Our understanding of communication and its evolution has advanced significantly through the study of simple models involving interacting senders and receivers of signals. Many theorists have thought that the resources of mathematical information theory are all that are needed to capture the meaning or content that is being communicated in these systems. However, the way theorists routinely talk about the models implicitly draws on a conception of content that is richer than bare informational content, especially in contexts where false content (...) is important. This article shows that this concept can be made precise by defining a notion of functional content that captures the degree to which different states of the world are involved in stabilizing senders’ and receivers’ use of a signal at equilibrium. A series of case studies is used to contrast functional content with informational content, and to illustrate the explanatory role and limitations of this definition of functional content. _1_ Introduction _2_ Modelling Framework _3_ Two Kinds of Content _3.1_ Informational content _3.2_ Functional content _4_ Cases _4.1_ Case 1: Simplest case _4.2_ Case 2: Partial pooling _4.3_ Case 3: Bottleneck _4.4_ Case 4: Partial common interest _4.5_ Case 5: Deception _4.6_ Case 6: A further problem arising from divergent interests _5_ Discussion Appendix. (shrink)

I introduce an extension of the Lewis-Skyrms signaling game, analysed from a dynamical perspective via simple reinforcement learning. In Lewis’ (Convention, Blackwell, Oxford, 1969) conception of a signaling game, salience is offered as an explanation for how individuals may come to agree upon a linguistic convention. Skyrms (Signals: evolution, learning & information, Oxford University Press, Oxford, 2010a) offers a dynamic explanation of how signaling conventions might arise presupposing no salience whatsoever. The extension of the atomic signaling game examined here—which I (...) will refer to as a salience game—introduces a variable parameter into the atomic signaling game which allows for degrees of salience, thus filling in the continuum between Skyrms’ and Lewis’ models. The model does not presuppose any salience at the outset, but illustrates a process by which accidentally evolved salience is amplified, to the benefit of the players. It is shown that increasing degrees of salience allow populations to avoid sub-optimal pooling equilibria and to coordinate upon conventions more quickly. (shrink)

This paper is concerned with how a simple metalanguage might coevolve with a simple descriptive base language in the context of interacting Skyrms–Lewis signaling games Lewis. We will first consider a metagame that evolves to track the successful and unsuccessful use of a coevolving base language, then we will consider a metagame that evolves a truth predicate for expressions in a coevolving base language. We will see how a metagame that tracks truth provides an endogenous way to break the symmetry (...) between indicative and imperative interpretations of the base language. Finally, we will consider how composite signaling games provide a way to characterize alternative pragmatic notions of truth. (shrink)

In this paper we use an experimental approach to investigate how linguistic conventions can emerge in a society without explicit agreement. As a starting point we consider the signaling game introduced by Lewis. We find that in experimental settings, small groups can quickly develop conventions of signal meaning in these games. We also investigate versions of the game where the theoretical literature indicates that meaning will be less likely to arise—when there are more than two states for actors to transfer (...) meaning about and when some states are more likely than others. In these cases, we find that actors are less likely to arrive at strategies where signals have clear conventional meaning. We conclude with a proposal for extending the use of the methodology of experimental economics in experimental philosophy. (shrink)

Lewis sender‐receiver games illustrate how a meaningful term language might evolve from initially meaningless random signals (Lewis 1969; Skyrms 2006). Here we consider how a meaningful language with a primitive grammar might evolve in a somewhat more subtle sort of game. The evolution of such a language involves the co‐evolution of partitions of the physical world into what may seem, at least from the perspective of someone using the language, to correspond to canonical natural kinds. While the evolved language may (...) allow for the sort of precise representation that is required for successful coordinated action and prediction, the apparent natural kinds reflected in its structure may be purely conventional. This has both positive and negative implications for the limits of naturalized metaphysics. (shrink)

David Hume’s skeptical solution to the problem of induction was grounded in his belief that we learn by means of custom. We consider here how a form of reinforcement learning like custom may allow an agent to learn how to learn in other ways as well. Specifically, an agent may learn by simple reinforcement to adopt new forms of learning that work better than simple reinforcement in the context of specific tasks. We will consider how such a bootstrapping process may (...) lead to a system that includes trial-and-error forms of learning like win-stay/lose-shift, probe and adjust, and simple reinforcement itself together with higher-rationality inferential tools. (shrink)

Wittgenstein used the notion of a language game to illustrate how language is interwoven with action. Here we consider how successful linguistic discourse of the sort he described might emerge in the context of a self-assembling evolutionary game. More specifically, we consider how discourse and coordinated action might self-assemble in the context of two generalized signaling games. The first game shows how prospective language users might learn to initiate meaningful discourse. The second shows how more subtle varieties of discourse might (...) co-emerge with a meaningful language. (shrink)

This article considers how a generalized signalling game may self-assemble as the saliences of the agents evolve by reinforcement on those sources of information that in fact lead to successful action. On the present account, generalized signalling games self-assemble even as the agents co-evolve meaningful representations and successful dispositions for using those representations. We will see how reinforcement on successful information sources also provides a mechanism whereby simpler games might compose to form more complex games. Along the way, I consider (...) how an old game might be appropriated to a new context by reinforcement on successful associations between old and new saliences. (shrink)

We present here a hierarchical model for the evolution of compositional language. The model has the structure of a two-sender/one-receiver Lewis signaling game augmented with executive agents who m...

