© C. Kemke Constructive Problem Solving 1 COMP 4200: Expert Systems Dr. Christel Kemke Department of Computer Science University of Manitoba.

© C. Kemke

Constructive Problem Solving 1

COMP 4200: Expert SystemsCOMP 4200:

Expert Systems

Dr. Christel Kemke

Department of Computer Science

University of Manitoba

© C. Kemke

Constructive Problem Solving 2

COMP 4200: Expert Systems COMP 4200: Expert Systems

Constructive Problem Solving I cf. Jackson, Chapter 14

Constructive Problem Solving II cf. Jackson, Chapter 15

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Constructive Problem Solving 3

Task Areas of Expert Systems

Task Areas of Expert Systems

System-Based View of XPS Task Analysis Tasks (Interpretation of System)

Diagnosis Classification

Synthesis Tasks (Construction of System) Construction Configuration Design Planning

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Constructive Problem Solving 4

Constructive Problem SolvingConstructive Problem Solving

Solution constructed by choosing and assembling solution elements.

Examples: develop a plan for a robot to bring a cup of coffee from IQ; construct a system, e.g. a computer, by assembling a set of components, like HD, CPU etc.

Solution elements are described as components (maybe with parameters); assembly is subject to constraints (robot cannot go to IQ if it cannot take the elevator; certain CPUs need certain power supply); solution might be subject to evaluation function

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Constructive Problem Solving 5

Constructive PS and Task AreasConstructive PS and Task Areas

Planningsolution elements = actionssolutions = sequence of actionsconstraints = e.g. physical or logical constraints

Designsolution elements = componentssolutions = combination of componentsconstraints = e.g. physical or logical constraints

Diagnosis of multiple disorderssolution elements = disorderssolutions = sets of disorders to explain the symptoms ;

determine 'best' set according to evaluation

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Constructive Problem Solving 6

Constructive PS ApproachConstructive PS Approach

Choose combination of solution elements set sequence complex arrangement

Combined according to constraints order (sequence of steps; arrangement of components) time (sequence of actions in time; limit of time) spatial arrangement (layout in space, e.g. floor plan) features and their agreements (e.g. matching voltage for

electrical components, matching colors for cloths) ...

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Constructive Problem Solving 7

Constructive PS as SearchConstructive PS as Search

Search Space: all combinations of solution elements

Search Space can be huge!

Restrict search by selecting solution elements based on known constraints; selection of new components is restricted through constraints.

Constraints can be formulated in rules:IF device requires battery THEN select battery for deviceIF select battery for device THEN pick battery WITH voltage(battery) = voltage(device)IF device requires battery AND device = watch THEN select micro-battery

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Constructive Problem Solving 8

Constructive PS - R1/XCONConstructive PS - R1/XCON

R1/XCON developed to design DEC VAX computer systems (early 1980ies)

R1 uses a database of computer components a rule base specifying design rules and constraints a working memory (WM) to store interim structures, in

particular the partial computer configuration generated so far

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Constructive Problem Solving 9

R1/XCON – Sample Component Jackson, p. 262, Figure 14.1

R1/XCON – Sample Component Jackson, p. 262, Figure 14.1

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Constructive Problem Solving 10

R1/XCON – Types of RulesR1/XCON – Types of Rules

Rule types related to tasks in PS:

1. Operator Rulescreate and extend partial configurations

2. Sequencing Rulesdetermine order of processing (contexts, modules)

3. Information-Gathering Rulesaccess database of components; perform various computations

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Constructive Problem Solving 11

R1/XCON – Sample RuleJackson, p. 262, Figure 14.2

R1/XCON – Sample RuleJackson, p. 262, Figure 14.2

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Constructive Problem Solving 12

R1/XCON – Basic PrinciplesR1/XCON – Basic Principles

R1 selects component from DB; entered as ‘token’ (instance) into Working Memory (WM).

Rules specify configuration patterns (conditions, constraints) and actions for extending partial configurations (consequences).

Rule set divided into "contexts" (modules) according to sub-tasks.

Strategy Finish a sub-task before starting a new one.

Implementation Add contexts to condition part of rules. Switch to new context in the action part.

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Constructive Problem Solving 13

R1/XCON – Sub-TasksR1/XCON – Sub-Tasks

1. Check and complete order.2. Configure CPU.3. Configure unibus modules, prepare cabinets

with modules.4. Configure paneling; assign panels to unibus

modules and devices.5. Generate floor plan. Device arrangement.6. Cabling.

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Constructive Problem Solving 14

R1/XCON – Problem SolvingR1/XCON – Problem Solving

Propose-and-Apply (Bachant 1988):

1. Initialize Goal (for current task)

2. Propose Operator (plausible next steps)

3. Prune Operator (according to global criteria)

4. Eliminate Operator (pairwise comparison)

5. Select one Operator (based on 2-4)

6. Apply Operator (extend configuration)

7. Evaluate Goal (okay? or not?)

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Constructive Problem Solving 15

R1/XCON - ConclusionR1/XCON - Conclusion

DB of components constraints and actions in rules about 10.000 rules defined and used integrate various experts' knowledge heavily based on "what-to-do-next" follows always one line of reasoning control through contexts (modules)