People can instantaneously create novel conventions that link individual communicative signals to meanings, both in experiments and everyday communication. Yet a basic principle of natural communication is that the meaning of a signal typically contrasts with the meanings of alternative signals that were available but not chosen. That is, communicative conventions typically form a system, rather than consisting of isolated signal-meaning pairs. Accordingly, creating a novel convention linking a specific signal and meaning seems to require creating a system of conventions linking possible signals to possible meanings, of which the signal-meaning pair to be communicated is merely a sub-case. If so, people will not link signals and meanings in isolation; signal-meaning pairings will depend on alternative signals and meanings. We outline and address theoretical challenges concerning how instantaneous conventions can be formed, building on prior work on "virtual bargaining," in which people simulate the results of a process of negotiation concerning which convention, or system of conventions, to choose. Moreover, we demonstrate empirically that instantaneous systems of conventions can flexibly be created in a 'minimal' experimental paradigm. Experimental evidence from 158 people playing a novel signaling game shows that modifying both the set of signals, and the set of meanings, can indeed systematically modify the signal-meaning mappings that people may instantaneously construct. While consistent with the virtual bargaining account, accounting for these results may be challenging for some accounts of pragmatic inference.

Human-like computing will require machines to communicate interactively with people, to take in human knowledge and preferences, to explain the machine’s actions, and to generally coordinate human and machine behaviour. But even the simplest communicative interactions raise deep theoretical challenges. Human and machine spontaneously have to “agree” on the mapping between possible signals and messages. Such mappings are extremely flexible and influenced by large numbers of contextual factors in real-world interactions. Typically, there are many candidate signal-message mappings. Successful communication requires that both parties agree on the same mapping. We outline experimental and theoretical work exploring an approach to these problems based on “virtual bargaining,” according to which each communicative party attempts to infer which mapping would be agreed were prior communication possible. This chapter explores how such problems are solved by humans, and suggests directions for building computational models of these processes.

Statistical learning (SL), sensitivity to probabilistic regularities in sensory input, has been widely implicated in cognitive and perceptual development. Little is known, however, about the underlying mechanisms of SL and whether they undergo developmental change. One way to approach these questions is to compare SL across perceptual modalities. While a decade of research has compared auditory and visual SL in adults, we present the first direct comparison of visual and auditory SL in infants (8-10 months). Learning was evidenced in both perceptual modalities but with opposite directions of preference: Infants in the auditory condition displayed a novelty preference, while infants in the visual condition showed a familiarity preference. Interpreting these results within the Hunter and Ames model (1988), where familiarity preferences reflect a weaker stage of encoding than novelty preferences, we conclude that there is weaker learning in the visual modality than the auditory modality for this age. In addition, we found evidence of different developmental trajectories across modalities: Auditory SL increased while visual SL did not change for this age range. The results suggest that SL is not an abstract, amodal ability; for the types of stimuli and statistics tested, we find that auditory SL precedes the development of visual SL and is consistent with recent work comparing SL across modalities in older children.

Previous research examining trust of autonomous vehicles has largely focused on holistic trust, with little work on evaluation of specific behaviours and interactions with human-controlled vehicles. Six experiments examined the influence of pull-in distance, vehicle perspective (overtaking/being overtaken), following distance and immersion on self-reported evaluations of, and physiological responses to, autonomous motorway overtakes. We found that: (i) overtake manoeuvres were viewed more positively as pull-in distance increased before reaching a plateau at approximately 28 m, (ii) physiological-based orienting responses occurred for the smallest pull-in distances, (iii) participants being overtaken were more forgiving of a sharper pull-in if the overtaking vehicle was followed closely by another vehicle, and (iv) for two of three cross-experiment comparisons participants were more forgiving of smaller pull-in distances with lower immersion levels. Overall, the results suggest that the acceptability of an overtake manoeuvre increases linearly with pull-in distance up to a set point for both overtaking and being overtaken manoeuvres, with some influence of traffic context and levels of immersion. We discuss the findings in terms of implications for the development of assisted and fully autonomous vehicle systems that perform in a way that will be acceptable to both the vehicle occupants and other road users. (C) 2019 Elsevier Ltd. All rights reserved.

