Unit 7: Base-Level Activation February 25, 2003

February 26, 2002Unit 72 Activation Revisited  Both latency and probability of recall depend on activation  Activation Equation Spreading activationPartial matchingNoise Base-level activation (sgp :bll t)

February 26, 2002Unit 73 Base-Level Activation  Base-level activation depends on the history of usage of a chunk  Memory strength depends on –How recently you used it in the past –How much you practiced it

February 26, 2002Unit 74 Base-Level Learning Time 0 now Pres 1Pres 2Pres kPres n

February 26, 2002Unit 75 Base-Level Learning time since the k-th presentation of the chunk i Time 0 now Pres 1Pres 2Pres kPres n decay parameter (sgp :bll 0.5) Mathematically transforming the ages to conform to the functions optimal in the environment

February 26, 2002Unit 76 Power Law of Forgetting  Strength of memories decreases with time E.g. - Speed to recognize a sentence at various delays –Number of paired associates that subjects recall –People’s ability to recognize the name of a TV show for varying numbers of years after it’s been canceled  More and more delay produces smaller and smaller losses  This is the idea that individual events are forgotten according to a power function

February 26, 2002Unit 77  p=probability –p is a decreasing function of retention time –p/(1-p) is a power function of retention time with exponent d –ln(p/(1-p)) is a linear function of ln(retentiontime) -d –Accounts for the fact that each event age (t k ) decays at rate d

February 26, 2002Unit 78 Power Law of Learning Memory improves with practice; recall often gets close to perfection, but speed increases with practice even after that: This is the idea that the accumulating sum of events is also a power function. Proof omitted shows that this holds true for evenly spaced presentations

February 26, 2002Unit 79  p= need probability n=number of occurrences –p is a linear function of n –p/(1-p) is approximately a power function of n –ln(p/(1-p)) is a linear function of ln (n) –Accounts for the sum of all event ages (t k s) contributing

February 26, 2002Unit 710 How many t k s are there at time 40, 10, and 100. What are they?

February 26, 2002Unit 711 What Is a Event Presentation?  Creating a new chunk (p my-production =goal> isa associate term1 vanilla term2 3  +goal> isa associate)  Re-creating an old chunk  Retrieving and harvesting a chunk

February 26, 2002Unit 712 Optimized Learning  At each moment when chunk i could be potentially retrieved, ACT-R needs to compute new  n computations; for each chunk ACT-R needs to store the presentations  Optimized learning is a fast approximation  1 operation per potential retrieval  (sgp :ol t)

February 26, 2002Unit 713 Optimized Learning Equation Time 0 now Pres 1Pres 2Pres kPres n Optimized learning works when the n presentations are spaced approximately evenly

February 26, 2002Unit 714

February 26, 2002Unit 715 Paired-Associates Example Study and recall pairs word-digit: vanilla 3 Each digit was used as a response twice. 20 paired associates; 8 trials

February 26, 2002Unit 716 Paired Associates: Results Accuracy: items get under retrieval threshold if not rehearsed soon Latency: power law of learning

February 26, 2002Unit 717 Homework: Zbrodoff’s Experiment True or false?A + 3 = D (true) Possible addends: 2, 3 or 4 Frequency manipulation: Control -- each problem x 2 Standard – 2-add x 3, 3-add x 2, 4-add x 1 Reverse -- 2-add X 1, 3-add X 2, 4-add x 3 3 Blocks G + 2 = H (false)

February 26, 2002Unit 718 Zbrodoff’s Data Control Two Three Four Block Block Block Standard Group (smaller problems more frequent) Two Three Four Block Block Block Reverse Group (larger problems more frequent) Two Three Four Block Block Block

February 26, 2002Unit 719 Tips  Compute the addition result when it’s not available for retrieval  May add extra effort to the productions that make the computation (articulation) (spp myproduction :effort.1)  (setallbaselevels )  (spp :ga 0 :pm nil)  Change retrieval threshold, latency factor, noise

February 26, 2002Unit 720 Activation, Latency, and Recall Activation Probability of Retrieval Base Level Retrieval Latency Back