The natural language
The question "Do you know what time it is" in natural language has different meaning in the way we understand it.
First, the person asking you the above might want you to tell him or her what the time is maybe by looking at your wrist watch or wall clock, the above question may be reframed like this "Please Sir/Ma, could you tell me what the time is ".
Secondly, the person asking the above question is trying to tell you that you are late, that you actual look at the time you are coming. The above question may be reframed like this "Do you know you are late".
Examples of declarative knowledge:
- A cathode ray tube is used to project a picture in most televisions (Decision Automation, 2007)
- Water is composed of hydrogen and oxygen.
- George Washington was the first president of the United States
Examples of Procedural knowledge:
- Reading a Chart - Read the title, look at the headings, view the data, draw conclusions from the data.
- Writing a Lesson Plan - review, focus, input, practice, independent practice, and review of the day's lesson.
Assume the 1st weight in the 1st rectangles are 2 and 1, the 1st threshold is 1.8 (Brookshear, 2009)
Assume the 2nd weight in the 2nd rectangles are 2, -1 and 3, the 2nd threshold is 3.8
If both inputs are 1s,
Then 1st rectangle output will be (1*2) + (1*1) = 2+1 = 3, since the result threshold(1.8), output is 1
Then the inputs for the 2nd rectangles now be 1, 1 and 1
The 2nd rectangle output will be (1*2) + (1*(-1)) + (1*3) = 2 - 1 + 3 = 4, since the result threshold(3.8), output is 1
If both inputs are 1 and 0,
Then 1st rectangle output will be (1*2) + (0*1) = 2 + 1 = 2, since the result threshold(1.8), output is 1
Then the inputs for the 2nd rectangles now be 1, 1 and 0
The 2nd rectangle output will be (1*2) + (-1*1) + (0*3) = 2 - 1 + 0 = 1, since the result threshold(3.8), output is 0
Assume a salesperson already has a list of cities he wants to visit and the condition is that he must visit each city only once, so there are distinct routes between the cities. The problem will for him to find how to get the shortest route between the cities so that the salesperson visits all the cities once (CS, n.d.). We will use heuristic search to achieve this problem
Applying this concept to the travelling salesperson problem.
- Randomly, you select a city as your start point;
- now you choose the nearest one to the current city, then go to it;
- until you visit all cities.
In this case, the start state is the current location
The goal state is the target location
The production is the simple change of location.
Brookshear, J. Glenn (2009) Computer Science: An Overview, 10th Ed. Boston: Pearson Education Inc.
CS (n.d.) Problems Problem Spaces and Search [Online] Available from http://www.cs.cf.ac.uk/htbin/Dave/AI/ai.pl?AI1/search.html+q_ans+prob_decomp+AI1/AI1.html+Lecture_8:_Simple_Production_System+Lecture_10:_Problem_Decomposition+AI_TOP_LEVEL+LECTURE_9:_Problems_Problem_Spaces_and_Search (Accessed: 13 March 2010)
Decision Automation (2007) Declarative Knowledge [Online] Available from http://decisionautomation.com/glossary/14.php (Accessed: 13 March 2010)