ADVANCED INTELLIGENT SYSTEMS

1
Chapter 13

• ADVANCED INTELLIGENT SYSTEMS

2
Learning Objectives

• ??????????????????????????????????????????????????
  ????????? (machine-learning)
• ?????????????????????????????????????????
  case-based systems
• ??????????????????????????????????????????
  genetic algorithms
• ???????????? fuzzy set theories
  ???????????????????????????? intelligent systems
• ??????????????????????????????????????????
  natural language processing (NLP)
• ??????????????????????????? ????????????
  ?????????????? voice technologies
• ????????????????? integrated intelligent support
  systems

3
Machine-Learning Techniques

• ????????????????????? Machine-learning
• Machine learning
• ????????????????????????????????????????????????
  (???? ????????????????????????????????????????? ?
  ??????? (historical cases))

4
Machine-Learning Techniques

• ??????????????????????????????????????????????????
  ?????????????? ? ???????????????????? ?????????
• Induction (??????????????????? ? ??
  ???????????????????????)
• Deduction (?????????????????????? ?
  ??????????????? ? ????????)
• Analogy (?????????????)
• ?????????????????? ? ?????????????????????????????
  ?????????????????????

5
Machine-Learning Techniques

• ?????????????????????? intelligent system ???????
• ??????????????????????????????????????????????????
  ????????
• AI ???????????????????????????????????????? ????
  ??????????????????????
• Machine learning ?????????????????????????????????
  ???????? ?????????????????????????????????????????
  ???? ?????????????????????????????
• ?????????????????????? learning systems
  ????????????????????????????
• ???????????????? ? ????????????????????? AI
  ??????????????????????? ???????????????????????
  (symbols) ??????????????????????????????

6
Machine-Learning Techniques

• ?????????????????????????????
• Supervised learning
• ??????????????? artificial neural networks
  ??????????????????????????????????????????????????
  ??????????????????????????????????????????????????
  ???????????????????????????????????????????
• Unsupervised learning
• ???????????? artificial neural networks
  ?????????????????????????????????????????
  ?????????????????????????????? (self-organizing)

7
Machine-Learning Techniques
8
Machine-Learning Techniques
Machine-learning methods and algorithms

• Inductive learning
• Case-based reasoning
• Neural computing
• Genetic algorithms
• Natural language processing (NLP)
• Cluster analysis
• Statistical methods

• Explanation-based learning
• A machine learning approach that assumes that
  there is enough existing theory to rationalize
  why one instance is or is not a prototypical
  member of a class

9
Case-Based Reasoning (CBR)

• Case-based reasoning (CBR)
• ???????????????????????????????/?????????????????
  ??????????????????????????? (historical cases)
• Analogical reasoning
• ????? outcome ??????????????????????????????
  ??????????????????????????????????????????????????
  ??????????? (past experience)
• Inductive learning
• ?????????????????????????????????????????????????
  ???????????????????????????)

10
Case-Based Reasoning (CBR)

• ???????????????????????????????? CBR
• ?????????????? ???
• Retrieve (???????)
• Reuse (???????)
• Revise (??????????????)
• Retain (????)

11
Case-Based Reasoning (CBR)

• ????????????????????? cases ?? CBR
• Ossified cases (harden cases)
• Case ??????????????????????????? further value
• Paradigmatic cases
• Case ??????????????? unique ?????????????????????
  ???????????????????????????????
• Stories
• Cases ????????????????????????????????
  ????????????????????????????? case ????????

12
Case-Based Reasoning (CBR)
13
Case-Based Reasoning (CBR)

• ?????????????? CBR
• ?????????????????????????????????
• ?????????????????????????
• ????????????????????????????????????????
• ???????????????? Complete formalized domain
  knowledge
• ??????????????????????????????????????????????
  concrete cases
• ??????????????????????
• ????????? case ???? ? ????????
• ??????????????????????????????????????????????????
  ?????

14
Case-Based Reasoning (CBR)
15
Case-Based Reasoning (CBR)

• ????????? ??????????????????? ????????????????????
  CBR
• ??????????????
• CBR in electronic commerce
• WWW and information search
• Planning and control
• Design
• Reuse
• Diagnosis
• Reasoning

16
Case-Based Reasoning (CBR)

• ????????????????????????????????????????????
• ??????????????????? case ????? ? ??????? ???????
  case ???????????????????????????
• ????????????????????????????? (automatic
  case-adaptation rules) ???????????????????????????
  ????
• ?????????????????????????????? ??????? indexing
  rules?
• ????????????????????????? index
  ??????????????????????
• ??????????????????????????????????????????????????
  ??????????????????? ?
• ???????????????? case ????????????????????????????
  (???? knowledge navigation)?

