9/5 Problem Solving (Discussion)

Algorithms

Repetitive means of checking every possibility or hypothesis to find an accurate answer

• Mechanical, procedural, accurate, time-consuming

Heuristics

strategies for simplifying problems and for generating satisfactory

Maximizing (heuristic)

put enormous effort into making the best choice, In search of the best choice possible, questioning for the best can be unfulfilling

Satisficing (heuristic)

In search of the first satisfactory choice, May regret choice if presented with more information

Representative Heuristic

assumption that an item that resembles members of some category is probably also in that category (Ex. E.g., Steve is very hy and withdrawn -> do you think he is a librarian or farmer?)

Base-rate information

how common each category is

Base rate fallacy

Tendency to overlook base rates when making judgements and focusing on specific information

Two types of information that may be available:

1. Base rate information – generic information about how common the event or category is

2. Specific information about a case in question

Availability Heuristic

Assumption that if we can easily think of examples of a category, then that category must be common

Confirmation bias

tendency to accept a hypothesis and then look for evidence to support it instead of considering other possibilities or disconfirming information

Functional fixedness

tendency to adhere to a single approach or single way of using an item

Why do we use heuristics if it makes errors?

They are adaptive most of the time

Expertise

Years of experience lead to changes in the brain (e.g., London cab drivers have larger hippocampus)

Limits of transfer

expertise in one area does not make you an expert in all

How to be a problem solver

Find a balance between algorithm/heirsotcs, maximizing and satisficing

Hin outside the frame (outside of the boc_ and wegh all the information)

Give yourself tiem and exercise patience

Become as expert (not a know it all)