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10/11/10 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 10/11/10 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: + • Food (UCS) is paired with the Bell (NS) and causes Drooling (UCR) After conditioning: • Bell (CS) causes Drooling (CR) 2 10/11/10 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 10/11/10 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 10/11/10 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 10/11/10 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