17
Case-Based Reasoning (CBR)

• ??????????????? case ???????????????????
• ??????????? distributed storage ??? case
  ???????????????????
• ?????????????????????? ? ?????????????????????????
  ???? ? ??????????? ??????????????????????????????
  ???????????? ? ?????? efficient querying
  ?????????? context ??????????? ???????????????????
  ??? ? ?????????????????????? rule ???? ? ????
• ??????????? factor errors ?????? original cases
  ???????????
• ??????????????????????????????????????????????????
  ?????????????????????????????? case base
  ?????????????????????

18
Case-Based Reasoning (CBR)

• Case base ????????????????????????????????????
  model ????????????????????? ????????????????????
  ? ???????????? ? ??????????????
• ???????? CBR ??????? knowledge representations
  ??? inferencing mechanisms ???? ? ???????????
• ?????????????? pattern-matching
  ???????????????????????????????????????
• ???? retrieval system ???? ? ??????????????????
  match ??? CBR schema ????????

19
Case-Based Reasoning (CBR)

• ???????????????? CBR system ???????????????
• ???????????????????????????????????????????
• ????????????? end users ??? customers
• ??????????????????????????????
• ????????????????????????????????????????????????
• ???????????? returns on investment (ROI)
  ????????????? ?
• ?????????????????????? customer-access strategy
• ??????????????????????????????????????????????

20
Genetic Algorithm Fundamentals

• Genetic algorithms (GAs)
• ?????????????????????????????????????????????????
  ????????????????????????????

21
Genetic Algorithm Fundamentals

• Genetic algorithm process and terminology
• Chromosome
• ?????????????????????????? genetic algorithm
• Reproduction
• ????????????????????? (new generations)
  ???????????????????????????????????? genetic
  algorithm

22
Genetic Algorithm Fundamentals

• Crossover (???????????????)
• ?????????????? ? ??? two superior solutions
  ?????? genetic algorithm ?????????????????????????
  ???

23

• Mutation (?????????????)
• ????????????????????????????????????? random
  change ?? potential solution

24
Genetic Algorithm Fundamentals
25
Genetic Algorithm Fundamentals
26
Genetic Algorithm Fundamentals

• ???????????????????????? genetic algorithm
• Number of initial solutions to generate
• Number of offspring to generate
• Number of parents and offspring to keep for the
  next generation
• Mutation probability (very low)
• Probability distribution of crossover point
  occurrence

27
Genetic Algorithm Fundamentals

• ??????????? genetic algorithms
• ????????? ? ??????????????????????????????????????
  ??????? genetic algorithms ??????????
• ???????? genetic algorithm ??? ???????????????????
  ??? ??????????????????????????????????????????????
  ?????????????????????/???????????????????
  genetic algorithm technology ??????????
• ?????????????? genes ??? few comparatively
  highly fit (but not optimal) individuals may come
  to dominate the population, ???????????????
  converge ????? local maximum

28
Genetic Algorithm Fundamentals

• genetic algorithms ???????????????? random number
  generators ???????????????????????????????????????
  ???????????? model
• ??????????????????????????????????????????????????
  ???????????????????????????????
• ???????????????????????????????????????????
  ????????????????????????????????????????????

29
Developing Genetic Algorithm Applications
Applications of GAs include

• Dynamic process control
• Induction of optimization of rules
• Discovery of new connectivity topologies (e.g.,
  neural computing connections, i.e., neural
  network design)
• Simulation of biological models of behavior and
  evolution

• Complex design of engineering structures
• Pattern recognition
• Scheduling
• Transportation and routing
• Layout and circuit design
• Telecommunication
• Graph-based problems

30
Fuzzy Logic Fundamentals

• Fuzzy logic
• ?????????????????????????????????????????????????
  ??????????????????????????????????????????????????
  ? ??????????????????????????? ??? expert
  system ???? ? ????
• Fuzzy sets
• ?????????????????????????????????????????????????
  ??????????????????????????????????????????????????
  ????????????????

31
Fuzzy Logic Fundamentals
32
Fuzzy Logic Fundamentals

• ?????????????? Fuzzy logic ?????????????????????
• ???????????????? (???? Japanese Nikkei stock
  exchange)
• ????????????????? (???????? fuzzy logic
  ????????????????????????)
• ??????????????????????????????????????????????????
  
