scholarly journals Co-dependency of exchanged behaviors is a cue for agency attribution in 10-month-olds

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tibor Tauzin ◽  
György Gergely
Keyword(s):  
Social Interactions ◽  
Random Signal ◽  
Social Goals ◽  
Signal Sequences ◽  
Interacting Agents ◽  
Directed Action ◽  
Intentional Agency

AbstractGoal-directed social interactions (whether instrumental or communicative) involve co-dependent, partially predictable actions of interacting agents as social goals cannot be achieved by continuously exchanging the same, perfectly predictable, or completely random behaviors. We investigated whether 10-month-olds are sensitive to the co-dependence and degree of predictability in an interactive context where unfamiliar entities exchanged either perfectly predictable (identical), partially predictable (co-dependent), or non-predictable (random) signal sequences. We found that when—following the interactive exchanges—one of the entities turned in the direction of one of two lateral target objects, infants looked more at the indicated referent, but only in the partially predictable signals condition. This shows that infants attributed agency to the orienting entity and interpreted its turning action as a referential object-directed action. The present findings suggest that the co-dependency and partial predictability of exchanged behaviors can serve as an abstract structural cue to attribute intentional agency and recognize goal-directed social interactions.

scholarly journals Dyadic brain modelling, mirror systems and the ontogenetic ritualization of ape gesture

2014 ◽  
Vol 369 (1644) ◽  
pp. 20130414 ◽  
Author(s):  
Michael Arbib ◽  
Varsha Ganesh ◽  
Brad Gasser
Keyword(s):  
Social Interactions ◽  
General Framework ◽  
Mirror Neuron ◽  
Neural Mechanisms ◽  
Interacting Agents ◽  
Ontogenetic Ritualization ◽  
Computational Detail ◽  
Simulation Results ◽  
Two Bodies

The paper introduces dyadic brain modelling, offering both a framework for modelling the brains of interacting agents and a general framework for simulating and visualizing the interactions generated when the brains (and the two bodies) are each coded up in computational detail. It models selected neural mechanisms in ape brains supportive of social interactions, including putative mirror neuron systems inspired by macaque neurophysiology but augmented by increased access to proprioceptive state. Simulation results for a reduced version of the model show ritualized gesture emerging from interactions between a simulated child and mother ape.

scholarly journals A Dynamical Generative Model of Social Interactions

2021 ◽  
Vol 15 ◽  
Author(s):  
Alessandro Salatiello ◽  
Mohammad Hovaidi-Ardestani ◽  
Martin A. Giese
Keyword(s):  
Social Interaction ◽  
Social Interactions ◽  
Automatic Generation ◽  
Generative Models ◽  
Generative Model ◽  
Interacting Agents ◽  
Visual Inputs ◽  
Classical Dynamical System ◽  
Motion Features ◽  
Dynamical System Models

The ability to make accurate social inferences makes humans able to navigate and act in their social environment effortlessly. Converging evidence shows that motion is one of the most informative cues in shaping the perception of social interactions. However, the scarcity of parameterized generative models for the generation of highly-controlled stimuli has slowed down both the identification of the most critical motion features and the understanding of the computational mechanisms underlying their extraction and processing from rich visual inputs. In this work, we introduce a novel generative model for the automatic generation of an arbitrarily large number of videos of socially interacting agents for comprehensive studies of social perception. The proposed framework, validated with three psychophysical experiments, allows generating as many as 15 distinct interaction classes. The model builds on classical dynamical system models of biological navigation and is able to generate visual stimuli that are parametrically controlled and representative of a heterogeneous set of social interaction classes. The proposed method represents thus an important tool for experiments aimed at unveiling the computational mechanisms mediating the perception of social interactions. The ability to generate highly-controlled stimuli makes the model valuable not only to conduct behavioral and neuroimaging studies, but also to develop and validate neural models of social inference, and machine vision systems for the automatic recognition of social interactions. In fact, contrasting human and model responses to a heterogeneous set of highly-controlled stimuli can help to identify critical computational steps in the processing of social interaction stimuli.