To drive safely among human drivers, cyclists and pedestrians, autonomous vehicles will need to mimic, or ideally improve upon, humanlike driving. Yet, driving presents us with difficult problems of joint action: 'negotiating' with other users over shared road space. We argue that autonomous driving provides a test case for computational theories of social interaction, with fundamental implications for the development of autonomous vehicles.

Accounts of individual differences in online language processing ability often focus on the explanatory utility of verbal working memory, as measured by reading span tasks. Although variability in reading span task performance likely reflects individual differences in multiple underlying traits, skills, and processes, accumulating evidence suggests that reading span scores also reflect variability in the linguistic experiences of an individual. Here, through an individual differences approach, we first demonstrate that reading span scores correlate significantly with measures of the amount of experience an individual has had with written language (gauged by measures that provide "proxy estimates" of print exposure). We then explore the relationship between reading span scores and online language processing ability. Individuals with higher reading spans demonstrated greater sensitivity to violations of statistical regularities found in natural language-as evinced by higher reading times (RTs) on the disambiguating region of garden-path sentences-relative to their lower span counterparts. This result held after statistically controlling for individual differences in a non-linguistic operation span task. Taken together, these results suggest that accounts of individual differences in sentence processing can benefit from a stronger focus on experiential factors, especially when considered in relation to variability in perceptual and learning abilities that influence the amount of benefit gleaned from such experience.

We used a non-linguistic experimental paradigm to explore the instantaneous creation and adaption of novel communicative systems of conventions. Groups of participants played a computer game, in which they sent and interpreted minimal signals to obtain shared rewards within a virtual scene. Within groups, trials manipulated the space of possible signals that could be sent, and the set of meanings to be expressed (the range of cases for the locations and quantities of rewards). Between groups, initial conditions were manipulated through early exposure to different sets of communicative cases. We observed participants spontaneously develop systems of conventions that were adapted to the full range of signal-meaning mappings encountered. Groups favoured systems optimised to their particular initial learning environment. These systems become entrenched and transferred to new signal-mapping environments to which they were not adapted.

We used a non-linguistic experimental paradigm to explore the instantaneous creation of new communicative conventions. Participants played a computer game, in which they sent and interpreted minimal signals to obtain shared rewards within a virtual scene. Trials manipulated the space of possible signals that could be sent, and the meanings to be expressed (locations and quantities of rewards); as such, optimal success in the task required participants to jointly construct signal-meaning mappings that functioned as part of a system, rather than in isolation. We observed different signalling strategies among participants, but with some individuals using ‘system-mapping’ conventions that globally reorganized in light of changing task constraints. Such behaviour reflects the principle of pre-emption in pragmatics, where the inferred meaning of an utterance depends on its relationship among a set of alternatives. Our initial findings provide a basis for future research, investigating contexts that are conducive to this phenomenon.

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Humans can communicate even with few existing conventions in common (e.g., when they lack a shared language). We explored what makes this phenomenon possible with a nonlinguistic experimental task requiring participants to coordinate toward a common goal. We observed participants creating new communicative conventions using the most minimal possible signals. These conventions, furthermore, changed on a trial-by-trial basis in response to shared environmental and task constraints. Strikingly, as a result, signals of the same form successfully conveyed contradictory messages from trial to trial. Such behavior is evidence for the involvement of what we term joint inference, in which social interactants spontaneously infer the most sensible communicative convention in light of the common ground between them. Joint inference may help to elucidate how communicative conventions emerge instantaneously and how they are modified and reshaped into the elaborate systems of conventions involved in human communication, including natural languages.

We used a novel experimental paradigm to investigate cognitive principles underpinning human communication. Through a computer game simulating different virtual scenes, pairs of participants sent and interpreted non-linguistic, minimal signals to achieve common goals. Participants’ signalling and interpretative actions demonstrated both flexibility and sensitivity to variations in the context of the shared visual scene: the same signal in one context could ‘flip’ its meaning in a new context. Such ‘invertible’ signals in the lab have their counterparts in patterns of real-world natural language use—from the phenomenon of enantiosemy (words/phrases that contain their ‘opposite’ meaning) to the pragmatics of satire and irony. But the emergence of such signals in our experiment challenges both correlational associative and recursive-mentalizing (‘mind-reading’) accounts of human communication and language. Instead, we point to a pragmatics-central perspective in which what is vital is our capacity for joint inference and coordination.

