CSC122 Week 1: Problem Solving Concepts

Overview of Problems and Problem-Solving Concepts

• A problem exists in every area of our daily lives and is defined as an unpleasant situation or condition that requires a better or perfect state to be desired.
• Problems are obstacles to overcome, and reaching the goal state is achieved by following a sequence of steps, which can be either simple or complex.

Types of Problems

• Routine Problems: problems with simple and predictable solutions, such as solving a math problem or spelling a word.
• Non-routine Problems: problems with subjective, abstract, and complex solutions, which are more difficult to solve.

Problem Solving

• Problem solving is the application of ideas, skills, or factual information as inputs in a specific sequence of steps to attain the solution to a problem or to reach a desired goal state.
• The sequence of steps is called the solution to the problem, which takes defined inputs and produces the desired output.

Types of Solution Approaches

• Algorithmic Solutions: solutions to problems in which the desired state is achieved by a defined and finite sequence of steps, such as making pizza or determining the number of rooms in a building.
• Heuristic Solutions: solutions to problems in which the goal state is reached by a series of steps that emerge from knowledge and experience or from various trials and error, such as making a speech at an event or playing and winning a soccer game.

Focus of the Course

• This course is mainly concerned with algorithmic solutions to problems, which can be solved by computers.
• Heuristics solutions are achieved using artificial intelligence techniques, such as artificial neural networks, fuzzy logic, and constraint optimization.

Some Solution Techniques

• 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.
• 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.
• Lateral thinking: approaching solutions indirectly and creatively.
• Means-ends analysis: choosing an action at each step to move closer to the goal.
• 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.
• Research: employing existing ideas or adapting existing solutions to similar problems.
• Root cause Analysis: identifying the cause of the problem.
• Proof: trying to prove that the problem cannot be solved.
• Divide and Conquer (D&C): breaking down a large, complex problem into smaller, solvable problems.

Solving Problems with Computers

• Computers are built to deal with algorithmic solutions, which are often difficult or very time-consuming for humans.
• Solving complex mathematical equations or arranging names in alphabetical order is an easy task for computers.

6 Steps of Solving Any Problem

• Identify the Problem: the first step of solving any problem is to identify the problem.
• Understand the Problem: understanding the problem entails having a good knowledge base of the problem.
• Identify Alternative Solutions to Problem: list as many alternate solutions as possible.
• Select the Best Solution: evaluate the pros and cons of each possible solution and select the best one.
• List the Instructions Involved in the Solution: provide step-by-step procedures to arrive at the desired goal state.
• Evaluate the Solution: check the result of the solution to ensure correctness and satisfaction of the need or situation.

Overview of Problems and Problem Solving Concepts

• Problems exist in every area of daily life and are obstacles to overcome, such as solving a math equation, making a decision, or accomplishing a task.
• A problem can be defined as an unpleasant situation or condition where a better or perfect state is desired.
• Reaching the goal state is achieved by following a sequence of steps, which can be either simple or complex.

Types of Problems

• Routine problems: have simple and predictable solutions, such as solving a math problem or spelling a word.
• Non-routine problems: have subjective, abstract, and complex solutions, such as arranging 10 popular languages from best to least, and are more difficult to solve.

Problem Solving

• Problem solving is the application of ideas, skills, or factual information as inputs in a specific sequence of steps to attain a solution to a problem or reach a desired goal state.
• The sequence of steps is called the solution to the problem, and the solution takes defined inputs and produces the desired output.
• One problem can have multiple solutions, but the aim of computer programmers is to find the best solution to the given problem.

Types of Solution Approaches

• Algorithmic solutions: solutions to problems in which the desired state is achieved by a defined and finite sequence of steps, such as making a pizza or getting to the CST building from the hostel.
• Heuristic solutions: solutions to problems in which the goal state is reached by a series of steps that emerge from knowledge and experience, such as making a speech at an event or playing and winning a soccer game.

Solution Techniques

• 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.
• 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 disprove the assumption.
• Reduction: transforming the problem into another problem for which solutions exist.
• Lateral thinking: approaching solutions indirectly and creatively.
• Means-ends analysis: choosing an action at each step to move closer to the goal.
• 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.
• Research: employing existing ideas or adapting existing solutions to similar problems.
• Root cause Analysis: identifying the cause of the problem.
• Proof: trying to prove that the problem cannot be solved, and the point where the proof fails will be the starting point for solving it.
• Divide and Conquer (D&C): breaking down a large, complex problem into smaller, solvable problems.

Solving Problems with Computers

• Computers are built to deal with algorithmic solutions, which are 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 computers.

6-Steps in Problem Solving

• Identify the problem: define the problem and its constraints.
• Understand the problem: consider the knowledge base and layout of the campus.
• Identify alternative solutions: list possible solutions to the problem.
• Select the best alternative: evaluate the pros and cons of each alternative and make a final decision.
• List instructions involved in the solution: specify the step-by-step procedures to arrive at the desired goal state.
• Evaluate the solution: check the result of the solution to ensure correctness and satisfaction.