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)

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)

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.

To coordinate action, information must be transmitted, processed, and utilized to make decisions. Transmission of information requires the existence of a signaling system in which the signals that are exchanged are coordinated with the appropriate content. Signaling systems in nature range from quorum signaling in bacteria [Schauder and Bassler, Kaiser ], through the dance of the bees [Dyer and Seeley ], birdcalls [Hailman, Ficken, and Ficken, Gyger, Marler and Pickert, Evans, Evans, and Marler, Charrier and Sturdy ], and alarm calls (...) in many species [Seyfarth and Cheney, Green and Maegner,Manser, Seyfarth and Cheney ], up to human language. Information processing includes filtering – that is discarding irrelevant information and passing along what is important – and integration of multiple pieces of information. Integration includes logical inference and voting. Finally, the information must be used to make decisions with consequences for payoffs that drive evolution or learning. (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)

Modeling and computer simulations, we claim, should be considered core philosophical methods. More precisely, we will defend two theses. First, philosophers should use simulations for many of the same reasons we currently use thought experiments. In fact, simulations are superior to thought experiments in achieving some philosophical goals. Second, devising and coding computational models instill good philosophical habits of mind. Throughout the paper, we respond to the often implicit objection that computer modeling is “not philosophical.”.

We are concerned here with how structural properties of language may come to reflect features of the world in which it evolves. As a concrete example, we will consider how a simple term language might evolve to support the principle of indifference over state descriptions in that language. The point is not that one is justified in applying the principle of indifference to state descriptions in natural language. Instead, it is that one should expect a language that has evolved in (...) the context of facilitating successful action to reflect probabilistic features of the world in which it evolved. (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)

This article concerns how rule-following behavior might evolve, how an old evolved rule might come to be appropriated to a new context, and how simple concepts might coevolve with rule-following behavior. In particular, we consider how the transitive inferential rule-following behavior exhibited by pinyon and scrub jays might evolve in the context of a variety of the Skyrms-Lewis signaling game, then how such a rule might come to be appropriated to carry out inferences regarding stimuli different from those involved in (...) the original evolution of the rule, and how this appropriation involves a step toward the evolution of basic ordinal concepts. (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)

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)

We consider how cue-reading, sensory-manipulation, and signaling games may initially evolve from ritualized decisions and how more complex games may evolve from simpler games by polymerization, template transfer, and modular composition. Modular composition is a process that combines simpler games into more complex games. Template transfer, a process by which a game is appropriated to a context other than the one in which it initially evolved, is one mechanism for modular composition. And polymerization is a particularly salient example of modular (...) composition where simpler games evolve to form more complex chains. We also consider how the evolution of new capacities by modular composition may be more efficient than evolving those capacities from basic decisions. (shrink)

Biologists and philosophers of biology have argued that learning rules that do not lead organisms to play evolutionarily stable strategies (ESSes) in games will not be stable and thus not evolutionarily successful. This claim, however, stands at odds with the fact that learning generalization---a behavior that cannot lead to ESSes when modeled in games---is observed throughout the animal kingdom. In this paper, I use learning generalization to illustrate how previous analyses of the evolution of learning have gone wrong. It has (...) been widely argued that the function of learning generalization is to allow for swift learning about novel stimuli. I show that in evolutionary game theoretic models learning generalization, despite leading to suboptimal behavior, can indeed speed learning. I further observe that previous analyses of the evolution of learning ignored the short term success of learning rules. If one drops this assumption, I argue, it can be shown that learning generalization will be expected to evolve in these models. I also use this analysis to show how ESS methodology can be misleading, and to reject previous justifications about ESS play derived from analyses of learning. (shrink)

I explore an agent-based model of the development and dissemination of scientific theory that makes very little use of any pre-defined “social structure” (such as partnerships or collaborations). In these models, under a broad range of values of the parameters, widespread (but not universal) “agreement” about scientific theory emerges. Moreover, the residual disagreement turns out to be important to developing new theories in the face of new evidence.

