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 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)

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 predictive and descriptive dispositions of inquirers to coevolve, term-wise incommensurable, but nevertheless descriptively faithful languages, to sequentially evolve, and 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)

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)

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 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)

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)

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)

Natural language contains many expressions with underspecified emotive content. This paper proposes a way to resolve such underspecification. Nonmonotonic inference over a knowledge base is used to derive an expected interpretation for emotive expressions in a particular context. This ‘normal’ meaning is then taken to influence the hearer’s expectations about probable interpretations, and, because of these probable interpretations, the decisions of the speaker about when use of underspecified emotive terms is appropriate.

Natural language contains many expressions with underspecified emotive content. This paper proposes a way to resolve such underspecification. Nonmonotonic inference over a knowledge base is used to derive an expected interpretation for emotive expressions in a particular context. This ‘normal’ meaning is then taken to influence the hearer’s expectations about probable interpretations, and, because of these probable interpretations, the decisions of the speaker about when use of underspecified emotive terms is appropriate.

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)