1. Generic Task
Routine Design

2. Outline Routine Design Definition.
Problem Decomposition & Specialists Hierarchy.
Routine Design Agents.
Specialist, Plan, Task, Step, Plan Sponsor, Constraint, and Table Matcher.
Routine Design Structure.
Routine Design Algorithm.
Multiple Design Definition.
The Differences Between Single and Multiple Designs.
Design Tree, Design Limiter, Specialist Selector Interacting, and Table Matcher.
Case Storing & Loading.
Mapping.

3. Routine Design Definition
It is a problem solver that has been identified for the solution of planning or more generally designed problems.
Design Constraints: Set of input attributes.
Design Specification: Set of output attributes.
Design
Constraints
Routine
Design
Design
Specification
Information processing task of Routine design

4. Problem Decomposition & Specialists Hierarchy
Any problem can be decomposed into a set of simpler sub-problems and each sub-problem can be also decomposed into another set of simpler sub-problems and so on.
The Routine design approach is based on hierarchy of cooperating specialists, each responsible for an identified part of a complete design (solving a specific problem).
The decomposition of a design problem solver into a hierarchy of specialists mirrors the decomposition of the design problem into sub-problems.

5. Problem Decomposition
Sub-Problem
Sub-Problem
Problem
Problem Decomposition
More Conceptual Aspects of the design process
Specialist
Specialist
Specialist
More Parametric Aspects of the design process
Specialist Hierarchy

6. Routine Design Agents 1. Specialist Specialist Initial constraints
It is a place holder for the design plans and the selection mechanism for selecting among the different plans.
One plan is chosen by a selector according to the input data and/or the current problem solving status.
The selector consults sponsors of different plans and decides which plan to invoke.
Each specialist has a plan selector, a set of plans to choose from, and maybe contains initial and final constraints.
Initial constraints
Specialist
Selector
Sponsor Plan2
Sponsor Plan1
Final constraints

7. 2. Plan: -
It specifies the course of action to be taken to pursue the design from the current status.
It may contains other specialists, tasks, constraints, and other Problem Solvers in an order dependent upon the problem being solved.
Specialists
Tasks
Plan
Constraints
Problem Solvers

8. It is a collection of related steps.
3. Task: -
It is a collection of related steps.
Task
Step n
Step 1 :
4. Step: -
It is the basic design action in Routine Design. It is responsible for setting the value of one design attribute.
It maybe uses a table matcher or calls another problem solver.
Step
Table Matcher
Problem Solver OR

9. 5. Plan Sponsor: - 6. Constraint: - Plan Sponsor Table Matcher
It determines if its plan is suitable (and how suitable).
It tags its plan belonging to one of the following four categories: -
Perfect for the current situation.
Suitable for the current situation.
Not sure.
Not applicable for the current situation.
Plan Sponsor
Table Matcher
6. Constraint: -
It is in the form of a comparison between the values of two design attributes. If the result of this comparison is false then the current agent will fail.

10. 6. Table Matcher (Pattern Matcher): -
It consists of a set of rows, each row consists of condition side and action side. The condition side is a conjunction form in set of attributes and the action side assigns a value for some output attribute.
Action Part
Condition Part

11. Routine Design Algorithm
1. Collect the input attributes and display it.
2. Set the selected attributes in the current case with their values.
3. Invoke the top level specialist.
4. The top level specialist checks its initial constraints (if any exist).
5. The top level specialist requests its selector to select a plan.
6. The selector asks the sponsors of the different plans to assess the applicability of their respective plans.
7. The sponsors examine the current design status and the input data and assign applicability ratings to their plans.
8. The selector examines the applicability ratings and selects a plan.
9. Invoke the chosen plan that will take one or more of the following actions:-
(a) Invoke other specialists, then each one will follow a scenario similar to that followed by top level specialist.
(b) Execute tasks. These tasks consists of steps each of which a computation or uses a table matcher to assign a value to a design attribute.
(c) Check constraints.
10. The top level specialist checks its final constraints (if any exist).
11. Collect the output attributes and display it.

12. Multiple Design Definition
It is an approach for generating multiple designs (solutions) satisfying a common set of design requirements and constraints.
Multiple
Design
Requirements
& Constraints
Set of Designs
Design (Solution) is a set of values for some
output attributes.