In this paper we use an experimental approach to investigate how linguistic conventions can emerge in a society without explicit agreement. As a starting point we consider the signaling game introduced by Lewis. We find that in experimental settings, small groups can quickly develop conventions of signal meaning in these games. We also investigate versions of the game where the theoretical literature indicates that meaning will be less likely to arise---when there are more than two states for actors to transfer (...) meaning about and when some states are more likely than others. In these cases, we find that actors are less likely to arrive at strategies where signals have clear conventional meaning. We conclude with a proposal for extending the use of the methodology of experimental economics in experimental philosophy. (shrink)

Natural languages are compositional in that the meaning of complex expressions depends on those of the parts and how they are put together. Here, I ask the following question: why are languages compositional? I answer this question by extending Lewis–Skyrms signaling games with a rudimentary form of compositional signaling and exploring simple reinforcement learning therein. As it turns out: in complex worlds, having compositional signaling helps simple agents learn to communicate. I am also able to show that learning the meaning (...) of a function word, once meanings of atomic words are known, presents no difficulty. (shrink)

Insofar as empirical inquiry involves the coevolution of descriptive language and theoretical commitments, a satisfactory model of empirical knowledge should describe the coordinated evolution of both language and theory. But since we do not know what conceptual resources we might need to express our future theories or to provide our best future faithful descriptions of the world, we do not now know even what the space of future descriptive options might be. One strategy for addressing this shifting-resource problem is to (...) track the predictive and linguistic dispositions of inquirers rather than to track their theories and conceptual resources directly. Sender-predictor games, a variant of Skyrms–Lewis sender-receiver games, provide very simple models for the coordinated coevolution of predictive and linguistic dispositions. Such models explain how it is possible for (1) predictive and descriptive dispositions of inquirers to coevolve, (2) term-wise incommensurable, but nevertheless descriptively faithful languages, to sequentially evolve, and (3) a sort of underdetermination to occur where inquirers might satisfy their descriptive and predictive aims by revising their linguistic dispositions, their theoretical dispositions, or both. Such models also provide an elementary characterization of what it might mean for descriptions of the world to be faithful and hence for empirical inquiry to be successful. In doing so they provide a relatively weak, but perfectly clear, endogenous account of epistemic norms. (shrink)

We consider how human subjects establish signaling conventions in the context of Lewis-Skyrms signaling games. These experiments involve games where there are precisely the right number of signal types to represent the states of nature, games where there are more signal types than states, and games where there are fewer signal types than states. The aim is to determine the conditions under which subjects are able to establish signaling conventions in such games and to identify a learning dynamics that approximates (...) how they succeed when they do. Our results suggest that human agents tend to use a win-stay/lose-shift with inertia dynamics to establish conventions in such games. We briefly consider the virtues and vices of this low-rationality dynamics. (shrink)

This paper applies the theoretical criteria laid out by D’Arms et al. to various aspects of evolutionary models of signalling. The question that D’Arms et al. seek to answer can be formulated as follows: Are the models that we use to explain the phenomena in question conceptually adequate? The conceptual adequacy question relates the formal aspects of the model to those aspects of the natural world that the model is supposed to capture. Moreover, this paper extends the analysis of D’Arms (...) et al. by asking the following additional question: Are the models that we use sufficient to explain the phenomena in question? The sufficiency question asks what formal resources are minimally required for the model to get the right results most of the time. (shrink)

Belief-revision models of knowledge describe how to update one’s degrees of belief associated with hypotheses as one considers new evidence, but they typically do not say how probabilities become associated with meaningful hypotheses in the first place. Here we consider a variety of Skyrms–Lewis signaling game (Lewis in Convention. Harvard University Press, Cambridge, 1969; Skyrms in Signals evolution, learning, & information. Oxford University Press, New York, 2010) where simple descriptive language and predictive practice and associated basic expectations coevolve. Rather than (...) assigning prior probabilities to hypotheses in a fixed language then conditioning on new evidence, the agents begin with no meaningful language or expectations then evolve to have expectations conditional on their descriptions as they evolve to have meaningful descriptions for the purpose of successful prediction. The model, then, provides a simple but concrete example of how the process of evolving a descriptive language suitable for inquiry might also provide agents with conditional expectations that reflect the type and degree of predictive success in fact afforded by their evolved predictive practice. This illustrates one way in which the traditional problem of priors may simply fail to apply to one’s model of evolving inquiry. (shrink)

