The author would like to thank Karen Offen, David Nye and her husband Johannes Pedersen for helpful criticisms they offered of an earlier draft of this essay.

A “sender–receiver” framework based on models developed in several fields can provide a general treatment of communicative and symbolic phenomena, replacing traditional semiotic theories that have failed to live up to the hopes of their advocates. Sender–receiver models have mostly been applied to linguistic behavior, gestures, and other ephemeral interactions between individuals. I look at the application of this framework to enduring artifacts, including pictures, using indigenous rock art in Australia as a case study.

Drawing on models of communication due to Lewis and Skyrms, I contrast sender-receiver systems as they appear within and between organisms, and as they function in the bridging of space and time. Within the organism, memory can be seen as the sending of messages over time, communication between stages as opposed to spatial parts. Psychological memory and genetic memory are compared with respect to their relations to a sender-receiver model. Some puzzles about “genetic information” can be resolved by (...) seeing the genome as a cell-level memory with no sender. (shrink)

In his recent Gifford Lectures, Holmes Rolston argues that the informational character of biological phenomena is better explained by a theistic God of the process variety than by appealing to naturalistic biological explanations. In this paper, I assess Rolston’s argument by examining current biological and philosophical interpretations of the role of the theoretical concept of information in the description and explanation of biological phenomena. I find that none of these understandings of the concept allow Rolston’s conclusion. Natural selection explanations are (...) in principle sufficient for accounting for the informational character of biological phenomena. (shrink)

Open peer commentary on the article “Constructivism as a Key Towards Further Understanding of Communication, Culture and Society” by Raivo Palmaru. Upshot: I discuss the solution proposed in the target article to the classic sociological problem of “intersubjectivity,” which is based on the conceptual triad of culture, socialisation and communication. From a constructivist perspective, I argue that Palmaru’s proposal does not advance on this matter.

A communication process can be described in terms of a sender transmitting information to a receiver. What happens if one of the two subject roles in this process is virtualised, i.e. substituted by a machine? Is it still appropriate to refer to this as an information transfer even if its source or target is missing? Can information originate from an unknown sender or be transmitted to a (completely) unknown receiver? Before examining these questions and answering them, one has (...) to clarify what is understood by information. As it turns out, different interpretations of this term lead to considerably different answers to the initially raised questions. We consider these questions particularly important since the continuing dissemination of so called information and virtualisation technologies changes the human communication processes fundamentally. These changes are part of the ongoing formation of an information society and may eventually lead to the formation of a new image of man. (shrink)

This commentary seeks to supplement the case Quilty-Dunn et al. make for the psychological reality of languages-of-thought (LoTs) in two ways. First, it focuses on the reduced physical demands which LoT architectures often make compared to alternative architectures. Second, it embeds LoT research within a broader framework that can be leveraged to understand the evolution of LoTs.

Modeling work by Brian Skyrms and others in recent years has transformed the theoretical role of David Lewis's 1969 model of signaling. The latter can now be understood as a minimal model of communication in all its forms. In this article, we explain how the Lewis model has been generalized, and consider how it and its variants contribute to ongoing debates in several areas. Specifically, we consider connections between the models and four topics: The role of common interest in communication, (...) signaling within the organism, meaning, and the evolution of human communication and language. (shrink)

Vagueness is an extremely common feature of natural language, but does it actually play a positive, efficiency enhancing, role in communication? Adopting a probabilistic interpretation of vague terms, we propose that vagueness might act as a source of randomness when deciding what to assert. In this context we investigate the efficacy of multiple sender channels in which senders choose assertions stochastically according to vague definitions of the relevant words, and a receiver then aggregates the different signals. These vague channels (...) are then compared with Boolean channels in which assertions are selected deterministically based on classical definitions. We show that given a sufficient number of senders, a linear stochastic channel outperforms Boolean channels when performance is measured by the expected squared error between the actual value described by the senders and the receiver’s estimate of it based on the signals they receive. The number of senders required for vague channels to be at least as accurate as Boolean channels is shown to be a decreasing function of the size of the language i.e. the number of description labels available to the senders. Vague channels are then shown to be robust to transmission error provided the error rate is not too large. In addition, we investigate the behaviour of both Boolean and vague channels for a parametrised family of distributions on the input values. Finally, we consider optimal vague channels assuming a fixed number of senders and show that, provided there are more than two senders, a vague channel can be found that outperforms the optimal Boolean channel. In this context, we show that for channels with relatively low numbers of senders S-curve production functions are optimal. (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)

