Unformatted text preview:

Slide 1Slide 2Slide 3Slide 4Slide 5Slide 6Slide 7Slide 8Slide 9Slide 10Slide 11Slide 12Slide 13Slide 14Slide 15Slide 16Slide 17Slide 18Slide 19Slide 20Slide 21Slide 22Slide 23Slide 24Slide 25Slide 26Slide 27Slide 28Slide 29Slide 30Slide 31Slide 32Slide 33Slide 34Slide 35Slide 36Slide 37Slide 38Slide 39Slide 40Conditioning & Learning Exam 2Rescorla & Wagner (1972)•V = associative strength•Alpha = CS salience•Beta = US salience•Lambda = perfect learning, or asymptote•Vtot = sum of associative strength•Practice effects, salience (intensity), and asymptote (we don’t learn something forever) should be addressed in ANY modelRescorla & Wagner model assumes that learning increases until you understand what you’re trying to learn •Discrepancy Resolution Model•Initially, there’s a big discrepancy between what you know and what you need to know; as you learn more, there is less of a discrepancy•When you’re surprised from the outcome of a conditioning trial, you learn. When you’re not surprised, you don’t learn•Positive increment in associative strength when you get more than you expect; negative increment in associative strenth when you get less than you expect•Strong association (ex: Tone - Shock) means you figured it out•Learning is a limited resource project•Stimuli compete for attention -> the stimulus that wins is the stimulus that you learn aboutExperiment: Acquisition of associative strength•16 trials•Trials 1-8 = tone + shock (acquisition of associative strength)•Acquisition curve•Animal wants to know everything he can•Begins at 0 -> large discrepancy•Learns a lot on 1st trial because he was very surprised by the outcome of the event in the 1st trial•Lower increase in CR is less in sequential trials because there is less to know, less discrepancy to resolve, and he is less surprised•W/ each trial, the discrepancy of what he knows and would like to know becomes less and less•Trials 9-16 = tone alone (extinction)•Extinction curve•Beginning (trial 9) exhibits fear because of what he has learned•Decrease in CR during 10th trial because he is surprised not to get shocked•Continues until animal learns the shock won’t come•What would Rescorla & Wagner say about this?•Calculating the change in associative strength (-1 to +1): Associative strength of 0 means the animal knows nothing, associative strength of +1 means the animal has perfect excitation, and associative strength of -1 means the animal has perfect inhibition•If the salience of a stimulus is 0, it cannot be detected; perfect stimulus has salience = 1•If the stimulus is perfect, then the animal will learn it all on trial 1Equation for example •Assume alpha=0.5 and beta=1.0•Trial 1: △V=(0.5)(1.0)(1-0)=0.5•Trial 2: △V= (0.5)(1.0)(1-0.5)=0.25•Trial 3: △V= (0.5)(1.0)(1-0.75)=0.125•Trial 4: △V= (0.5)(1.0)(1-0.875)=0.063•Trial 9: △V= (0.5)(1.0)(0-1)= -0.5•Trial 10: △V= (0.5)(1.0)(0-0.5)= -0.25•Trial 11: △V= (0.5)(1.0)(0-0.25)= -0.125•In reality, extinction is much slower than depicted because the animal is reluctant to give up the association learned in acquisitionReaquisition Experiments•Animals maintain old memories so they can use them when important (sometimes tone means shock, sometimes no -> choose which memory in time of need -> important psychologically•Animal has one memory after acquisition, and gains another after extinction - animal has 2 memories at time of reaquisition•Rescorla & Wagner Model (/72) - stimuli that go together have higher salience•ex: grape flavor + poison (α=1, β=1)•△V= (1)(1)(1-0)=1; complete learning on 1st trialBlocking (always get sick from rice - expect to get sick from rice regardless if it’s from anything else that you eat•Blocking No Blocking 1. L+S (0.5) _______ (0) 2. L+S (0.75) _______ (0) 3. L+S (0.875) _______ (0) 4. L+S (0.94) _______ (0) 5. LT+S LT+S •Animal shouldn’t learn much about the tone if the light predicts the shock•Learned about 0.03 about the toneOvershadowing (never had rice or fish and get sick -> blame it on the fish b/c fish is more salient)•If you have fish & sausage (equally salient), there’s uncertainty in which caused the illness•No Overshadowing Overshadowing 1. L+ (0.5) LT+ 1. L+ (0.75) LT+ 1. L+ (0.875) LT+ •L -> 0.5 in each trial after & T -> 0.5 in each trial after = overshadowing effect•Light competes for associative strength w/ tone•F = fish, S = sausage•FS - sick•FS - sick - don’t know which causes sickess (50/50 chance of either one)•FS - sick•F - sick - say fish makes you sick, not the sausageConditioned Inhibition (I’m in a bad neighborhood at night and am scared until a police officer walks behind me and inhibits my fear•1. L+•2. L+•3. L+•4. L+•5. LT-•6. L+•7. L+•8. L+•9. LT-•10. L+•11. L+•12. L+•13. LT-- The tone is acquiring negative associative strength b/c it predicts less than the animal expected- Light becomes a very good exciter and tone becomes a very good inhibitor- Tone has a very negative associative strength- Why does it take so long for a conditioned inhibitor to become an exciter? (ex: hard to accept if police started to rob people)- Rescorla & Wagner Model does not predict facilitated reacqisitionLatent inhibition (If I eat oysters 1000x w/o getting sick and then one day I get sick, I won’t blame the oysters•Latent Inhibition No Latent Inhibition 1. L- 1. ______ 2. L- 2. ______ 3. L- 3. ______ 100. L- 100. ______ 101. L+ = no fear 101. L+ = CR•Rescorla & Wagner Model says latent inhibition should not occur•Side note: Any good theory can’t only explain available data, but must also make novel predictionsThe Rescorla & Wagner Model predicted many things that

View Full Document

Rutgers PSYCHOLOGY 311 - Conditioning & Learning

Download Conditioning & Learning
Our administrator received your request to download this document. We will send you the file to your email shortly.
Loading Unlocking...

Join to view Conditioning & Learning and access 3M+ class-specific study document.

We will never post anything without your permission.
Don't have an account?
Sign Up

Join to view Conditioning & Learning 2 2 and access 3M+ class-specific study document.


By creating an account you agree to our Privacy Policy and Terms Of Use

Already a member?