This article uses sim-max games to model perceptual categorization with the goal of answering the following question: To what degree should we expect the perceptual categories of biological actors to track properties of the world around them? I argue that an analysis of these games suggests that the relationship between real-world structure and evolved perceptual categories is mediated by successful action in the sense that organisms evolve to categorize together states of nature for which similar actions lead to similar results. (...) This conclusion indicates that both strongly realist and strongly antirealist views about perceptual categories are too simple. (shrink)

We are concerned here with explaining how successful rule-following behavior might evolve and how an old evolved rule might come to be successfully used in a new context. Such rule-following behavior is illustrated in the transitive judgments of pinyon and scrub-jays (Bond et al., Anim Behav 65:479–487, 2003). We begin by considering how successful transitive rule-following behavior might evolve in the context of Skyrms–Lewis sender–receiver games (Lewis, Convention. Harvard University Press, Cambridge, 1969; Skyrms, Philos Sci 75:489–500, 2006). We then consider (...) two ways that an agent might come to use an old evolved rule in a new context. The first involves the agent evolving successful dispositions for one concrete type of experience, then associating a new type of experience with the old evolved dispositions. The second involves the agent evolving dispositions that represent a general inferential schema, then composing these dispositions with others in a way that allows the agent to make inferences concerning a new concrete type of experience. (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)

Should the norms of honor cultures be classified as a variety of morality? In this paper, we address this question by considering various empirical bases on which norms can be taxonomically organised. This question is of interest both as an exercise in philosophy of social science, and for its potential implications in meta-ethical debates. Using recent data from anthropology and evolutionary game theory, we argue that the most productive classification emphasizes the strategic role that moral norms play in generating assurance (...) and stabilizing cooperation. Because honor norms have a similar functional role, this account entails honor norms are indeed a variety of moral norm. We also propose an explanation of why honor norms occur in a relatively unified, phenotypically distinctive cluster, thereby explaining why it is tempting to regard them as taxonomically distinct. (shrink)

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)

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)

There is a perennial philosophical dream of a certain natural order for the natural kinds. The name of this dream is ‘the hierarchy requirement’. According to this postulate, proper natural kinds form a taxonomy which is both unique and traditional. Here I demonstrate that complex scientific objects exist: objects which generate different systems of scientific classification, produce myriad legitimate alternatives amongst the nonetheless still natural kinds, and make the hierarchical dream impossible to realize, except at absurdly great cost. Philosophical hopes (...) for a certain order in nature cannot be fulfilled. Natural kinds crosscut one another, ubiquitously so, and this crosscutting spells the end of the hierarchical dream. (shrink)

In response to those who argue for ‘property cluster’ views of natural kinds, I use evolutionary models of sim-max games to assess the claim that linguistic terms will appropriately track sets of objects that cluster in property spaces. As I show, there are two sorts of ways this can fail to happen. First, evolved terms that do respect property structure in some senses can be conventional nonetheless. Second, and more crucially, because the function of linguistic terms is to facilitate successful (...) action in the world, when such success is based on something other than property clusters, we should not expect our terms to track those clusters. The models help make this second point salient by highlighting a dubious assumption underlying some versions of the cluster kinds view—that property clusters lead to successful generalization and induction in a straightforward way. As I point out, those who support property cluster kinds as natural can revert to a promiscuous realism in response to these observations. (shrink)

A curious ambiguity has arisen in the race debate in recent years. That ambiguity is what is actually meant by ‘biological racial realism’. Some philosophers mean that ‘race is a natural kind in biology’, while others mean that ‘race is a real biological kind’. However, there is no agreement about what a natural kind or a real biological kind should be in the race debate. In this article, I will argue that the best interpretation of ‘biological racial realism’ is one (...) that interprets ‘biological racial realism’ as ‘race is a genuine kind in biology’, where a genuine kind is a valid kind in a well-ordered scientific research program. I begin by reviewing previous interpretations of ‘biological racial realism’ in the race debate. Second, I introduce the idea of a genuine kind and compare it to various notions of natural and real biological kinds used in the race debate. Third, I present and defend an argument for my view. Fourth, I provide a few interesting consequences of my view for the race debate. Last, I provide a summary of the article. (shrink)

