Unit 5: Activation and Latency

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

2. Subsymbolic Quantities • Symbolic processing: chunks and productions • Subsymbolic processing: • chunk activation: controls retrieval • production utility: controls conflict resolution Unit 5

3. 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 Unit 5

4. Activation Activation of chunk i Base level activation of chunk i Spreading activation Activation from the source of activation j (typically 1/n ) Strength of association between j and i Unit 5

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

6. ISA city-fact country France city Paris ISA city-fact country Spain city Barcelona ISA city-fact country France city Marseille ISA city-fact country France city Orleans Situation at Time of Retrieval Goal ISA geography-test country France city nil capital Paris Chunks Goals bias certain chunks - Which chunk should be retrieved? - How long does it take? Both answers depend on the concept of activation. Unit 5

7. ISA city-fact Country Spain city Barcelona Goal ISA city-fact country France city Paris ISA geography-test country France city nil state “retrieving” capital Paris S11 ISA city-fact country France city Marseille France S12 ISA city-fact country France city Orleans S21 S13 Paris Spreading Activation Unit 5

8. ISA city-fact Country Spain city Barcelona ISA city-fact country France city Paris ISA city-fact country France city Marseille ISA city-fact country France city Orleans Spreading Activation Goal ISA geography-test country France city nil state “retrieving” capital Paris Source 1 W2S21 W1S11 Source 2 WjSji France W1S12 j sources i chunks W1S13 Paris W1…n = 1/n Where n is the spread from goal Unit 5

9. S5 Spread of Activation From Source (AKA Fan) ISA city-fact country France city Paris S1 fan=n+2 France ISA city-fact country France city Marseille S2 S4 S3 ISA city-fact country France city Orleans ISA geography-test country France city nil Unit 5

10. Why it Makes Sense • The source of activation contributes less (W) as the number of goal source slots increases (Wj=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 Unit 5

11. 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 Wj source spreads to • S-ln(n), where n is the number of other chunks Unit 5

12. A Retrieval Situation Chunk1 isa x slot1 bike* slot2 helmet slot3 coat 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)) Chunk2 isa x slota bike* slotb rock slotc punk Chunk3 isa z slota badmusic slotb umbrella* slotc rap =Goal> isa q slot5 bike slot6 umbrella Chunk4 isa q slot5 umbrella* slot6 disco Chunk5 isa q slot5 7 slot6 banana Chunk6 is m slota bear slotb lion slotc tiger +Retrieval> isa x slot1 bike slot2 helmet slot3 =item only bike is relevant source currently spreading so only bike applies to retrieval Chunk7 isa n slota umbrella* slotb classic slotc classical * places receiving activation boost so, for our retrieval A=B+WS=.5*(S-ln(4)) +retrievals get the highest activation chunk 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? Unit 5

13. Retrieval Latency Time to retrieve chunk i Latency factor Activation of chunk i Unit 5

14. 3 9 6 Study Test 6 The Sternberg Task Unit 5

15. The Sternberg Task Unit 5

16. Sji Sji Sji List Goal ISA do-Sternberg list list State “attend-test” item “3” Sternberg-Task Model ISA do-Sternberg list list item “3” State study ISA do-Sternberg list list item “9” State study ISA do-Sternberg list list item “6” State study 3 item list j =1 (source spread from the list context) Sji = S – ln (n+2) n increases  Sji decreases  Ai decreases Latency increases Unit 5

17. Sternberg Task: Targets (sgp :lf 0.64) ; sets F (setq *s* 3) ; sets S Unit 5

18. The Fan Effect (Anderson, 1974) Study A <person> is in the <location> 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. <person> could have occurred in 1, 2, or 3 facts. <location> could have occurred in 1, 2, or 3 facts. Test: studied? A hippie is in the park. (target) A debutante is in the church. (foil) Unit 5

19. Fan-Experiment Results Unit 5

20. 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 Unit 5