1. Unit 5: Activation and Latency February 11, 2003

2. Unit 52 Subsymbolic Quantities  Symbolic processing: chunks and productions  Subsymbolic processing: –chunk activation: controls retrieval –production utility: controls conflict resolution

3. Unit 53 Activation The activation of a chunk depends on:  History of usage of the chunks (how frequently and recently the chunk has been used)  base-level activation  Context in which the chunk is used  spreading activation

4. Unit 54 Activation Activation of chunk i Base level activation of chunk i Activation from the source of activation j (typically 1/n ) Strength of association between j and i Spreading activation

5. Unit 55 Chunk Retrieval (p request-retrieval =goal> ISA geography-test country =x capital =c city nil state “get-retrieval”  =goal> state “retrieving” +retrieval> ISA city-fact country =x) (p get-retrieval =goal> ISA geography-test state “retrieving” country =x city nil =retrieval> ISA city-fact city =y  =goal> state “done” city =y)

6. Unit 56 Situation at Time of Retrieval - Which chunk should be retrieved? - How long does it take? Both answers depend on the concept of activation. ISA geography-test country France city nil capital Paris Goal ISA city-fact country France city Paris ISA city-fact country France city Orleans ISA city-fact country France city Marseille ISA city-fact country Spain city Barcelona Goals bias certain chunks Chunks

7. Unit 57 Spreading Activation ISA geography-test country France city nil state “retrieving” capital Paris Goal France Paris S 21 S 13 S 12 S 11 ISA city-fact country France city Paris ISA city-fact country France city Orleans ISA city-fact country France city Marseille ISA city-fact Country Spain city Barcelona

8. Unit 58 Spreading Activation ISA geography-test country France city nil state “retrieving” capital Paris Goal France Paris ISA city-fact country France city Paris ISA city-fact country France city Orleans ISA city-fact country France city Marseille ISA city-fact Country Spain city Barcelona W 1 S 11 W 1 S 12 W 1 S 13 W 2 S 21 W 1…n = 1/n Where n is the spread from goal Source 1 Source 2 W j S ji j sources i chunks

9. Unit 59 Spread of Activation From Source (AKA Fan) ISA city-fact country France city Paris ISA city-fact country France city Orleans ISA city-fact country France city Marseille France S3S3 S2S2 S1S1 ISA geography-test country France city nil S4S4 S5S5 fan=n+2

10. Unit 510 Why it Makes Sense  The source of activation contributes less (W) as the number of goal source slots increases (W j =1/n) –This can be though of as a limit on how much can be profitably focused on at once –As more chunks are in goals slots, so attention (working memory) gets spread thin  Spreading activation also is less if it has to spread to more things… S-ln(n) –As n increases the strength of the spread decreases *note the small n’s refer to different quantities n in the first case is number of goal sources n in the second case is the number of chunks matching the source

11. Unit 511 Two limits  Limitation on spread as a function of how many items W spreads to –(our class model will not utilize this)  Limitation on spread as a function of the number of chunks that the W j source spreads to –S-ln(n), where n is the number of other chunks

12. Unit 512 +Retrieval> isa x slot1 bike slot2 helmet slot3 =item Chunk1 isa x slot1 bike* slot2 helmet slot3 coat Chunk2 isa x slota bike* slotb rock slotc punk Chunk3 isa z slota badmusic slotb umbrella* slotc rap Chunk5 isa q slot5 7 slot6 banana Chunk4 isa q slot5 umbrella* slot6 disco Chunk7 isa n slota umbrella* slotb classic slotc classical Chunk6 is m slota bear slotb lion slotc tiger so, for our retrieval A=B+WS=.5*(S-ln(4)) =Goal> isa q slot5 bike slot6 umbrella two slots in goal, so w=1/2 say bike is in 2 chunks so bike WS=.5*(S-ln(4)) say umbrella is in 3 chunks so umbrella WS=.5*(S-ln(5)) only bike is relevant source currently spreading so only bike applies to retrieval * places receiving activation boost +retrievals get the highest activation chunk A Retrieval Situation Even non-matching chunks can be retrieved if they are highest after penalty (in this lesson non- matching chunks will only be retrieved if the correct chunk is not present because there is no noise in the equation) Can you ever retrieve a chunk of the wrong type?

13. Unit 513 Retrieval Latency Time to retrieve chunk i Latency factor Activation of chunk i

14. Unit 514 The Sternberg Task Study 3 9 6 Test6

15. Unit 515 The Sternberg Task

16. Unit 516 Sternberg-Task Model ISA do-Sternberg list item “3” State study ISA do-Sternberg list item “9” State study ISA do-Sternberg list item “6” State study ISA do-Sternberg list State “attend-test” item “3” Goal j =1 (source spread from the list context) Sji = S – ln (n+2) n increases  Sji decreases  Ai decreases  Latency increases List Sji 3 item list

17. Unit 517 Sternberg Task: Targets (sgp :lf 0.64) ; sets F (setq *s* 3) ; sets S

18. Unit 518 The Fan Effect (Anderson, 1974) Study A is in the could have occurred in 1, 2, or 3 facts. A hippie is in the park. A hippie is in the church. A hippie is in the bank. A captain is in the park. A captain is in the church. A debutante is in the bank. A fireman is in the park. Test: studied? A hippie is in the park. (target) A debutante is in the church. (foil)

19. Unit 519 Fan-Experiment Results

20. Unit 520 Tips  Read only the person and the location The lawyer is in the church Use =visual-location> … screen-x (within 10 20)  Meanings (lawyer* isa meaning word “lawyer”)  Two productions that retrieve a fact  Will need to find S and F that best fit data