An essential element of goal-directed decision-making in social contexts is that agents' actions may be mutually interdependent. However, the most well-developed approaches to such strategic interactions, based on the Nash equilibrium concept in game theory, are sometimes too broad and at other times ‘overlook’ good solutions to fundamental social dilemmas and coordination problems. The authors propose a new theory of social decision-making—virtual bargaining—in which individuals decide among a set of moves on the basis of what they would agree to do if they could openly bargain. The core principles of a formal account are outlined (vis-à-vis the notions of ‘feasible agreement’ and explicit negotiation) and further illustrated with the introduction of a new game, dubbed the ‘Boobytrap game’ (a modification on the canonical Prisoner's Dilemma paradigm). In the first empirical data of how individuals play the Boobytrap game, participants' experimental choices accord well with a virtual bargaining perspective, but do not match predictions from a standard Nash account. Alternative frameworks are discussed, with specific empirical tests between these and virtual bargaining identified as future research directions. Lastly, it is proposed that virtual bargaining underpins a vast range of human activities, from social decision-making to joint action and communication.

Many social interactions require humans to coordinate their behavior across a range of scales. However, aspects of intentional coordination remain puzzling from within several approaches in cognitive science. Sketching a new perspective, we propose that the complex behavioral patterns or 'unwritten rules' governing such coordination emerge from an ongoing process of 'virtual bargaining'. Social participants behave on the basis of what they would agree to do if they were explicitly to bargain, provided the agreement that would arise from such discussion is commonly known. Although intuitively simple, this interpretation has implications for understanding a broad spectrum of social, economic, and cultural phenomena (including joint action, team reasoning, communication, and language) that, we argue, depend fundamentally on the virtual bargains themselves.

Implicit Learning Out of the Lab: Language and Music Patrick Rebuschat (p.rebuschat@lancaster.ac.uk) Martin Rohrmeier (mr1@mit.edu) Department of Linguistics and English Language Lancaster University, Lancaster, United Kingdom Department of Linguistics and Philosophy, Massachusetts Institute of Technology, Cambridge, MA, USA Morten H. Christiansen (christiansen@cornell.edu) Zoltan Dienes (dienes@sussex.ac.uk) Department of Psychology, Cornell University Ithaca, NY, USA School of Psychology, University of Sussex Brighton, United Kingdom Clement Francois (cfrancois@idibell.cat) Daniele Schon (daniele.schon@incm.cnrs-mrs.fr) Xiuyan Guo (xyguo@psy.ecnu.edu.cn) Shanghai Key Laboratory of Magnetic Resonance and School of Psychology and Cognitive Science, East China Normal University, Shanghai, China INSERM U 1106, Institut de Neuroscience des Systemes Aix-Marseille Universite, Marseille, France Shan Jiang (jiangs988@126.com) Feifei Li (lifeifei1206@163.com) School of Social Administration, Shanghai University of Political Science and Law, Shanghai, China School of Psychology and Cognitive Science, East China Normal University, Shanghai, China Jennifer B. Misyak (jennifer.misyak@wbs.ac.uk) Richard Widdess (rw4@soas.ac.uk) Behavioural Science Group, Warwick Business School University of Warwick, Coventry, United Kingdom Department of Music, School of Oriental and African Studies, University of London, United Kingdom Keywords: Implicit learning; statistical learning; explicit learning; music cognition; language acquisition. towards the use of more ecologically-valid stimuli. In addition to introducing novel and exciting subject areas, the research discussed in this symposium also reflects the strong tendency, within cognitive science, for methodological diversification. The talks will discuss data from behavioral and neurophysiological experiments as well as results of computational modeling. Goals and Scope Implicit learning, essentially the ability to acquire unconscious (implicit) knowledge, is a fundamental aspect of human cognition. This symposium focuses on the acquisition of two cognitive systems that are widely regarded as prime examples of implicit learning “in the real world”, namely language and music (see e.g. Rebuschat et al., 2011; Rohrmeier & Rebuschat, 2012). This symposium brings together leading researchers from across the cognitive sciences (psychology, linguistics, cognitive neuroscience, computer science, and musicology) in order to discuss current trends in implicit learning research, to identify the progress made in recent years, and to outline future directions to take, both in terms of topics and novel methodologies. The symposium will consist of five talks, followed by a brief general discussion. Each talk approaches the symposium topic from a highly innovative and interdisciplinary angle. Christiansen and Misyak focus on individual differences in implicit language learning, while Rebuschat concentrates on the role of implicit and explicit learning in second language (L2) acquisition. Francois and Schon’s work demonstrates the impressive effect of musical practice on the implicit learning of linguistic structure, while the last two talks, by Dienes and colleagues and by Rohrmeier and Widdess, focus on the implicit learning of Chinese tonal poetry and of syntactic features of North Indian music, respectively. These last two studies reflect a particularly important trend in implicit learning research Morten H. Christiansen and Jennifer B. Misyak Individual differences in implicit statistical learning and language Over the past decade, implicit learning under the guise of statistical learning has emerged as an important experimental paradigm with which to study mechanisms involved in language acquisition. Although few empirical studies have directly linked variation across statistical learning and language, it is generally assumed that greater sensitivity to statistical structure leads to better language performance. Here, we report the results of studies investigating the relationship of individual differences in statistical learning of adjacent and nonadjacent dependencies to variations in the processing of local and nonlocal dependencies in natural language. Together, the results indicate that individual differences in statistical learning are positively related to variations in language processing. However, the complexity of the pattern of interrelations suggests that future developmental and adult work on implicit statistical learning must incorporate careful attention to a diversity of natural dependency-structures to establish the proper relationship between adjacent and nonadjacent manifestations of statistical learning and the

