1/15/16 Goals of this course (1) Nativism, Empiricism, Representation, and Domain-specificity Examine the Big Questions of cognitive science through the lens of computational modelling. • Is cognition a collection of separate domain-specific abilities or an interacting whole? Topics in Cognitive Modelling • How much of cognition is innate? Jan. 15, 2016 • Are mental representations symbolic or distributed? • Are mental processes based on rules or associations? John Lee, Chris Lucas • To what extent are our cognitive abilities determined by our School of Informatics physical body and environment (i.e., grounded/embodied)? University of Edinburgh 2 Nativism vs. empiricism Behaviourism Nativism: much of humans’ cognitive ability is inborn. • Dominant view in psychology from • (cf. Leibniz, Kant, Chomsky, Pinker) 1920s-1950s. • Only study observable behaviour, not unobservable mental representations, Empiricism: our cognitive abilities are the result of states and processes. learning from experience. • All behaviour results from learned • (cf. Locke, Hume, Skinner) associations (stimulus-response). We’ll discuss modern points of view on both sides, and ideas about representation and domain-specificity that typically go along with these views. 3 4 Image: life.com Behaviourism Problems with behaviourism • Dominant view in psychology from • What happens in moments of 1920s-1950s. “insight”? • Only study observable behaviour, not • Ex: Chimps figuring out how to get unobservable mental representations, out-of-reach bananas (Kohler, 1927). states and processes. • All behaviour results from learned associations (stimulus-response). • A highly empiricist view: eschews “human nature”, believes social environment is key. 5 6 Image: retrobookshop.co m Image: Kohler (1927). 1 1/15/16 Problems with behaviourism Problems with behaviourism • What makes humans different from other animals • How can learning even happen if nothing exists first? and why do human universals exist across cultures? “Nothing exists in the intellect that was not first in the • Partial list of cultural universals compiled by D. E. Brown:* senses.” – Locke* aesthetics; age statuses, terms; anthropomorphization; baby “Except the intellect itself.” – Leibniz* talk ; belief in s uper natur al/r eligion; beliefs about death, for tune and mis for tune; body ador nment; c hildbir th c us toms ; childhood fear of loud noises; classification of age, body parts, colors, fauna, flora, kin, sex, tools, weather conditions; • The bias-variance dilemma in statistical machine collective identities; conflict; coyness display; crying; learning is a more formal statement of this problem. culture/nature distinction; customary greetings; dance; death rituals; diurnality; divination; … 7 8 *As quoted in Pinker (2002). *As quoted in Pinker (2002). The cognitive revolution Nativism in linguistics • Chomsky (1959) attacks Skinner’s book Verbal • Chomsky’s “argument from the poverty of the stimulus”: Behavior. children’s grammatical knowledge is too complex to be learned from the input they receive. • Children do not, e.g., utter “house” every time they see one: language use is stimulus-independ ent. • Ex. Hierarchical structure vs. linear structure in Y-N questions. • Language is infinite; children produce sentences they have I am going. The dog is cute. Hyp: to form Y-N question, move never heard, apparently following complex grammatical rules Am I going? Is the dog c ute? aux. verb to front. (i.e., internal knowledge). • The start of the “cognitive revolution”: the study of the internal mind. • Additionally, Chomsky argues that much grammatical knowledge is innate. 9 10 Nativism in linguistics Nativism in linguistics • Chomsky’s “argument from the poverty of the stimulus”: Chomsky argues: children’s grammatical knowledge is too complex to be • Wrong answer involves linear structure (move the 1st aux). learned from the input they receive. The man who is going is here. • Ex. Hierarchical structure vs. linear structure in Y-N questions. Is the man w ho going is here? I am going. The dog is cute. Hyp: to form Y-N question, move Am I going? Is the dog c ute? aux. verb to front. • Correct answer involves knowing that sentences have hierarchical structure (move the aux in the main clause). [[The [man [w ho [is going]]]] [is here]]. The man who is going is here. Which aux. verb to move? • This type of sentence is not common enough for children to have Is the man w ho going is here? heard it, yet they do not make errors.* or • Therefore, knowledge of hierarchical structure and relevance of main Is the man w ho is going here? clause must be innate. 11 12 *Both of these points have been disputed more recently. 