In line with Allen Newell's challenge to develop complete cognitive architectures, and motivated by a recent proposal for a unifying subsymbolic computational theory of cognition, we introduce the cognitive control architecture SEMLINCS. SEMLINCS models the development of an embodied cognitive agent that learns discrete production rule-like structures from its own, autonomously gathered, continuous sensorimotor experiences. Moreover, the agent uses the developing knowledge to plan and control environmental interactions in a versatile, goal-directed, and self-motivated manner. Thus, in contrast to several well-known (...) symbolic cognitive architectures, SEMLINCS is not provided with production rules and the involved symbols, but it learns them. In this paper, the actual implementation of SEMLINCS causes learning and self-motivated, autonomous behavioral control of the game figure Mario in a clone of the computer game Super Mario Bros. Our evaluations highlight the successful development of behavioral versatility as well as the learning of suitable production rules and the involved symbols from sensorimotor experiences. Moreover, knowledge- and motivation-dependent individualizations of the agents’ behavioral tendencies are shown. Finally, interaction sequences can be planned on the sensorimotor-grounded production rule level. Current limitations directly point toward the need for several further enhancements, which may be integrated into SEMLINCS in the near future. Overall, SEMLINCS may be viewed as an architecture that allows the functional and computational modeling of embodied cognitive development, whereby the current main focus lies on the development of production rules from sensorimotor experiences. (shrink)

Research has shown that both adults and children organize familiar activity into discrete units with consistent boundaries, despite the dynamic, continuous nature of everyday experiences. However, less is known about how observers segment unfamiliar event sequences. In the current study, we took advantage of the novelty that is inherent in modern dance. Modern dance features natural human motion but does not contain canonical goals—therefore, observers cannot recruit prior goal‐related knowledge to segment it. Our main aims were to identify whether observers (...) segment modern dance into the steps intended by the dancers, and what types of cues contribute to segmentation under these circumstances. Experiment 1 used a classic event segmentation task and found that adults were able to consistently identify only a few of the dancers’ intended steps. Experiment 2 tested adults in an offline labeling task. Results showed that steps which could more easily be labeled offline in Experiment 2 were more likely to be segmented online in Experiment 1. (shrink)

The idea that the form of a word reflects information about its meaning has its roots in Platonic philosophy, and has been experimentally investigated for concrete, sensory-based properties since the early 20th century. Here, we provide evidence for an abstract property of ‘boundedness’ that introduces a systematic, iconic bias on the phonological expectations of a novel lexicon. We show that this abstract property is general across events and objects. In Experiment 1, we show that subjects are systematically more likely to (...) associate sign language signs that end with a gestural boundary with telic verbs (denoting events with temporal boundaries, e.g., die, arrive) and with count nouns (denoting objects with spatial boundaries, e.g., ball, coin). In Experiments 2–3, we show that this iconic mapping acts on conceptual representations, not on grammatical features. Specifically, the mapping does not carry over to psychological nouns (e.g. people are not more likely to associate a gestural boundary with idea than with knowledge). Although these psychological nouns are still syntactically encoded as either count or mass, they do not denote objects that are conceived of as having spatial boundaries. The mapping bias thus breaks down. Experiments 4–5 replicate these findings with a new set of stimuli. Finally, in Experiments 6–11, we explore possible extensions to a similar bias for spoken language stimuli, with mixed results. Generally, the results here suggest that ‘boundedness’ of words' referents (in space or time) has a powerful effect on intuitions regarding the form that the words should take. (shrink)

Silent gesture is not considered to be linguistic, on par with spoken and sign languages. It is claimed that silent gestures, unlike language, represent events holistically, without compositional structure. However, recent research has demonstrated that gesturers use consistent strategies when representing objects and events, and that there are behavioral and clinically relevant limits on what form a gesture may take to effect a particular meaning. This systematicity challenges a holistic interpretation of silent gesture, which predicts that there should be no (...) stable form‐meaning correspondence across event representations. Here, we demonstrate to the contrary that untrained gesturers systematically manipulate the form of their gestures when representing events with and without a theme (e.g., Someone popped the balloon vs. Someone walked), that is, transitive and intransitive events. We elicited silent gestures and annotated them for manual features active in coding transitivity distinctions in sign languages. We trained linear support vector machines to make item‐by‐item transitivity predictions based on these features. Prediction accuracy was good across the entire dataset, thus demonstrating that systematicity in silent gesture can be explained with recourse to subunits. We argue that handshape features are constructs co‐opted from cognitive systems subserving manual action production and comprehension for communicative purposes, which may integrate into the linguistic system of emerging sign languages. We further suggest that nonsigners tend to map event participants to each hand, a strategy found across genetically and geographically distinct sign languages, suggesting the strategy's cognitive foundation. (shrink)