In game-theoretic signaling models, evolution tends to favor perfectly precise signaling systems, but in the natural world communication is almost always imprecise. I argue that standard explanations for this discrepancy are only partially sufficient, and I show that communication is often ambiguous because signal senders take advantage of context sensitivity. As evidence, I make two additions to the signaling model: a cost for more complex signaling strategies and the ability to combine information in signals with independent information. Analysis and simulation (...) of the altered model shows that it leads to the predicted outcome of evolution favoring ambiguous signaling. (shrink)

In recent years, many scholars have suggested that the Baldwin effect may play an important role in the evolution of language. However, the Baldwin effect is a multifaceted and controversial process and the assessment of its connection with language is difficult without a formal model. This paper provides a first step in this direction. We examine a game-theoretic model of the interaction between plasticity and evolution in the context of a simple language game. Additionally, we describe three distinct aspects of (...) the Baldwin effect: the Simpson– Baldwin effect, the Baldwin expediting effect and the Baldwin optimizing effect. We find that a simple model of the evolution of language lends theoretical plausibility to the existence of the Simpson– Baldwin and the Baldwin optimizing effects in this arena, but not the Baldwin expediting effect. (shrink)

This paper concerns how rule-following behavior might evolve in the context of a variety of Skyrms–Lewis signaling game, how such rules might subsequently evolve to be used in new contexts, and how such appropriation allows for the composition of evolved rules. We will also consider how the composition of simpler rules to form more complex rules may be significantly more efficient than evolving the complex rules directly. And we will review an example of rule following by pinyon and scrub jays (...) as an illustration of the appropriation of a rule to a new context :142–150, 2013a; Barrett, Philos Sci, 2014). The proposal here is that the composition of rules might occur in a way that is precisely analogous to such simple appropriation. Finally, we will briefly consider how any finite truth-functional operation might evolve by the sequential appropriation of simpler rules. (shrink)

Skyrms-Lewis signaling games illustrate how meaningful language may evolve from initially meaningless random signals (Lewis, Convention 1969; Skyrms 2008). Here we will consider how incommensurable languages might evolve in the context of signaling games. We will also consider the types of incommensurability exhibited between evolved languages in such games. We will find that sequentially evolved languages may be strongly incommensurable while still allowing for increasingly faithful descriptions of the world.

Signaling games with reinforcement learning have been used to model the evolution of term languages (Lewis 1969, Convention. Cambridge, MA: Harvard University Press; Skyrms 2006, “Signals” Presidential Address. Philosophy of Science Association for PSA). In this article, syntactic games, extensions of David Lewis’s original sender–receiver game, are used to illustrate how a language that exploits available syntactic structure might evolve to code for states of the world. The evolution of a language occurs in the context of available vocabulary and syntax—the (...) role played by each component is compared in the context of simple reinforcement learning. (shrink)

The emergence of signaling systems has been observed in numerous experimental and real-world contexts, but there is no consensus on which shared mechanisms underlie such phenomena. A number of explanatory mechanisms have been proposed within several disciplines, all of which have been instantiated as credible working models. However, they are usually framed as being mutually incompatible. Using an exemplar-based framework, we replicate these models in a minimal configuration which allows us to directly compare them. This reveals that the development of (...) optimal signaling is driven by similar mechanisms in each model, which leads us to propose three requirements for the emergence of conventional signaling. These are the creation and transmission of referential information, a systemic bias against ambiguity, and finally some form of information loss. Considering this, we then discuss some implications for theoretical and experimental approaches to the emergence of learned communication. (shrink)

I consider how complex logical operations might self-assemble in a signalling-game context via composition of simpler underlying dispositions. On the one hand, agents may take advantage of pre-evolved dispositions; on the other hand, they may co-evolve dispositions as they simultaneously learn to combine them to display more complex behaviour. In either case, the evolution of complex logical operations can be more efficient than evolving such capacities from scratch. Showing how complex phenomena like these might evolve provides an additional path to (...) the possibility of evolving more or less rich notions of compositionality. This helps provide another facet of the evolutionary story of how sufficiently rich, human-level cognitive or linguistic capacities may arise from simpler precursors. 1Signalling and Self-assembly2Simple Unary Logic Games3Composing Unary Functions for Binary Inputs 3.1Utilizing pre-evolved dispositions3.2Co-evolving logical dispositions3.3Learning appropriate outputs3.4Taking account of the full state-space of unary games3.5Role-free composition4Discussion 4.1Efficacy and efficiency of learning complex dispositions4.2Other binary operations4.3To infinity and beyond5Conclusion. (shrink)

In Lewisean signaling games with common interests, perfect signaling strategies have been shown to be optimal in terms of communicative success and evolutionary fitness. However, in signaling game models that involve contextual cues, ambiguous signaling strategies can match up to or even outperform perfect signaling. For a minimalist example of such a context signaling game, I will show that three strategy types are expected to emerge under evolutionary dynamics: perfect signaling, partial ambiguity and full ambiguity. Moreover, I will show that (...) partial ambiguity strategies are the most expected outcome and have the greatest basin of attraction among these three types when sender and receiver costs are arbitrarily small or similar. I will demonstrate that the evolutionary success of partial ambiguity is due to being risk dominant, which points to a better compatibility with other strategy types. (shrink)