• Algorithms are specific procedures that guarantee a correct solution if followed properly, but may be time-consuming.
• Heuristics are general "rules of thumb" that are useful but do not guarantee a correct solution.

• Specific techniques include:
  • Generate and test: Testing possible solutions until the right one is found.
  • Means-ends analysis: Dividing the problem into sub-problems, detecting differences between states and applying operators to reduce the differences to reach a goal.
  • Backward search: Starting from the goal state and working backwards to the initial state.
  • Planning strategy: Creating a plan of action to solve the problem.
  • Thinking aloud: Verbalising thoughts during problem-solving, also called concurrent verbalisation.
  • Root cause analysis: Eliminating the cause of the problem.
  • Trial and error: Testing possible solutions until one works.
  • Brainstorming: Generating a large number of ideas in a group, then developing these ideas further.

5. What are some of the specific techniques of problem-solving?

Specific techniques include: generate and test, means-ends analysis, backward search, planning strategy and thinking aloud. Other techniques also exist such as root cause analysis, trial and error and brainstorming.

6. What is backward search in problem-solving?

Backward search is a heuristic where the problem solver starts from the goal state and works backwards to the initial state. This is useful for problems where the goal state is uniquely specified.

7. Discuss "thinking aloud" as a method for studying human problem-solving.

Thinking aloud or concurrent verbalisation is a method where subjects verbalise their thoughts while solving a problem, providing a description of their solution process. This method relies on short-term memory, whereas retrospective verbalisation relies on long-term memory. The verbal description is called a protocol. While widely used, it may interfere with the problem-solving process.

8. How are creativity and problem solving related?

Creativity is believed to play a vital role in insight problem solving. Many problems called insight problems are believed to have solutions arising from insight. Insight is an important part of the creative process. The link between creativity and insight-based problem solving is that both suddenly come to mind after a period of not knowing what to do.

9. How does artificial intelligence function in problem-solving?

Artificial intelligence uses computer programmes to mimic human problem-solving skills in specific fields. It can use algorithms and heuristics to solve problems, but has difficulty with intuition, and lacks "common sense".

10. What are the stages in problem-solving? Highlight the stages with a problem from your day to day life.

• Understanding the problem: Identifying the goal, the obstacles, and the nature of the problem.
• Generating solutions: Brainstorming potential solutions.
• Judging solutions: Evaluating potential solutions, which includes moving closer to the goal and identifying obstacles.
• Carrying out a solution: Implementing the best solution.
• Evaluating the solution: Checking the solution for effectiveness.

• Example: A daily problem could be a broken washing machine.
  • Understanding the problem: The washing machine isn't working; the goal is to have clean clothes; the obstacle is the malfunctioning machine.
  • Generating solutions: Try to fix it yourself, call a repairman, or use a laundromat.
  • Judging solutions: Each solution has pros and cons: DIY is cheapest but risky, a repairman is reliable but costly, and the laundromat is convenient but requires effort.
  • Carrying out a solution: Calling a repairman.
  • Evaluating the solution: Was the machine fixed properly and at a reasonable cost?

11. Compare and contrast the generate-test, the means-ends, and the backward search method of problem-solving.

• Generate-test: Involves generating possible solutions and testing them until one works; useful when there aren't too many possibilities.
• Means-ends analysis: Involves dividing the problem into sub-problems and trying to reduce the difference between the current state and the goal state; a very common and useful strategy.
• Backward search: Starts with the goal and works back to the initial state; useful for problems with a uniquely specified goal state.
• Generate and test is useful when possibilities are few and easily tested; means ends analysis is useful when the goals can be subdivided into more manageable steps; and backward search works best when there's a clear goal to begin with.

12. Discuss "thinking aloud" as a method of studying human problem-solving.

Thinking aloud, or concurrent verbalisation, involves subjects verbalising their thought processes while solving a problem. This provides a protocol of their solution process. It relies on short-term memory, and it can provide insight into the steps taken during problem-solving. Although widely used, it can interfere with some aspects of problem-solving.

13. Discuss "other strategies" in problem-solving. For example, abstraction, divide and conquer etc.

• Other strategies:
  • Root cause analysis: Focuses on eliminating the source of a problem.
  • Trial and error: Tests various solutions until one works.
  • Brainstorming: A group activity for generating many solutions to a problem.
• Also planning strategy, which involves devising a plan of action to solve a problem.

14. Critically evaluate the utility of artificial intelligence in problem-solving?

Artificial intelligence can mimic human expertise and use algorithms and heuristics to solve problems. However, it lacks intuition and common sense. Also, it cannot capture human creativity, emotional awareness, and adaptability. While promising, it is not as versatile as human problem-solving, with questions surrounding its utility remaining.

15. Compare and contrast the general stages of problem-solving with the stages of creative problem-solving.

• The general stages include understanding, generating, judging, carrying out, and evaluating solutions.
• Creative problem-solving is thought to have similar stages, however, according to Wallas they are: preparation, incubation, illumination or insight, and verification.
• The stages of creative problem-solving often include an incubation period where the problem is worked on unconsciously which is not a feature of the general stages of problem-solving. Creative problem solving is more focused on insight and generating new solutions, whereas general problem-solving can use more routine or algorithmic methods.

