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Study NoteCOS102

Problem-Solving Strategies: Heuristics, Means-Ends Analysis & More

The Core Strategies

Every problem-solving question in this course boils down to naming which strategy is being described. Learn these five cold:

  • Algorithm — a precise, ordered sequence of steps guaranteed to reach a result (e.g. an installation manual).
  • Heuristic — a loosely-defined "rule of thumb" that guides you without guaranteeing a correct or optimal result (e.g. "working backwards", the affect heuristic).
  • Means-Ends Analysis (MEA) — reduce the difference between where you are (current state) and where you want to be (goal state) by working through subgoals. The classic textbook example is the Tower of Hanoi.
  • Trial and Error — systematically testing options to see what works (e.g. turning off WiFi, then Bluetooth, to find why your phone is misbehaving).
  • Pseudocode — not a problem-solving strategy at all; it's a notation for writing down an algorithm.
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The Steps of Means-Ends Analysis

  1. Define the initial state (the problem).
  2. Visualize the goal state.
  3. Identify the difference between the two.
  4. Take action based on that analysis.

There's no step called "aggregate the problem into larger loops" — that's the opposite of how MEA works; it always breaks things down, never up.

The Affect Heuristic

A specific named heuristic worth knowing: the affect heuristic is decision-making driven by your current emotions, not logic or experience.

Why This Matters for Your Exams

These questions are almost always "which strategy is this scenario an example of?" Build a mental checklist: does it guarantee a correct answer (algorithm)? Is it a rough guiding rule (heuristic)? Does it work backward from a goal through subgoals (MEA)? Or is it just testing things one by one (trial and error)?

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