actions • Similar to a situated action type of system design: • actions can be unplanned and depend strongly on context • Can anticipate multiple future environment states, which may never be realised leading to a theory of multiple possible future environments or world states. • EM-IS not include a model of the internal behaviour, e.g., processes of actions by the system Ubiquitous computing: smart devices, environments and interaction

47. EM-IS • Systems that build such a model of the environment enable their services & applications to optimise & adapt their behaviour to account for behaviours in environment which are not accessible but which are predetermined (as defined in the environment model). • E.g.,, in the adaptive transport scheduling scenario, • In pure R-IS, vehicle will not stop when no passengers are at pickup point (providing no passengers on the vehicle wish to leave). • EM-IS: ….. Ubiquitous computing: smart devices, environments and interaction

48. Overview • Types of Intelligence and IS Model • Reflex & Environment Models for IS • Goal and Utility based models for IS  • Hybrid IS Models • KB-IS Models • KB Management: Creation & Deployment • Knowledge Representations: rules, BB, semantics • Logic reasoning Models for IS • Soft Computing IS • Generic IS Operations Ubiquitous computing: smart devices, environments and interaction

49. Goal-based IS (G-IS) • Also referred to as planning-based IS, defines an internal plan or sequence of actions to achieve a future system goal • Unlike EM-IS, action selection for a G-IS depends on which next system action brings system towards future goal state • G-IS tends to dissociate control of actions from environment situation or context of action (unlike EM-IS) • G-IS vs. R-IS, events which trigger system actions as external events • In G-IS, internal events, e.g., a scheduled system task that becomes delayed, can also trigger system actions. • Main benefit of G-IS: users can delegate tasks at a much higher level of abstraction, focussing on what needs to be achieved rather than on details of how this is achieved Ubiquitous computing: smart devices, environments and interaction

50. G-IS Ubiquitous computing: smart devices, environments and interaction