Policy and guideline proposals for ethical artificial intelligence research have proliferated in recent years. These are supposed to guide the socially-responsible development of AI for a common good. However, there typically exist incentives for non-cooperation ; and, these proposals often lack effective mechanisms to enforce their own normative claims. The situation just described constitutes a social dilemma—namely, a situation where no one has an individual incentive to cooperate, though mutual cooperation would lead to the best outcome for all involved. In (...) this paper, we use stochastic evolutionary game dynamics to model this social dilemma in the context of the ethical development of artificial intelligence. This formalism allows us to isolate variables that may be intervened upon, thus providing actionable suggestions for increased cooperation amongst numerous stakeholders in AI. Our results show how stochastic effects can help make cooperation viable in such a scenario. They suggest that coordination for a common good should be attempted in smaller groups in which the cost of cooperation is low, and the perceived risk of failure is high. This provides insight into the conditions under which we should expect such ethics proposals to be successful with regard to their scope, scale, and content. (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)

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...

This paper presents a Lewis-Skyrms signaling game that can exhibit a type of compositionality novel to the signaling game literature. The structure of the signaling game is motivated by an analogy to the alarm calls of putty-nosed monkeys (Cercopithecus nictitans). Putty-nosed monkeys display a compositional system of alarm calls with a semantics that is sensitive to the ordering of terms. This sensitivity to the ordering of terms has not been previously modeled with a Lewis-Skyrms signaling game literature. Signaling games are (...) valued for showing how communicative systems can arise with minimal learning tools. Simulation results show that basic (Roth-Erev) reinforcement learning is sufficient for the acquisition of a compositional signaling system sensitive to the ordering of terms. (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)

In response to those who argue for ‘property cluster’ views of natural kinds, I use evolutionary models of similarity-maximizing games to assess the claim that linguistic terms appropriately track sets of objects that cluster in property spaces. As I show, there are two sorts of ways this can fail to happen. First, evolved terms that do respect property structure in some senses can be conventional nonetheless. Second, and more crucially, because the function of linguistic terms is to facilitate successful action (...) in the world, when such success is based on something other than property clusters, we should not expect our terms to track those clusters. The models help make this second point salient by highlighting a dubious assumption underlying some versions of the cluster kinds view—that property clusters lead to successful generalization and induction in a straightforward way. As I point out, those who support property cluster kinds as natural can revert to a promiscuous realism in response to these observations. 1 Introduction2Cluster Kinds3Models and Results 3.1Similarity-maximizing games3.2Voronoi languages, clusters, and categories4Conventionality and Functionality in Kind Terms 4.1Conventional categories4.2Functionality and categories5Unnatural Perceptual Categories6The Payoff Relevance of Property Space7Conclusion. (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)

This article surveys the main philosophical and formal ideas revolving around language as being conventional from the perspective of game theory. For very basic situations, this leads to a coherent view of conventions that offers interesting insights. Although there exist many open problems, this article will argue by outlining partial solution attempts that there is no principled reason for not applying methods from game theory to them.

Sender–receiver games, first introduced by David Lewis ([1969]), have received increased attention in recent years as a formal model for the emergence of communication. Skyrms ([2010]) showed that simple models of reinforcement learning often succeed in forming efficient, albeit not necessarily minimal, signalling systems for a large family of games. Later, Alexander et al. ([2012]) showed that reinforcement learning, combined with forgetting, frequently produced both efficient and minimal signalling systems. In this article, I define a ‘dynamic’ sender–receiver game in which (...) the state–action pairs are not held constant over time and show that neither of these two models of learning learn to signal in this environment. However, a model of reinforcement learning with discounting of the past does learn to signal; it also gives rise to the phenomenon of linguistic drift. 1 Introduction2 Dynamic Signalling Games with Reinforcement Learning2.1 Introducing new states2.2 Swapping state–action pairs3 Discounting the Past3.1 Learning to signal in a dynamic world3.2 An unexpected outcome: linguistic drift4 ConclusionAppendix: A Markov Chain Analysis. (shrink)

