Problem Solving Flashcards
Problem Solving
Going from a problem to goal state
-A multi-step process that involves 3 stages
Multi-Step Cognitive Process
- Recognizing and representing problem
- Analyzing and solving it
- Assessing the solution’s effectiveness
The Monk Problem
What do problems tell us about the nature of problem solving?
The Problem-Solving Cycle
- Define problem
- Analyze problem
- Identify solutions (strategies)
- Choose solution (best solution)
- Plan of action
- Implement and evaluate (Was it the best strategy to use?)
- You lost your keys while out walking the dog
- Notice where your keys are not; realize you are locked out
- Solutions?
- Retrace your steps
- Carry out solution
- Was the chosen solution effective?
Example of problem-solving cycle
Recursive
Repeat this cycle as many times as necessary to find a solution
-Ensures resolution
Applicable and Adaptable
The output of the cycle should be a solution to a current problem and a version that can generalize to new scenarios
-Generalization important = learn
Generalization of Solution in Memory
-Important for adaptive behaviour
-Storing specific solutions without detail to apply to new scenarios
-Memory for solutions should include ‘essence’ and not specifics
Well Defined Problems
-Requirements are unambiguous
-All information needed to solve the problem is present
-Applying algorithms
-Puzzles
Ill Defined Problems
-How to overcome problem/the goal is ambiguous
-Requires added information
-Situational
-E.g. relaxation.. beach or hike?
Well-Defined Problems
-Games like chess, sudoku
-Goal directedness
-Defined goal state
-Task constraints (clear steps)
-Single, expected outcome
Ill-Defined Problems
-Ambiguous situations
-Have few limitations (rules) for how to solve the problem
-Multiple solutions or expected outcomes
-Social or self problem solving (rely on different neuro-cognitive processes)
Episodic Memory
Important for providing solutions (# of steps) for problems
Ill-Defined Problems Carry a Load
-Greater actvity in the right lateral prefrontal cortex
-Solving these problems carries a greater ‘cognitive load’
-Do not have schematic solutions to reduce working memory capacity
Cognitive Load
The amount of information that your working memory system can hold at one time
It is because these problems reduce working memory capacity
Why do ill-defined problems carry a high cognitive load?
Moravec’s Paradox
Artificial intelligence (AI) can solve well-defined problems well, but not ill-defined problems and simple skills
-AI algorithms work well with certainty but not with uncertainty
A Problem Space (Well-defined problems)
- Initial and goals state (e.g. drive to mtl)
- Intermediate paths and operations (e.g. stops at Tims because hungry; subgoal; helps move to goal state)
- Task Constraints (e.g. stay on highway)
The Tower of Hanoi Problem Space
- Start/finish (initial + goal states)
- Lines, possible moves you can make (operations)
- Can’t put a bigger piece on top of a small one (constraints)
well-defined problem; task constraints
The Tower of Harnoi Problem is an example of a _______ because it has ______
Brute Force
-Systematic algorithm that represents all the possible steps from the problem to goal state
-Guaranteed to find a solution, but inefficient
Combinatorial Explosion
Computing too many alternatives
-System kind of shuts down
-Linked to decision fatigue
Heuristics
Stategies to select moves in a problem space to avoid combinatorial explosion and decision fatigue
-Trial and error
-Hill climbing strategy
-Means and analysis
Concurrent Verbalizations
Describe what you are doing as you do it (how you are solving a problem)
Retrospective Verbalizations
Describe what you did at an earlier time
-Influenced by metacognitive processes
-What you did before
Trail and Error
-Considered ‘‘lower-level thinking’’
-Try out a number of solutions, rule out what doesn’t work
-Good for limited outcome problems (What colour of my shirt matches these pants?)
-Not good for multi-outcome problems (solving rubik cube)
Hill Climbing Strategy
-Select the operation that brings you closer to the goal without examining the whole problem space
-This strategy can lead to a false outcome, a ‘local maxima’ (subgoal) is mistaken as the final goal
-Does not always work because some problems require you to move away from the goal in order to solve it
The Hobbits and Orcs Problem
-Solution requires moving hobbits and orcs back and forth
-Requires moving away from goal first
Means-Ends Strategy
-More flexible approach than hill-climbing
-What ‘‘means’’ do I have to make the current state look like the goal state?
-Identifying sub-problems to complete the goal
-Includes forward and backward movements
-Constantly evaluating the difference between current and goal states
-Taking into account all possible strategies
Hill Climbing Strategy
A dog is face to a fence, it decides to plow through the fence. This is an example of…
Means End Strategy
A dog s face to a fence, it decides to think about other potential moves to get to the other side, like finding a hole. This is an example of…
Means End Strategy
-Envisioning end or ultimate goal
-Determining the best strategy for attaining the goal given current situation
-Highlights the importance of recursion
-Sub-goals and step by step approach to getting to solution
They have more knowledge than novices
What makes expert problem solvers better than novices?
True
Experts use better rules or strategies when solving problems. True or False.
Experts spend more time defining a problem
Non-experts spent more time trying to develop a solution; Experts to define the problem appropriately
Expertise and Viewing a Problem Solving
-Experts are more familiar with certain information and so they represent a problem differently than non-experts
-Expert radiologists use ‘global’ visual processes when viewing scans (do not focus on unnecessary details)
Experts engage different brain processes to view a problem
-Expert radiologists recruit broader visual areas when viewing chest x-rays
-Experts recruit more brain areas that process information related to their expertise
-Experts are better able to use domain-relevant knowledge to perform a task
Experts engage in holistic brain processing to solve a problem
Novices activate left hemisphere of brain while experts activate right side
Limited Transfer Between Domains
Just because Snoop Dogg is an expert lyricist (rapper) does not mean he is an expert baker
