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On the Coevolution of Language and Cognition—Gricean Intentions Meet Lewisian Conventions

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Logic and Algorithms in Computational Linguistics 2018 (LACompLing2018)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 860))

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Abstract

How might human language have emerged; and is it essentially based on convention or intention? The paper is an attempt at outlining an answer to the first question by trying to answer the second. It is not an attempt at formally modeling the evolution of language-apt creatures or the emergence of human communication. The aim is to achieve a better understanding of the phenomena (language and communication) to be modeled. Our starting point will be the idea that linguistic and other cognitive capacities must have coevolved and provided mutual scaffolding for one another. We will follow Tomasello, Bickerton and others in assuming that cooperation is the key to language evolution. This will motivate us to model the emergence of communication and meaning along game-theoretic lines, as suggested by Lewis and others. One pressing problem is the problem of equilibrium selection. We will briefly discuss an alleged solution but will find it wanting as it does not model the emergence of human language. The remainder of the paper will be devoted to arguing that combining Grice’s intention-based model of meaning with Lewis’ account of conventions helps explain how human language might have unfolded and solve the problem of equilibrium selection.

A long and complex train of thought can no more be carried on without the aid of words, whether spoken or silent, than a long calculation without the use of figures or algebra

Charles Darwin

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Notes

  1. 1.

    The idea that species or life forms transform was already around at the beginning of the 19th century (cf. [2]). Given that, before Darwin, the term ‘evolution’ was primarily used in an embryological sense (cf. [3]), precursors to Darwin’s account are occasionally called ‘transformist’ accounts.

  2. 2.

    There is accumulating evidence that cognitive control, which requires the inhibition of a prepotent (or automatic) response as well as cognitive flexibility, i.e., the ability to entertain and switch between (possibly conflicting) task sets or representations, is necessary for language processing and, in turn, augmented by having a symbolic language at one’s disposal (cf., e.g., [21,22,23,24,25]; cf. [26] for an overview). Analogical reasoning and transfer, i.e. “the application of learned regularities to novel domains and/or modalities” ([27], p. 117), seem also required for–and at the same enhanced by–language mastery (cf. [28,29,30,31]). Language and categorization are intimately intertwined, too (cf. [32] for review). This list could be continued (cf. [33] for a discussion).

  3. 3.

    By using the term ‘idea’ I don’t mean to suggest that it is a pictorial or percept-like representation that is thus evoked; still, it seems plausible to assume that more embodied (instead of fully amodal) representations are evoked by those early uses of signs and at this stage of cognitive and linguistic development (cf. [33]).

  4. 4.

    Cf., e.g., Jackendoff ‘s ([36], p. 238) suggestion as to possible incremental evolutionary steps.

  5. 5.

    Did language evolve primarily as a means of communication or a means of thought? Noam Chomsky and Robert Berwick, e.g., claim that “…language evolved as an instrument of internal thought, with externalization a secondary process” ([34], p. 74). Lev Vygotsky and Alexander Luria, on the other hand (and adopting, in contrast to Chomsky and Berwick, a developmental perspective), have it that “the sign primarily appears in the child’s behaviour as a means of social relations, as an inter-psychological function. Becoming afterwards a means by which the child controls its behaviour”, this being an example “of the transformation of means of social behaviour into means of individual psychological organization” ([13], p. 138). The ‘ecumenical’ account suggested here sees the two functions as being intimately intertwined (with communication being given a head start).

  6. 6.

    An intriguing question is how mental states with content– mental representations–might have evolved in the first place. This is a problem Teleosemantics aims to tackle (the locus classicus is [38]). It aspires to explain how certain inner states acquire the function of reliably indicating certain states of the world, and how they thus acquire (natural) meaning [39]. More specifically, as Karen Neander explains: “According to teleological theories of content, what a representation represents depends on the functions of the systems that produce or use the representation. The relevant notion of function is said to be the one that is used in biology and neurobiology […]. Proponents of teleological theories of content generally understand such functions to be what the thing with the function was selected for, either by ordinary natural selection or by some other natural process of selection” ([40], p. 1). These theories face various indeterminacy problems ([40], p. 1) and are said to classify too many states as representational states (cf. [41] for discussion). From the perspective of this paper, the most pressing problem is, again, to provide an incremental account of the transition from basic forms of representational states to fully propositional, complex thought and language, and of the coevolution of mental and semantic content.

  7. 7.

    From a strictly biological point of view, it is not language but language-apt-creatures that evolved; the focus would be on the purely biological prerequisites of language production and comprehension. In the paper, I will assume a broader perspective, as I am interested in the socio-cognitive prerequisites and effects of human language.

  8. 8.

    Again, that is neither to deny that others species have to coordinate their behavior as well. The claim is not that the need for coordination is a sufficient condition for the evolution of language. Nor is it to deny that other mechanisms (than coordination) might have played a role, too. In the animal kingdom, indices (the roar of a red deer as a reliable index of his size) and handicaps (the peacock’s tale reliably indicates prowess; [52]) might guarantee stable communication (cf. [53]). More importantly, the danger of losing reputation might also foster what is called honest communication (cf., e.g., [53,54,55,56]). And, as Mitchell Green points out, signaling may become reliable when animals have to pay a social cost, such as the loss of reputation or credibility, if they fake the signal (cf. [57]).

