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Biological Evolution of the Saussurean Sign as a Component of the Language Acquisition Device

Biological Evolution of the Saussurean Sign as a Component of the Language Acquisition Device. James R. Hurford University of Edinburgh, Scotland Presented by Laurel Preston May 17, 2006 Linguistics 580, Professor Lewis. Overview. Purpose Assumptions Machinery Simulations Results

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Biological Evolution of the Saussurean Sign as a Component of the Language Acquisition Device

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  1. Biological Evolution of the Saussurean Sign as a Component of the Language Acquisition Device James R. Hurford University of Edinburgh, Scotland Presented by Laurel Preston May 17, 2006 Linguistics 580, Professor Lewis

  2. Overview • Purpose • Assumptions • Machinery • Simulations • Results • Discussion

  3. Purpose • To propose an explanatory model of early stage language. • Nativist component: innate strategy for acquiring a communication system • Functional component: evolutionary mechanism whereby communicative success confers a selective advantage Summary of model: Communicative success confers a selective advantage Innate Saussurean strategy is the most advantageous for communicative success Saussurean individuals invade population, displacing rivals

  4. Simulation Summary • Initial populations with defined communicative behavior • Individuals with different strategies for language acquisition • Assume: communicative success confers selective advantage • Discover: which individuals come to dominate the population?

  5. Assumptions Saussurean bi-directional sign: the “fundamental formal structure” underlying human language

  6. Assumptions, continued • Language evolved for the purpose of communication • Early stage language existed; no syntax • Acquisition strategy can be transmitted genetically • Darwinian natural selection • Mendelian genetics • Transmission and reception are logically distinct

  7. Machinery: definitions • Successful communication • “any encounter between individuals where one (the transmitter), while mentally attending to a particular concept, carries out some observable act (which may be a gesture, a vocalization, or whatever), and another individual (the receiver), as a result of observing this act comes to attend to the same concept.” p.191

  8. Machinery: definitions (2) • Communicative potential, interpretive potential For individuals s, h and objects o:

  9. Machinery: definitions (3) • Matrix of transmission probabilities • Matrix of reception probabilities objects signals signals objects

  10. Machinery: definitions (3a) Matrix of transmission probabilities objects signals

  11. Machinery: definitions (3b) Matrix of reception probabilities signals objects

  12. Machinery: definitions (4) • Strategy • Component of the Language Acquisition Device • Individuals with different strategies will observe the same data but construct different internal representations • ‘strategy’ does not imply conscious intention or control

  13. Strategies: Imitator Transmission Reception Transmission^ Reception^ • transmission and interpretation are not necessarily coordinated • happy to imitate correct or incorrect behavior

  14. Strategies: Calculator Reception^ Transmission^ Transmission Reception • ‘optimal response’ to the observed sampling • transmission and interpretation are not necessarily coordinated

  15. Strategies: Saussurean Transmission Reception^ Transmission^ • acquisition of transmission is the same as for Imitator • transmission and interpretation are necessarily coordinated • never observes/samples transmission

  16. Simulations • Given: starting populations with different CPs: Random, Emergent, Perfect • 30 individuals, 5 objects, 7 signals • 20 simulations of each scenario; 100 generations • 3-way competitive simulations: 10 individuals from each strategy population • 2-way competitive simulations: 15 individuals from two of the strategy populations at a time: I vs C, C vs S, I vs S • 1-way non-competitive simluations

  17. Results: competitive

  18. Results: Calculators only

  19. Results: Imitators only

  20. Results: Saussureans only

  21. Discussion • How is ambiguity modeled? • Homonomy, synonomy • Calculators can’t say ‘I don’t know’; they have to guess • “I do not believe that I have loaded the dice by idealizing any of these strategies in such a way as to render it less (or more) successful” (p.221) • Do we agree?

  22. Calculator deriving reception behavior from observed transmission behavior signals objects signals objects

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