16. Discuss the concept of thinking aloud approach of problem solving.

The thinking aloud approach, also known as concurrent verbalisation, involves individuals verbalising their thoughts while they are actively engaged in problem solving. The verbalisations provide a protocol of the problem solving process. This is a widely used technique in cognitive psychology. However there is some evidence to suggest that it may interfere with the problem solving process.

17. Discuss the nature of the problem.

The nature of a problem refers to its inherent characteristics, including its complexity, clarity, and the type of thinking it requires. Problems can range from well-defined to ill-defined.

• Well-defined problems have a clear initial state, a defined goal state, specific operators (actions) and clear rules for transforming the initial state into the goal state. Examples include mathematical equations or jigsaw puzzles.
• Ill-defined problems lack one or more of these clear elements. For example, the problem of "how to bring peace" is ill-defined because the initial state, the goal state, and the methods to achieve it are unclear and may vary widely.
• The nature of a problem also includes its magnitude and difficulty level. A problem's difficulty increases with the number of elements involved, and the difference between the initial and goal states.
• Understanding a problem involves identifying its key components, such as goals, obstacles, and relevant information. It also involves ignoring irrelevant details and representing the problem using symbols, lists, or visual images.

18. What is an algorithm?

An algorithm is a step-by-step procedure that guarantees a correct solution to a problem if followed precisely.

• Algorithms are characterised by four essential properties:
  • Each step must be exact and unambiguous.
  • The process must terminate after a finite number of steps.
  • It must provide the correct answer to the problem.
  • It must be general and solve every instance of the problem.
• An example of an algorithm is a mathematical formula, like the rules of multiplication. In the case of an anagram, an algorithm would be to try all possible letter sequences until a meaningful word is found.
• While algorithms ensure a correct solution, they can be time-consuming, especially for complex problems.

19. What are heuristics?

Heuristics are general suggestions or "rules of thumb" that are useful in solving a variety of problems, but do not guarantee a correct solution.

• Heuristics are mental shortcuts that simplify problem-solving, but they can sometimes lead to errors.
• Unlike algorithms, heuristics do not systematically explore all possibilities but rather rely on strategies and past experiences to reach a solution.
• Examples of heuristics include means-end analysis, working backward, and using analogies.

20. What is involved in the "generate and test" technique?

The "generate and test" technique is a problem-solving strategy that involves creating a list of possible solutions and then testing each one to see if it meets the necessary criteria.

• This technique is useful when there are a limited number of possibilities to consider.
• For example, in searching for lost keys, you might generate a list of locations where you might have left them and then check each location.
• When using this technique, some possible answers may come to mind that seem correct but are not.

21. What do you understand by the term "Means-Ends Analysis?"

Means-ends analysis is a problem-solving heuristic where the problem is broken down into sub-problems to reduce the difference between the current state and the goal state.

• This method involves identifying the "ends" you want to achieve and figuring out the "means" you will use to reach those ends.
• The approach consists of several steps: setting up a goal, looking for differences between the current state and the goal state, finding a method to reduce the difference, setting a sub-goal to apply that method.
• It involves creating sub-goals to eliminate the differences between the current state and the conditions for applying the desired operator.
• Means-ends analysis is a common strategy that people use daily, and can be expressed precisely as a production system with if-then pairs.

22. What are the 3 problem-solving skills that insight involves? Give examples.

Insight involves three key problem-solving skills:

• Selective Encoding: This involves identifying the information that is relevant to a problem while ignoring the information that is irrelevant. For instance, when solving the "nine-dot problem" you need to throw off the assumption that lines have to lie within the visual boundaries.
• Selective Combination: This involves putting the elements of a problem together in a new way. Darwin's theory of evolution is an example, in which he combined existing facts in a new and coherent way.
• Selective Comparison: This involves relating new information to past knowledge. For example, in the process of creative problem solving people may make new combinations of information they know to achieve an insight.

23. What are the various stages in creative discoveries?

Creative discoveries often involve the following stages:

• Preparation: This is the stage where relevant parts of the problem are identified, and the problem solver gathers relevant information.
• Incubation: This involves a period of unconscious processing of the problem. The solver may not be actively working on the problem during this phase.
• Illumination or Insight: This is the moment when the solution suddenly comes to mind. The previously unrelated elements of the problem come together in a novel way.
• Verification: The final step which involves testing whether the new solution is useful and effective.

24. What is meant by the computer simulation approach in problem-solving?

The computer simulation approach involves programming a computer to perform tasks in a manner similar to how humans do.

• Researchers compare the computer's performance with that of humans on the same tasks.
• Computer simulation helps in developing information processing theories of problem-solving.
• Computer programs can model problem-solving strategies, such as the General Problem Solver (GPS) which was developed by Newell, Shaw, and Simon.
• Artificial intelligence is the branch of science that studies the capacity of computers to demonstrate intelligent behaviour.

25. What are the criticisms against computer simulation? Discuss.

There are several criticisms against the computer simulation approach:

• Complexity of human thought: Some argue that human thinking is too complex to be mimicked by a machine.
• Lack of true thinking: Others argue that even if computers can solve problems, it does not equate to genuine thinking.
• The essence of thinking: It is argued that computer programs only stimulate processes like reasoning and calculating but don't capture the deeper essence of thinking.
• Some critics, like the philosopher Heidegger, believe that the properties of computer programs that represent a chain of inferences are not the essence of thinking.