  9. 9.

    Here is a definition: “An assignment of strategies to players is a Nash equilibrium iff no agent can improve his payoff by deviating unilaterally from it. An equilibrium is strict iff each agent decreases his payoff by deviating unilaterally from it” ([60], p. 10). More formally, a “strategy vector s* = s1*, s2*, s3* … sn* is a Nash equilibrium if πi (si*, s−i*) ≥ πi (si, s−i*) for all si and all i” ([61], p. 64). Lewis himself defines it thus: “In an equilibrium combination, no one agent could have produced an outcome more to his liking by acting differently, unless some of the others’ actions also had been different” ([58], p. 8).

  10. 10.

    “A strategy si* is a best response to a strategy vector s*−i of the other players if πi (si*, s−i*) ≥ πi (si, s−i*), for all si” ([61], p. 64).

  11. 11.

    According to Lewis, players’ interests need not be perfectly aligned; it suffices if “coincidence of interest predominates” ([58], p. 24).

  12. 12.

    Cf. the Yale Open Online Course Game Theory by Ben Polak.

  13. 13.

    Similarly, an evolutionarily stable state of a population of type σ can be defined thus: “A population state σ is evolutionary stable if and only if for all τ ≠ σ, (i) π(σ, σ) ≥ π(τ, σ), (ii) If π(τ, σ) = π(σ, σ), then π(σ, τ) > π(τ, τ)” ([64], p. 208).

  14. 14.

    Here is an example of Huttegger and colleagues’s [66]: The sender may send signal 1 in response to state 1 and state 2, and signal 2 or signal 3 in response to state 3; the receiver may react to signal 1 by performing act 1 or act 2, but performs act 3 upon signal 2 and 3.

  15. 15.

    According to Patrick Grim, pragmatic features (such as behavior in accordance with Grice’ maxims) also “fall out as a natural result of information maximization in informational networks” ([68], p. 134). He employs the framework of spatialized game theory in which “agents do not interact randomly with all other agents in the population. They interact (or interact with increased probability) with specific agents–their neighbors in the network structure” ([68], p. 135). Given spatializiation, communication emerges “in response to environmental pressures on the basis of individual gains” ([68], p. 139). Note that the framework presupposes a cooperative, non-competitive context, as otherwise individuals would not be willing to freely share (valuable) information.

  16. 16.

    As Sterelny puts it, “language is not a signaling system”, nor is it a kind of “super-vervetese” ([73], p. 220).

  17. 17.

    According to Dan Sperber and Dedre Wilson, “[e]very act of ostensive communication communicates a presumption of its own optimal relevance” ([72], p. 15). And in ostensive inferential communication, one makes “manifest to an audience one´s intention to make manifest a basic layer of information” ([72], p. 54).

  18. 18.

    Someone might think that models of strategic communication based on games of incomplete information, as developed by Crawford and Sobel [75], fare better in this respect. It is somewhat questionable whether they can model the emergence of signals (how they acquire meaning), though. More pragmatic models will be briefly discussed below.

  19. 19.

    My aim is not (as that should require another paper) to come up with a watertight definition of language but only to pinpoint some of the key features human language exhibits; there are further candidates, of course (the locus classicus is [81]).

  20. 20.

    Some animals, in producing signs, seem to also display a certain sensitivity to communicative or social rules, as when duetting birds engage in some sort of turn-taking (cf. [84]).

  21. 21.

    Skyrms claims that “[n]ature has presented vervets with something very close to a classic Lewis signaling game” ([62], p. 23).

  22. 22.

    It is controversial whether there could have been a smooth transition from animal signals to human ostensive communication (cf. [93] vs. [35, 94]).

  23. 23.

    There is some evidence that these movements are less ritualized than Tomasello and colleagues suggest. Studies investigating how travel of mother-infant dyads in wild chimpanzees gets initiated found that there is more idiosyncrasy, flexibility, variability, and social negotiation in general in the use of these signals than has previously been acknowledged (cf. [96]). Still, these gestures are used to influence behavior, not minds.

  24. 24.

    I am grateful to Christian Nimtz for very helpful discussion on this point.

  25. 25.

    Skyrms would disagree; he insists- that “all meaning is natural meaning” ([62], p. 1).

  26. 26.

    More recently, pragmatic reasoning and inference has also become a subject of neuroscientific studies [99]; and pragmatic assumptions have been put to experimental test [100].

  27. 27.

    Iconicity is a tricky issue as the notion of resemblance or similarity is notoriously hard to spell out (cf. [102], or [103] for an overview). For present purposes, suffice it to say that an iconic sign somehow–by mere association or in combination with other cognitive skills–tends to evoke an image of the thing denoted in the listeners’ mind.

  28. 28.

