Download Chapter 4 notes

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Learning
Chapter 4
Homework for next -me: •  Journal Task #37 •  Experimental Deadline 2: October 13th! –  Alterna-ves must be submiFed by 5pm •  Traphagen 330 Pavlovian Drooling Pups! 1
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Classical Condi-oning: Terms •  Uncondi-oned S-mulus (UCS): naturally occuring s-mulus that leads to a reflexive response. FOOD •  Uncondi-oned Response (UCR): the reflexive response to the uncondi-oned s-mulus. SALIVATING •  Neutral S-mulus (NS): s-mulus that previously has no effect on the desired response. BELL Classical Condi-oning: Terms •  Condi-oned S-mulus (CS): previously neutral s-mulus that elicits a reflexive response aVer repeatedly being paired with UCS. BELL •  Condi-oned Response (CR): learned reflexive response to a CS. SALIVATING The setup….. Before conditioning:
•  Food (UCS) causes Drooling (UCR) During conditioning:
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•  Food (UCS) is paired with the Bell (NS) and causes Drooling (UCR) After conditioning:
•  Bell (CS) causes Drooling (CR) 2
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The Pavlovs get new neighbors….. Terminology •  Acquisi4on: the formula-on of the s-mulus-­‐response associa-on •  Ex4nc4on: A decrease of a learned response due to repeatedly presen-ng the CS without the UCS •  Spontaneous Recovery: The reappearance of an ex-nguished response (CS presented alone) My car
•  Example: (a.k.a. “The Beast”)
Car accident The other
guy’s car….
Operant Condi-oning: What’s in it for me? •  Defini-on: the learning of voluntary behavior through rewards and punishments 3
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4 Very Important Terms •  Reinforcement: any event or s-mulus, that when following a response, increases the probability that the response will occur again. •  Punishment: any event or object that, when following a response, makes that response less likely to happen again. •  Posi4ve: Adding anything to the environment. •  Nega4ve: Taking away anything from the environment. –  Posi-ve does not mean good; nega-ve does not mean bad! Reinforcement •  Posi4ve Reinforcement: reinforcement of a response by the addi-on of something that increases the likelihood that the response will be repeated –  Example: Going to the gym = buying books, clothes or shoes!! •  Nega4ve Reinforcement: the reinforcement of a response by the removal or avoidance of something that increases the likelihood that the response will be repeated –  Example: Turn in homework on -me = no penalty Reinforcement (cont) •  Primary reinforcer: sa-sfies a basic need –  Example: food, water, shelter •  Secondary reinforcer: has no intrinsic value but becomes reinforcing when paired with a primary reinforcer –  Example: money 4
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Punishment •  Posi4ve Punishment: the punishment of a response by the addi-on of something that will decrease the likelihood that the response will be repeated –  Example: Wash the dishes everyday for a month aVer you skipped school •  Nega4ve Punishment: the punishment of a response by the removal of something that will decrease the likelihood that the response will be repeated –  Example: Grounded (removing privileges) when you break curfew A helpful tool Effect on Behavior
Added to
environment
Removed
from the
environment
Increases
Decreases
Positive
Reinforcement
Positive Punishment
Negative
Reinforcement
Negative Punishment
Shaping •  Defini4on: the reinforcement of simple steps in behavior that lead to a desired, more complex behavior 5
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Schedules of Reinforcement: •  Con4nuous Reinforcement: the reinforcement of every response –  Example: Macy’s – Open credit/receive $5 •  Par4al Reinforcement: reinforcing some, but not all, responses –  Example: Barnes & Noble – Every three member cards sold/free café drink Schedule of Reinforcements •  Fixed Interval: the interval of 2me that must pass before reinforcement becomes possible is always the same –  Example: Hourly wage •  Variable Interval: the interval of 2me that must pass before reinforcement becomes possible is different for every trial or event –  Example: Pop quiz •  Fixed Ra4o: the number of responses required for reinforcement is always the same –  Example: Taco Del Mar punch card •  Variable Ra4o: the number of responses required for reinforcement is different for each trial or event –  Example: Slot machines (Vegas thrives because of variable ra-o!!) LiFle Experiment, Big Consequences: Bobo!! •  Observa-onal Learning: Learning of new behavior through observa-on of a model 6