• ?????????????????????????????????????
• ????????????????????
• ?????????????????????????????????????????
• ??????????????????????????????????????????????????
  ?????????????????????????????
• ????????????? (Sorting problems) ??
  multidimensional spaces

33
Fuzzy Logic Fundamentals

• ??????????????? ? ???????????????????????????
  (???? ?????? (waiting lines))
• ?????????????????????????????????????????????????
• ??????????????? (Project selection)
• ???????????????????????????
• ?????????????????????????????
• ?????????????????????????????
• ????????????????????
• ????????????????????????????????

34
Natural Language Processing (NLP)

• ????????????????????????????? (Natural language
  processing (NLP))  
• ?????????????????????????????????????????????????
  ?????????????????????????
• NLP ??????????? ???
• ????????????????????? (Natural language
  understanding)
• ???????????????????? (Natural language
  generation)

35
Natural Language Processing (NLP)

• ?????????????????????? NLP ?????????????
• ?????????????????????
• ???????????????????
• ????????????????????????????
• ???????????????? ???? ??????????????
• ??????????????????????????

36
Natural Language Processing (NLP)

• ???????????? NLP ??????????
• ?????????????????????????????????
• ????????????? ?? ???? ????????????????????????????
  ????????????????????? ???????????? NLP
  ???????????????????????????????

37
Natural Language Processing (NLP)

• ?????????????? NLP
• ??????????????????? ????????????????????
• Abstracting and summarizing text
• ???????????????????? (Analyzing grammar)
• ?????????????? (Understanding speech)
• ??????????????? software package ???? ? ???? ???
  query ???????????????????????????? applications
  programs ????????????????? ? ???
• Text mining
• FAQs ??? query answering

38
Natural Language Processing (NLP)

• ?????????????? (Machine translation)
• ?????????????????????????????????????????????
• ?????????????????????? machine translation
• ???????? (Intelligibility)
• ??????????? (Accuracy)
• ???????? (Speed)

39
Voice Technologies

• ????????????????????????????????????????????? ?
  ???
• ????????????? (?????????) (Voice (or speech)
  recognition)
• ?????????????? (?????????) (Voice (or speech)
  understanding)
• Text-to-voice (???? ?????????????????? (or voice
  synthesis))

40
Voice Technologies

• Voice (speech) recognition
• ????????????????????????? ? ?????????????????????
  ????????????
• Speech understanding
• ???????????????????????????????????? AI
  ??????????????????????????????????????????????????
  ???????????????

41
Voice Technologies

• ??????????????? voice technologies
• ????????????????? (Ease of access)
• ??????????
• ??????????????????????? (Manual freedom)
• Remote access
• ????????????
• ?????????????????????
• ????????????????????????? (Quick selection)
• ????????????? (Security)
• ???????????????????????? (Cost benefit)

42
Voice Technologies

• ??????????? speech recognition ??? speech
  understanding
• ??????????????????????? ? ???? ???????????????????
  ?????????????????????????????????
• ?????????
• ?????????????????????????????????????
  ????????????????????????????????

43
Voice Technologies

• Voice synthesis
• ?????????????????????????????????????????????????
  ??? (text-to-speech)
• ???? text-to-speech ??????????????????????
• ??????????????????????????????????????????????????
  ???????????????????? symbolic linguistic
  representation
• ?????????????? symbolic linguistic representation
  ??????????????????????????????????????????????????
  ??????????????????????

44
Voice Technologies

• Voice technology applications
• Call center
• Contact of customer care center
• Computer/telephone integration (CTI)
• Interactive voice response (IVR)
• Voice portal
• Voice over IP (VoIP)

45
Voice Technologies

• Voice portals
• Web sites, usually portals, with audio interfaces

46
Developing Integrated Advanced Systems

• Fuzzy neural networks
• Fuzzification
• A process that converts an accurate number into
  a fuzzy description, such as converting from an
  exact age into young or old
• Defuzzification
• Creating a crisp solution from a fuzzy logic
  solution

47
Developing Integrated Advanced Systems
48
Developing Integrated Advanced Systems
49
Developing Integrated Advanced Systems

• Genetic algorithms and neural networks
• The genetic learning method can perform rule
  discovery in large databases, with the rules fed
  into a conventional ES or some other intelligent
  system
• To integrate genetic algorithms with neural
  network models use a genetic algorithm to search
  for potential weights associated with network
  connections
• A good genetic learning method can significantly
  reduce the time and effort needed to find the
  optimal neural network model

50
???????? 13

• ????? ..