[Week 1] Overview of problems and problem solving.pptx

www.covenantuniversity.edu.n Overview of Problems and Problem solving Concepts Lecture Note (Week 1) The CSC122 Team 1 2  Learning Objectives  Understand what a problem is in computing terms  Describe the difference between heuristi...

www.covenantuniversity.edu.n Overview of Problems and Problem solving Concepts Lecture Note (Week 1) The CSC122 Team 1 2  Learning Objectives  Understand what a problem is in computing terms  Describe the difference between heuristic and algorithmic solutions to problems  List and describe the six problem-solving steps to solve a problem that has an algorithmic solution.  Use the six problem-solving steps to solve any problem 3  Lecture Outline  What is a Problem?  Types of Problems  What is Problem Solving?  Solution Techniques  Problem Solving using Computers  Process Of Problem Solving (6 steps) 4  What is a Problem?  Problems exist in every area of our daily lives – List Specific Examples of Problems  Problems are obstacles to overcome. – E.g. Solve a Maths equation, Make a decision, accomplish a task etc.  A Problem can be defined as an unpleasant situation or condition which a better or perfect state is desired. – The situation is referred to as the present state, and the desired state is known as the goal state. 5  Reaching the goal state is achieved by following – a sequence of steps which can be either simple or complex.  Inputs made to the present state is what determines if the desired goal stage will be reached. – Therefore a problem is defined by its input and the property of its desired goal state. 6  Types of Problems  Routine Problems – A problem with a simple, and predictable solution. Solve a math problem, spell a word etc.  Non-routine Problems – A problem with subjective, abstract and complex solutions. – More difficult to solve Arrange 10 popular languages from best to least 7  Problem Solving Problem solving is the application of ideas, skills, or factual information as inputs in specific sequence of steps to attain to the solution to a problem or to reach a desired goal state. 8  Problem Solving  The sequence of steps is called the Solution to the problem. – The solution of a problem will take defined inputs and produce the desired output. Solution Specific Desired to the Input State Problem 9  Problem Solving  However, – One problem can have multiple solutions, But the aim of computer programmers is to find the best solution to the given problem. – Not all Problems have straight-forward solutions, Some require a series of trial and error before a solution can be reached 10  In-class Interaction [5Mins]  List some problems that have more than one solution – Identify the best solution?  List some problems with solutions that would involve trial and error? 11 Types of Solution Approaches  In computer programming, there are two classifications of solutions to problems – Algorithmic Solutions – Heuristic Solutions 12  Algorithmic Solution  These are solutions to problems in which the desired state is achieved by a defined and finite sequence of steps – E.g. to make pizza, to get the CST building from the Hostel, to determine the number of rooms in Senate Building etc.  The sequence of steps it takes to arrive at the goal/desired state is called Algorithm. 13  Heuristic Solutions  These are solutions to problems in which the goal state is reached by series of steps which emerge – From Knowledge and Experience – From various Trials and Error  Therefore, solutions that cannot be reached by direct steps are called Heuristics Solutions. – For Example Making a speech at an event, playing and winning a soccer game, find the right marriage partner. 14  Focus of this Course  This course is mainly concerned with Algorithmic solution to problems, – Which can be solved by the computers.  Heuristics solutions are achieved – Using artificial intelligence techniques. E.g. Artificial Neural Network, Fuzzy Logic, Constraint Optimization etc. 15  Some Solution Techniques (1 of 5)  Abstraction – Solving the problem in a model of the system before applying it to the real system  Analogy – Using a solution that solved an analogous problem  Brainstorming – Suggesting a large number of solutions or ideas and combining and developing them until an optimum is found(especially among groups of people) 16  Some Solution Techniques (2 of 5)  Trial-and-Error – Testing possible solutions until the right one is found  Hypothesis testing – Assuming a possible explanation to the problem and trying to prove (or, in some contexts, disprove) the assumption  Reduction – Transforming the problem into another problem for which solutions exist 17  Some Solution Techniques (3 of 5)  Lateral thinking – Approaching solutions indirectly and creatively  Means-ends analysis – Choosing an action at each step to move closer to the goal (e.g. sorting numbers)  Method of focal objects – Synthesizing seemingly non-matching characteristics of different objects into something new  Morphological analysis – Assessing the output and interactions of an entire system 18  Some Solution Techniques (4 of 5)  Research – Employing existing ideas or adapting existing solutions to similar problems  Root cause Analysis – Identifying the cause of the problem  Proof – Try to prove that the problem cannot be solved. The point where the proof fails will be the starting point for solving it 19  Some Solution Techniques (5 of 5)  Divide and Conquer (D&C) – Breaking down a large, complex problem into smaller, solvable problems 20  Solving Problems with Computers  Computers are built to deal with algorithmic solutions, – Often difficult or very time consuming for humans.  