As formal theoretical linguistic methodology has matured, recent years have seen the advent of applying it to objects of study that transcend language, e.g., to the syntax and semantics of music (Lerdahl & Jackendoff 1983, Schlenker 2017a; see also Rebuschat et al. 2011). One of the aims of such extensions is to shed new light on how meaning is construed in a range of communicative systems. In this paper, we approach this goal by looking at narrative dance in the form (...) of Bharatanatyam. We argue that a semantic approach to dance can be modeled closely after the formal semantics of visual narrative proposed by Abusch (2013, 2014, 2021). A central conclusion is that dance not only shares properties of other fundamentally human means of expression, such as visual narrative and music, but that it also exhibits similarities to sign languages and the gestures of non-signers (see, e.g., Schlenker 2020) in that it uses space to track individuals in a narrative and performatively portray the actions of those individuals. From the perspective of general human cognition, these conclusions corroborate the idea that linguistic investigations beyond language (see Patel-Grosz et al. forthcoming) can yield insights into the very nature of the human mind and of the communicative devices that it avails. (shrink)

Humans are capable of understanding an incredible variety of actions performed by other humans. Even though these range from primary biological actions, like eating and fleeing, to acts in parliament or in poetry, humans generally can make sense of each other’s actions. Understanding other people’s actions is called action understanding, and it can transcend differences in race, gender, culture, age, and social and historical circumstances. Action understanding is the cognitive ability to make sense of another person’s action by integrating perceptual (...) information about the behavior with knowledge about the immediate and sociocultural contexts of the action and with one’s own experience. Scholars are increasingly dissatisfied with monodisciplinary approaches to understanding human action. Such one-sidedness can rest upon various motives. For example, “hermeneutic interpretations” of action understanding tend to emphasize historical and cultural influences while overlooking that ultimately such influences depend upon individual cognitive processes. This has provoked criticism of the corresponding assumption that humans are born as a “blank slate” and that culture is solely responsible for all cognitive contents. However, such critique in turn easily slides into an overemphasis on the biology of human nature and a denial of sociocultural influences on cognition (Pinker, 2003). Fortunately, recent interdisciplinary endeavors have shown that an interdisciplinary approach is preferable when investigating complex functions like action understanding. The purpose of this chapter is to propose a “mechanism-based explanation” of action understanding that will provide a theoretical framework for integrating various and often conflicting disciplinary insights. (shrink)

How can we explain the intentional nature of an expert’s actions, performed without immediate and conscious control, relying instead on automatic cognitive processes? How can we account for the differences and similarities with a novice’s performance of the same actions? Can a naturalist explanation of intentional expert action be in line with a philosophical concept of intentional action? Answering these and related questions in a positive sense, this dissertation develops a three-step argument. Part I considers different methods of explanations in (...) cognitive neuroscience (Bennett & Hacker’s philosophical, conceptual analysis; Marr’s three levels of explanation; Neural Correlates of Consciousness research; mechanistic explanation), defending ‘mechanistic explanation’ as a method that provides the necessary tools for integrating interdisciplinary insights into human action. Furthermore, a dynamic, explanatory mechanism allows the assessment of the impact of learning and development on expert action in a valuable way that other methods don’t. Part II continues by scrutinizing several cognitive neuroscientific theories of learning and development (neuroconstructivism; dual-processing theories; simulation theory; extended mind/cognition hypothesis), arguing for the complex interactions between different types of processing and different action representations involved in expert action performances. Moreover, according to our discussion of a particular ‘simulation theory’ these interactions can be influenced in several ways with the use of language, allowing an agent to configure a specific action representation for performance at a later stage. The results of Parts I and II are then applied in Part III to a parallel discussion of philosophical analyses of intentional action (discussing i.a. Frankfurt, Bratman, Pacherie and Ricoeur) and cognitive neuroscientific insights in it. Both approaches are found to converge in emphasizing the importance for an expert to develop stable patterns of actions that comply maximally not only with his intentions, but also with his motor expertise and with situational conditions. Consequently, his actions – automatic, or not – rely on this ‘sculpted space of actions’. (shrink)

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