Evolving signaling systems can be said to induce partitions on the space of world states as they approach equilibrium. Formalizing this claim provides a general framework for understanding what it means for language to “cut nature at its seams”. In order to avoid taking our current best science as providing the adaptive target for all evolving systems, the state space of the world must be characterized exclusively in terms of the coincidence of stimuli and payoffs that drives the evolution of (...) cognitive complexity. Cognition exploits the reliable clustering of events in this space. Using this framework to analyze our ordinary concepts of truth and justification, it appears that while justification can be a simple matter of conforming to historically entrenched strategies, truth cannot be fully specified on the basis of the system’s causal history, but requires a robust clustering in the larger world state space. (shrink)

Barrett and others have used Lewis-style evolutionary games to argue that we ought not to trust our scientific languages to inform us about ontology. More specifically, Barrett has shown that in some simple evolutionary contexts the best descriptive languages need not cut nature at its joints, that they may guide action as successfully as possible while simultaneously being deeply conventional. The present article expands upon Barrett’s argument, exploring the space for conventionalism in more metaphysically robust causal evolutionary models. By using (...) evolutionary prediction games, the present article examines the range of metaphysical facts in these models and shows how Barrett’s sceptical argument may be both challenged and expanded to cover these systems, resulting in a more thoroughgoing scepticism about what metaphysical conclusions may be drawn from linguistic and theoretical structure. (shrink)

All natural languages exhibit a distinction between content words and function words. Yet surprisingly little has been said about the e...

Compositionality is a key design feature of human language: the meaning of complex expressions is, for the most part, systematically constructed from the meanings of its parts and their manner of composition. This paper demonstrates that rudimentary forms of compositional communicative behavior can emerge from a variant of reinforcement learning applied to signaling games. This helps explain how compositionality could have emerged gradually: if unsophisticated agents can evolve prevalent dispositions to communicate compositional-like, there is a direct evolutionary benefit for adaptations (...) that exploit the systematicity in form-meaning mappings more rigorously. (shrink)

Skyrms-Lewis sender-receiver games with invention allow one to model how a simple mathematical language might be invented and become meaningful as its use coevolves with the basic arithmetic competence of primitive mathematical inquirers. Such models provide sufficient conditions for the invention and evolution of a very basic sort of arithmetic language and practice, and, in doing so, provide insight into the nature of a correspondingly basic sort of mathematical knowledge in an evolutionary context. Given traditional philosophical reflections concerning the nature (...) and preconditions of mathematical knowledge, these conditions are strikingly modest. (shrink)

This paper uses sim-max games to model perceptual categorization with the goal of answering the following question: to what degree should we expect the perceptual categories of biological actors to track properties of the world around them? I will argue that an analysis of these games suggests that the relationship between real-world structure and evolved perceptual categories is mediated by successful action in the sense that organisms evolve to categorize together states of nature for which similar actions lead to similar (...) results. This conclusion indicates that both strongly realist and strongly anti-realist views about perceptual categories are too simple. (shrink)

Signals regarding the behavior of others are an essential element of human moral systems and there are important evolutionary connections between language and large-scale cooperation. In particular, social communication may be required for the reputation tracking needed to stabilize indirect reciprocity. Additionally, scholars have suggested that the benefits of indirect reciprocity may have been important for the evolution of language and that social signals may have coevolved with large-scale cooperation. This paper investigates the possibility of such a coevolution. Using the (...) tools of evolutionary game theory, we present a model that incorporates primitive “moral signaling” into a simple setting of indirect reciprocity. This model reveals some potential difficulties for the evolution of “moral signals.” We find that it is possible for “moral signals” to evolve alongside indirect reciprocity, but without some external pressure aiding the evolution of a signaling system, such a coevolution is unlikely. (shrink)

Natural language expressions fall into two categories: content and function words. While function words are essential to compositional semantics, surprisingly little has been said about their emergence. In this paper, I will show that most extant approaches to the emergence of compositional signaling fail to account for the emergence of functional vocabulary. After providing a result that explains why this is so,, I will present a model and simulation results exhibiting conditions under which such vocabulary can emerge from simple learning (...) dynamics. This model captures the intuition that function words help aid communication with a limited vocabulary in the presence of contextual variability. (shrink)