1. Unit 7: Base-Level Activation February 25, 2003

2. 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)

3. 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

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

5. 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

6. 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

7. 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

8. 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

9. 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

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

11. 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

12. 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)

13. 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

14. February 26, 2002Unit 714

15. 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

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

17. 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)

18. February 26, 2002Unit 718 Zbrodoff’s Data Control Two Three Four Block 1 1.840 2.460 2.820 Block 2 1.210 1.450 1.420 Block 3 1.140 1.420 1.170 Standard Group (smaller problems more frequent) Two Three Four Block 1 1.840 2.650 3.550 Block 2 1.080 1.450 1.920 Block 3 0.910 1.080 1.430 Reverse Group (larger problems more frequent) Two Three Four Block 1 2.250 2.530 2.420 Block 2 1.470 1.460 1.110 Block 3 1.240 1.120 0.870

19. 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

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