Although statistical learning and language have been assumed to be intertwined, this theoretical presupposition has rarely been tested empirically. The present study investigates the relationship between statistical learning and language using a within-subject design embedded in an individual-differences framework. Participants were administered separate statistical learning tasks involving adjacent and nonadjacent dependencies, along with a language comprehension task and a battery of other measures assessing verbal working memory, short-term memory, vocabulary, reading experience, cognitive motivation, and fluid intelligence. Strong interrelationships were found among statistical learning, verbal working memory, and language comprehension. However, when the effects of all other factors were controlled for, performance on the two statistical learning tasks was the only predictor for comprehending relevant types of natural language sentences.

Although statistical learning and language have been assumed to be intertwined, this theoretical presupposition has rarely been tested empirically. The present study investigates the relationship between statistical learning and language using a within-subject design embedded in an individual-differences framework. Participants were administered separate statistical learning tasks involving adjacent and nonadjacent dependencies, along with a language comprehension task and a battery of other measures assessing verbal working memory, short-term memory, vocabulary, reading experience, cognitive motivation, and fluid intelligence. Strong interrelationships were found among statistical learning, verbal working memory, and language comprehension. However, when the effects of all other factors were controlled for, performance on the two statistical learning tasks was the only predictor for comprehending relevant types of natural language sentences.

Language comprehension is a complex task that involves constructing an incremental interpretation of a rapid sequence of incoming words before they fade from immediate memory, and yet the task is typically carried out effi ciently and with little conscious effort. Given the complexity associated with extracting intended meaning from an incoming linguistic signal, it is perhaps not surprising that multiple cognitive and perceptual systems are simultaneously engaged during the process. One ramifi cation of the multifarious nature of online language comprehension is that individuals tend to vary greatly in terms of their processing skill. Indeed, considerable by-subject variability in performance on syntactic processing tasks has been observed in numerous studies over the past two decades (e.g., King and Just, 1991 ; MacDonald, Just, and Carpenter, 1992 ; Novick, Trueswell, and Thompson-Schill, 2005 ; Pearlmutter and MacDonald, 1995 ; Swets et al., 2007 ), and yet debate still exists in regard to both the sources and the nature of this documented variability. This chapter explores some potential sources of variability in online comprehension skill. First, we briefl y discuss the proposed role that verbal working memory plays during syntactic processing, followed by the exploration of an alternative hypothesis that reassesses the effects of verbal working memory in terms of individual differences in learning-based, experiential factors. Subsequently, we consider the degree to which variability in “cognitive control” has the potential to account for variability in syntactic processing tasks, and then we touch on, briefl y, the infl uence of variability of perceptual systems on processes related to language comprehension. The literature on individual differences in syntactic processing is vast, and it is not possible to cover all of it in the small number of pages allotted to this chapter. Instead, we hope that the information contained here will help guide those with burgeoning interests in the area of individual differences research toward some of the current topics and debates within the fi eld. Before discussing factors that may account for variability in online syntactic C H A P T E R 1 7