    The earliest uses of the mammoth-sign may have been multi-modal, employing whatever means were available; gestures, sounds, pantomime, etc. (cf. [104]).

  29. 29.

    Or maybe mimetic skills were acquired in the context of social learning, as more elaborate tool-using-techniques were transmitted from one generation to the next. To learn complex action sequences requires high-fidelity transmission, which in turn is aided by imitation learning ([49]; cf. also [105]).

  30. 30.

    It may, but need not, be an expression of that desire. Expressive behavior, according to Dorit Bar-On, is a sort of proto-Gricean behavior, that exemplifies “a significant intermediate stage between mere code-like signaling and full (post-)Gricean linguistic communication […]” ([108], p. 348). And while I agree that expressive behavior may be interestingly different from mere ‘code-like signaling’ and have great explanatory value, I don’t quite see how to get from expressive communication to Gricean communication (cf. [107]).

  31. 31.

    Communicative intentions are out in the open. This is not to deny that speakers happen to have ignoble intentions and use linguistic means in the pursuit of ignoble goals. One thus ought to distinguish between communicative intentions (concerning what one is trying to communicate) and other intentions (concerning what else, beyond being understood, one is trying to achieve by communicating). Yet communication always aims at being understood. And only when signals have acquired fairly stable meaning can deception by linguistic means (lying) get off the ground.

  32. 32.

    Language might help to augment meta-cognitive capacities by engaging us in cognition-enhancing loops (cf. [33] for a discussion).

  33. 33.

    Consequently, some form of Gricean reasoning has to be built into the model–contrary to what Lewis claims; he has it that “meaningnn is a consequence of conventional signaling” ([58], p. 154). He already presupposes a certain level of cognitive sophistication as agents who engage in signaling conventions have cognitively demanding (higher-order) mutual expectations, on his account (an assumption Skyrms is eager to drop; cf. [67]).

  34. 34.

    As Franke explains, the “main idea is that pragmatics reasoning starts by considering some salient, perhaps unstrategic behavior of either speaker or listener. Call this level-0 behavior. Level-(k + 1) behavior is then defined, in simplified terms, as a rational strategy against level-k behavior” ([121], p. 278). This may help to model our ancestors' first communicative attempts.

  35. 35.

    As Daniel Lassiter and Noah Goodman point out, in applying Bayesian models of linguistic communication “we assume that speakers and listeners maintain probabilistic models of each other’s utterance planning and interpretation process, and that these models drive pragmatic language use”. ([122], p. 3806) More fully, it is assumed that “a listener L updates her information state, given that some utterance has been made, by reasoning about how the speaker would have chosen utterances or other actions in various possible worlds, weighing the result by the probability that those worlds are indeed actual:

    1. (7)

      PL(w/u) α PS(u/w) x PL(w).

    Conversely, a speaker chooses utterances by reasoning about how the listener will interpret the utterance, together with some private utterance preference PS(u) (representing, for example, frequency effects or a preference for brevity and ease of retrieval).

    1. (8)

      PS(u/w) α PL(w/u) x PS(u).

    These equations are both instantiations of Bayes’ rule. However, since they are mutually recursive reasoning could go on forever, unless we impose some bound. In addition, it is not obvious where in (7) and (8) literal meaning, as studies in compositional semantics, intrudes (cf. Franke 2009: Chap. 1)” [122].

  36. 36.

    It is highly implausible that our pre-linguistic ancestors already had mental attitudes (such as intentions) with perfectly precise mental content. It is equally implausible that they became language-apt yet were not able to think.

  37. 37.

    While a free-rider in the moral sense is someone who benefits from the fact that certain norms are in place in their community yet, occasionally at least, secretly contravenes these norms if it is to their own benefit, a semantic free-rider would benefit from their being semantic norms (or conventions) in place but also secretly contravene them. Given that communication aims at being understood and that communicative intention are out in the open, secretly contravening semantic norms (using words in another than their conventional meaning and trying to not let this on) does not seem like a sensible thing to do; at least it is hard to see what could thus be gained.

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Acknowledgements

I am tremendously grateful to Roussanka Loukanova, who organized a workshop on Logic and Algorithms in Computational Linguistics at the University of Stockholm in August 2017, and gave me the opportunity to present an earlier version of the paper; many thanks also to the other participants for valuable comments and critique. I am also very grateful to audiences at the Universities of Münster, Osnabrück and Zurich, especially to Susanne Boshammer, Charles Lowe, Christian Nimtz, Sebastian Schmoranzer and Niko Strobach. Finally, I would like to thank three anonymous referees for very helpful feedback and Rudi Owen Müllan and Charles Lowe for proofreading the manuscript.

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    Nikola Anna Kompa

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    Roussanka Loukanova

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Kompa, N.A. (2020). On the Coevolution of Language and Cognition—Gricean Intentions Meet Lewisian Conventions. In: Loukanova, R. (eds) Logic and Algorithms in Computational Linguistics 2018 (LACompLing2018). Studies in Computational Intelligence, vol 860. Springer, Cham. https://doi.org/10.1007/978-3-030-30077-7_8

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