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)

Social Networking Sites (SNSs) not only enable users to read or create content about brands, but also to easily pass along this content using information diffusion mechanisms such as retweeting or sharing. While these capabilities can be optimal for viral marketing, little is known, however, about how reading brand messages passed along by SNS contacts influences online brand communication outcomes. Results of a survey with active SNS users indicate that (1) message evaluation, (2) the relationship with the sender, and (...) (3) the receiver’s opinion leadership and opinion-seeking levels influence not only the receiver’s intention to pass along the message further, but also his or her attitude towards the brand. The implications of these findings are discussed, including how these capabilities brought on by SNSs change the brand-consumer relationship online. (shrink)

Godfrey-Smith advocates for linking deception in sender-receiver games to the existence of undermining signals. I present games in which deceptive signals can be arbitrarily frequent, without this undermining information transfer between sender and receiver.

Brian Skyrms offers a fascinating demonstration of how fundamental signals are to our world. He uses various scientific tools to investigate how meaning and communication develop. Signals operate in networks of senders and receivers at all levels of life, transmitting and processing information. That is how humans and animals think and interact.

This chapter contains section titles: Introduction Senders and Receivers Content States of the Mind and Brain.

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)

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)

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)

Transfer of information between senders and receivers, of one kind or another, is essential to all life. David Lewis introduced a game theoretic model of the simplest case, where one sender and one receiver have pure common interest. How hard or easy is it for evolution to achieve information transfer in Lewis signaling?. The answers involve surprising subtleties. We discuss some if these in terms of evolutionary dynamics in both finite and infinite populations, with and without mutation.

This paper studies a sender-receiver game in which both players want the receiver to choose the state-optimal action. Before observing the state, the sender observes a “contextual signal,” a payoff-irrelevant signal that correlates with states and is imperfectly shared with the receiver. Once the sender observes the state, the sender sends a message to the receiver, incurring a small messaging cost. It is shown that there is no miscommunication in any efficient equilibrium if the messaging cost (...) is uniform or contextual information is poorly shared between players. However, if the messaging costs are different between some messages, and contextual information can affect the probability ranking of states and is shared reasonably well, any efficient equilibrium that favors the sender exhibits miscommunication. Furthermore, the messages that cause miscommunication can be coarse or ambiguous, depending on how well players share contextual information. (shrink)

David Lewis (1969) introduced sender-receiver games as a way of investigating how meaningful language might evolve from initially random signals. In this report I investigate the conditions under which Lewis signaling games evolve to perfect signaling systems under various learning dynamics. While the 2-state/2- term Lewis signaling game with basic urn learning always approaches a signaling system, I will show that with more than two states suboptimal pooling equilibria can evolve. Inhomogeneous state distributions increase the likelihood of pooling equilibria, (...) but learning strategies with negative reinforcement or certain sorts of mutation can decrease the likelihood of, and even eliminate, pooling equilibria. Both Moran and APR learning strategies (Bereby-Meyer and Erev 1998) are shown to promote successful convergence to signaling systems. A model is presented that illustrates how a language that codes state-act pairs in an order-based grammar might evolve in the context of a Lewis signaling game. The terms, grammar, and the corresponding partitions of the state space co-evolve to generate a language whose structure appears to reflect canonical natural kinds. The evolution of these apparent natural kinds, however, is entirely in service of the rewards that accompany successful distinctions between the sender and receiver. Any metaphysics grounded on the structure of a natural language that evolved in this way would track arbitrary, but pragmatically useful distinctions. (shrink)

In signaling games, a sender has private access to a state of affairs and uses a signal to inform a receiver about that state. If no common association of signals and states is initially available, sender and receiver must coordinate to develop one. How do players divide coordination labor? We show experimentally that, if players switch roles at each communication round, coordination labor is shared. However, in games with fixed roles, coordination labor is divided: Receivers adjust their mappings (...) more frequently, whereas senders maintain the initial code, which is transmitted to receivers and becomes the common code. In a series of computer simulations, player and role asymmetry as observed experimentally were accounted for by a model in which the receiver in the first signaling round has a higher chance of adjusting its code than its partner. From this basic division of labor among players, certain properties of role asymmetry, in particular correlations with game complexity, are seen to follow. (shrink)