Solving a complex mathematical equation or arranging 3000 names in alphabetical order is an easy task for the computer. 21 Problem Solving: Humans & Computers  Human beings can arrive at heuristic solutions better than computers.  For humans, these problem are not difficult – Identify a human’s voice, play free kicks or how to speak Spanish  For computers, the difficulty is in programming the machine to solve the problem: – How can computers be programmed (in a set of steps) to play free kick, or speak Spanish? 22  However…  The field of Computer Science that deals with heuristic types of problems is called Artificial Intelligence (AI). – AI enables a computer to do things like build its own knowledge-bank and speak in a human language.  In AI, computers and computer software are capable of intelligent behavior and the goals of AI includes: – Reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects etc. 23  6 Steps of Solving any Problem 1. Identify the Problem 2. Understand the Problem 3. Identify alternative solutions to problem – Create a list of possible solutions 4. Select the best way to solve the problem from the list 5. List out the instructions that are involved in the selected solution to the problem 6. Evaluate the solution 24  Identify the Problem  The first step of solving any problem is to – Identify the problem  You must ask, what is the problem? – A set of problems may be given to you by the instructors, or you may have to identify a problem on your own.  A problem not known cannot be solved. 25  Understand the Problem  Understanding the problem entails, having a good knowledge base of the problem.  For Example Solving – Computer hardware problem, requires knowledge about computer parts. – Calculus problems requires knowledge of calculus  In providing solution, one must communicate with the client and understand what is involved in solving the problem. 26  Identify alternative Solutions to Problem  A problem might have more than one solution. – List as many alternate solutions as much as possible. – Interacting with others in a brainstorming session, could provide insights to alternative ways of solving the problem.  Create a list of all the possible ways to solving the problem 27  Select the best Solution  Evaluate the Pros and Cons of each of the possible solutions – The evaluation would determine the best solution to select 28  List Instructions Involved in the Solution  The instructions are the step-by-step procedures that will be followed to arrive at the desired goal state. – Instructions are useless except understood by the individual or machine. – Instructions must be in: Human or Computer-readable forms  These Steps are called ALGORITHMS 29  Evaluate Solution  In evaluating the solution, the result of the solution is checked to ensure correctness.  Also the solution must meet/satisfy the need of the person, or the situation requesting the solution.  If the result is unsatisfactory or incorrect, – The list of instructions must be reviewed or – The other 5 Steps must be repeated. 30  6-Steps in Action  Lets Explore the 6 Steps in Action 31  Identify the Problem How does Someone get to CST Building from Daniel Hall in 10 Mins? 32  Understand the Problem  The knowledge base of the individual and the layout of the campus must be considered.  Also the various constraint of the campus should be known, – e.g. one would not include using a private-jet or helicopter as solutions. 33 Identify Alternatives Solutions  Use a Cab  Use a bicycle  Drive a personal car  Use Shuttle Bus  Walk through the Female Halls area  Jogging  Walk through the main road  Ask for a Lift from vehicles passing by 34  Select the best Alternative  To select the best, weed out alternatives that are not acceptable, – e.g. those that would require much money, energy or time.  Specify the pros and cons,  Make a final decision. 35  List the instructions  Prepare a list of instructions (Steps) that will be taken, in the minutest detail that will result in getting to CST Building in 10 minutes 36  Evaluate the Solution  See if the result matches the expectation of the problem.  If not, the instructions (Steps) should be reviewed or the overall process should be repeated. 37  Assignment  Write Short Notes on 5 Solution Techniques highlighted in this lecture note. – Maximum of 3 Pages – Submission via Moodle – Lifeline: 38