13. The Differences Between Single and Multiple Designs
Design Database (Tree)
For a given set inputs ( design requirements ) a multiple design system generates a group of trees, where each node represents a value for a design attribute.
Each path from a root to a leaf node represents a complete design (solution).
The Multiple Design deals with the design tree on behalf of the current case to satisfy each design alone.
Att1 = V1a
Att2 = V2a
Att2 = V2b
Att3 = V3d
Att3 = V3a
Att3 = V3b
Att3 = V3c
A graphic representation of a typical multiple design output

14. Design Tree Construction Algorithm
There are two variables are used in this algorithm. They are Current_Nodes and Current_Agent to store the current nodes and current agent respectively.
1. First, the input attributes branch is built.
2. Current_Nodes = last node in the above branch.
While ( Agents Relation is executed ) do step 3.
3. If ( Current_Agent = Specialist )
Then {Pass Current_Nodes to the selected plan in an order. }
Else If ( Current_Agent = Plan OR Task )
Then { Pass Current_Nodes to its first item, then the returned nodes from this item are sent to the next item and so on. }
Else If ( Current_Agent = Step )
Then { Check each row of Current_Agent’s table matcher against each of the
paths ending at the nodes passed to it, adding the result of the row to
the paths satisfying the conditions of that row. }.
4. Filter the design tree from input attributes.
Design Tree Construction Algorithm

15. Example: - This example describes how the design tree is constructed.
Specialist
Plan1
Plan2
Task11
Task12
Task21
Task22
Step111
Step112
Step121
Step211
Step221
Design Tree Construction steps
Spec. Call Plan1( [ N1 ] )
Plan1 Call Task11( [ N1 ] , [ N4 ] )
Task11 Call Step111( [ N1 ] , [ N2 , N3 ] )
Task11 Call Step112( [ N2 , N3 ] , [ N4 ] )
Plan1 Call Task12( [ N4 ] , [ N5 , N6 ] )
Task12 Call Step121( [ N4 ] , [ N5 , N6 ] )
Spec. Call Plan2( [ N1 ] )
Plan2 Call Task21( [ N1 ] , [ N7 , N8 ] )
Task21 Call Step211( [ N1 ] , [ N7 , N8 ] )
Plan2 Call Task22( [ N7 , N8 ] , [ N9 , N10 ] )
Task22 Call Step221( [ N7 , N8 ] , [ N9 , N10 ] )
Agents Hierarchy

16. The Constructed Design Tree
Spec. Call Plan1( [ N1 ] )
Plan1 Call Task11( [ N1 ] , [ N4 ] )
Task11 Call Step111( [ N1 ] , [ N2 , N3 ] )
Task11 Call Step112( [ N2 , N3 ] , [ N4 ] )
Plan1 Call Task12( [ N4 ] , [ N5 , N6 ] )
Task12 Call Step121( [ N4 ] , [ N5 , N6 ] )
Spec. Call Plan2( [ N1 ] )
Plan2 Call Task21( [ N1 ] , [ N7 , N8 ] )
Task21 Call Step211( [ N1 ] , [ N7 , N8 ] )
Plan2 Call Task22( [ N7 , N8 ] , [ N9 , N10 ] )
Task22 Call Step221( [ N7 , N8 ] , [ N9 , N10 ] ) N1 N2 N3 N7 N8 N4 N9
N10 N5 N6
Output Design Tree

17. Design Limiter Definition: -
- It is in the form of a table matcher and it is used to exclude the designs (solutions) that are known from experience to not be favorable if other designs exist.
It is invoked at two levels, step and task levels. N1 N3 N7 N4 N9
N10 N5 N6

18. Specialist Sponsor Interacting
If (all returned plans within a ranking category fail)
Then { The next ranking category are used and so on }
If (all plans fail)
Then { This specialist will fail }
Specialist
Selector
Set of
Plans
Call
Set of highest
category plans

19. Table Matcher In Multiple Design
Condition Part
Action Part
Example
Single Design
Multiple Design

20. New Case Directory Structure
Case Storing & Loading
Each Problem Solver accesses its current case. So, when we will be storing the Neper’s current case, we must store the other current cases of other Problem Solvers.
We changed the case file format to avoid the compiler error and the directory structure that will be used in storing as shown in the next figure.
< selected directory>
<case name>Neper.case “Neper’s case”
<case name>_subs “New Folder”
<case name>Planting.case “Planting’s case”
<case name>Harvest.case “Harvest’s case”
New Case Directory Structure
Note that:- The selected directory must be ended with “\”.

21. Mapping
It is an important feature that allows the Problem Solvers to interchange the values of their attributes.
Example: -
Neper
Planting
Irrigation
Input
output