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Study Guide on Problem-Solving - defined terms, comparison with memory, history, and false assumptions

6 Pages
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Department
Cognitive Science
Course Code
COG250Y1
Professor
John Vervaeke

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PROBLEM SOLVING
VS. MEMORY:
we make things meaningful in many different ways, so there are many
dimensions that must be considered during remembering. Relevance
realization is required to explain memory in order to explain categorization.
Cognition requires intelligence, though.. maybe problem-solving is more basic
than both memory and categorization!
Content addressability: having to organize memory in order to facilitate
zeroing in on the RELEVANT information. Giving search-specific
parameters based on content.
GPS: general problem solver, heart of cog. Revolution, attempted by Newell &
Simon 1957
Well-Defined vs. Ill-Defined: Ill-defined problems are difficult to
FORMULATE, while well-defined problems are easy to understand but it
may be difficult to take the necessary steps to solve the problem.
Initial State: in which there is an unsolved problem, a desired goal whose
method of attainment is not yet apparent
Operators: Actions one may do to alter the initial state in the hopes of
approaching the goal state
Path Constraints: must be obeyed DURING problem-solving attempts,
whether or not they are related to or essential for achieving the goal state.
Goal State: The state in which the problem is solved
Algorithm: A completely reliable routine or procedure that can be carried
out in a finite # of steps
Heuristics: Rules of thumb that tend to improve probability of success
without actually guaranteeing a solution
Rationality: in this case, a large part = knowing when & when not to be
LOGICAL
Means-ends Analysis: compare current state to goal state, identify salient
differences between the two, select operators that will reduce them, etc etc etc
Computatorial Explosion:
Problem Formulation: picking out FEATURES, BACKGROUNDING
things, APPERCEIVING the dynamic whole, RELATING the whole to ones
interests, finding A PROBLEM/question with the situation.
Sizing Up:
Noein: noticing the significance of?
Apperception:
www.notesolution.com
Dynamical System: a self-organizing structure that has feedback elements
in it.
Importance: relevant to oneself
Co-relevance: how pieces of info are relevant to each other
Salience: how organisms direct their attention to relevant info that will
facilitate & moderate its environment.
Mental Set Formation: making a sense of a situations bidirectional
relationship with problem formulation?
Fixation:
Insight:
Functional Fixedness:
Expertise: almost COMPLETELY a function of mental set formation
Experts Fallacy: this mental set formation makes experts more susceptible
to fixations, which may be negative in many situations
Propositional Insight: involving a claim with truth-value
Procedural Insight: The possession of a skill more than the grasping of a
fact
Program: Inferential manipulation of propositions
Concurrent Verbalization: having people put into words whatever they’re
doing (in Schooler et. Al.s case, during problem-solving)
Primitive Learning: Conditioning?
Internal Opponent Processing: *
Partial information:
Causal Intensity:
Internal homeostasis??
HISTORY:
Potters 3-Stage Process:
large amount of info (most irrelevant)
selection process choose relevant information
oseems to share a lot in common with problem solving
It is passed to consciousness
overy vague
noting that to offer an explanation is to answer a question is to solve a
problem, we understand why people subsequently propose that the
FUNDAMENTAL FEATURE OF COGNITION may be problem-solving.
www.notesolution.com

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Description
PROBLEM SOLVING VS. MEMORY: we make things meaningful in many different ways, so there are many dimensions that must be considered during remembering. Relevance realization is required to explain memory in order to explain categorization. Cognition requires intelligence, though.. maybe problem-solving is more basic than both memory and categorization! Content addressability: having to organize memory in order to facilitate zeroing in on the RELEVANT information. Giving search-specific parameters based on content. GPS: general problem solver, heart of cog. Revolution, attempted by Newell & Simon 1957 Well-Defined vs. Ill-Defined: Ill-defined problems are difficult to FORMULATE, while well-defined problems are easy to understand but it may be difficult to take the necessary steps to solve the problem. Initial State: in which there is an unsolved problem, a desired goal whose method of attainment is not yet apparent Operators: Actions one may do to alter the initial state in the hopes of approaching the goal state Path Constraints: must be obeyed DURING problem-solving attempts, whether or not they are related to or essential for achieving the goal state. Goal State: The state in which the problem is solved Algorithm: A completely reliable routine or procedure that can be carried out in a finite # of steps Heuristics: Rules of thumb that tend to improve probability of success without actually guaranteeing a solution Rationality: in this case, a large part = knowing when & when not to be LOGICAL Means-ends Analysis: compare current state to goal state, identify salient differences between the two, select operators that will reduce them, etc etc etc Computatorial Explosion: Problem Formulation: picking out FEATURES, BACKGROUNDING things, APPERCEIVING the dynamic whole, RELATING the whole to ones interests, finding A PROBLEMquestion with the situation. Sizing Up: Noein: noticing the significance of? Apperception: www.notesolution.com
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