2 1/15/16 Theoretical assumptions What is in UG? In LAD? • A set of strong constraints on the possible forms that Basic idea: All languages follow certain principles, with languages can take (Universal Grammar). UG is certain parameters of variation. • Domain specific (e.g., refers to linguistic notions like nouns and Pr inc iple A: verbs, plus much more technical ones) A reflexive pronoun must have a higher antecedent in some domain. • Represented using symbols and deterministic rules. The domain parameter: Option (a): domain = the smallest clause containing the reflexive pronoun. Option (b): domain = the sentence containing the reflexive pronoun. • An associated learning system (Language Acquisition Device) that works with UG to allow acquisition of particular languages. Reflexive pronoun: himself, herself, etc. 13 Antec edent: the thing the pr onoun r efer s to. 14 What is in UG? In LAD? Nativism in other domains Basic idea: All languages follow certain principles, with Spelke (1994) presents a nativist view of development certain parameters of variation. in other domains. Pr inc iple A: A reflexive pronoun must have a higher antecedent in some domain. Claims that “core knowledge” of physics, psychology, The domain parameter: number, and geometry is innate. Option (a): domain = the smallest clause containing the reflexive pronoun. Option (b): domain = the sentence containing the reflexive pronoun. •E.g., Contact principle for physics: an object can only affect the motion of another object through contact. Parameters are set based on observed input data. Domain-specific: does not apply to animals. Various specific algorithms have been proposed, often based on “cues” or “triggers”, specific types of sentences that indicate specific parameter settings. 15 16 Infant knowledge of physical laws Infant knowledge of physical laws An experiment: • If a principle is innate, very young children should be surprised by seeing it violated. • Looking-time studies: 1. Habituate (bore) children with one display. Habituation Superficially different Violates principle 2. Compare time they look at two new displays: a. Violates principle but looks similar. b. Obeys principle but superficially different. 17 18 Image: Spelke, 1994 3 1/15/16 Infant knowledge of physical laws Spelke’s nativism: Results: Similar assumptions to Chomsky: •Infants look longer at violations of continuity than • Innate knowledge is domain-specific. violations of inertia (objects changing paths) • E.g., law of contact refers only to physics of objects. • Innate knowledge is about fundamental properties of the •At the same time, infants reach predictively in world that are not necessarily perceptually salient or even accordance with inertia. possible to perceive. Spelke’s interpretation: Similar arguments to Chomsky: •Innate knowledge of continuity principle. • Sophisticated early knowledge without much experience indicates innateness: “it just wouldn’t be possible to learn X based on the input received.” 19 20 Summing up Connectionism Strongly nativist researchers assume • A new incarnation of empiricism, stemming from AI • Many basic cognitive functions (perception, reasoning, research in the late 70s/early 80s. language, etc.) rely largely on innate knowledge. • The beginning of the “statistical revolution” in machine • This knowledge is domain-specific, generally using symbolic learning, moving from rule-based to statistical algorithms. representations. • Artificial neural networks show promise as robust and • Learning processes are also domain-specific, though many successful method for learning from data. nativists don’t actually say much about learning, focusing • In machine learning, research on ANNs and their more on what is not learned. descendants continues as a practical technique. • Sometimes assume strong modularity: different parts of the • In cognitive science, use of ANNs is typically part of a brain are responsible for different functions, and internal philosophical view: connectionism. workings of modules are opaque to each other. 21 22 Rethinking Innateness (Elman et al., 1996) Artificial neural networks • Elman et al.’s “biologically inspired” • ANNs reproduce what Elman et al. believe to be the empiricism: critical aspects of neural structure: • Learning mechanisms and experience are • Distributed computation using small computational elements. more powerful than nativists believe. • Each element accesses only local information. • Hardware implementation (i.e., neural • Information is represented in a distributed way. structure) is critical. • Responses are nonlinear. • Evolutionary origins and environment are also important. 23 24 Image: entwicklungswissenschaft. de Figure: http://en.wikipedia.org/wiki/Artificial_neural_network 4 1/15/16 What is “innate”? What is innate? • Elman et al.: “innate” as resulting from