Social Rewards: From Basic Social Building Blocks to Complex Social Behavior

2018 ◽  
Vol 13 (6) ◽  
pp. 700-717 ◽  
Author(s):  
Diana I. Tamir ◽  
Brent L. Hughes
Keyword(s):  
Social Behavior ◽  
Social Interactions ◽  
Social Behaviors ◽  
Building Blocks ◽  
Social Goals ◽  
Future Research ◽  
Dual Approach ◽  
Complex Social Behavior ◽  
Social Act ◽  
Social Rewards

Humans are social creatures, engaging almost constantly in social behaviors that serve ultimate social goals, such as forming strong bonds with one another. However, most social behaviors provide only incremental progress toward an ultimate goal. Instead, the drive to engage in any individual social act may derive from its proximal value rather than its ultimate goal. Thus, this proximal value forms the foundation on which the complexities of human sociality are built. We describe two complementary approaches for using proximal social rewards to understand social behaviors and their ultimate goals: (a) decontextualizing social rewards—paring down complex social interactions can help identify which basic building blocks remain valuable even in minimalistic contexts—and (b) recontextualizing social rewards—reintroducing motivational and contextual factors into the study of social experience can help identify how proximal rewards serve their ultimate function. We discuss how this dual-approach framework can inform future research by bridging basic social building blocks and real-world social goals.

THE SOCIAL NATURE OF INFORMATION AND THE ROLE OF TRUST

2002 ◽  
Vol 11 (03n04) ◽  
pp. 381-403 ◽  
Author(s):  
CRISTIANO CASTELFRANCHI
Keyword(s):  
Social Interactions ◽  
Social Relationships ◽  
Social Aspects ◽  
Social Construct ◽  
Social Nature ◽  
Interacting Agents ◽  
Information Agents ◽  
The Social ◽  
Nature Of Information

In this paper, I claim that "information" is a social construct, is created and tailored on purpose by somebody for somebody else or collectively, accepted, believed, or propagated through social interactions. In particular, I argue about the essential social nature of several crucial aspects of information in IT and specifically in relation to Information Agents. After situating this view of information within the broader perspective of Social Artificial Intelligence — the new AI paradigm — I analyize the intrinsic social aspects of information ontology, search and access, presentation, overload, credibility and sources, value. The issue of real "collaboration" in providing information deserves special attention and I introduce our theory of over-help and of the ability to provide something different from what is requested in order to satisfy the real need beyond the request. In the second part, I focus on the crucial role of trust (an intrinsically social and cognitive notion) for dealing with information and sources especially on the web. My objective is to claim that: if information per se is a social construct, then its technology should be socially designed and integrated, and that machines must be involved in real social relationships because they have to mediate them among humans. It is necessary incorporating some part of this social knowledge and capability in the information technology itself, especially in adaptive and interacting "agents" and MAS.

scholarly journals Network Structured Kinetic Models of Social Interactions

2021 ◽  
Author(s):  
Martin Burger
Keyword(s):  
Social Interactions ◽  
Kinetic Equations ◽  
Reaction Diffusion ◽  
Reaction Diffusion Equations ◽  
Macroscopic Models ◽  
Interacting Agents ◽  
Microscopic Interactions ◽  
Mesoscopic Level ◽  
Nonlocal Reaction

AbstractThe aim of this paper is to study the derivation of appropriate meso- and macroscopic models for interactions as appearing in social processes. There are two main characteristics the models take into account, namely a network structure of interactions, which we treat by an appropriate mesoscopic description, and a different role of interacting agents. The latter differs from interactions treated in classical statistical mechanics in the sense that the agents do not have symmetric roles, but there is rather an active and a passive agent. We will demonstrate how a certain form of kinetic equations can be obtained to describe such interactions at a mesoscopic level and moreover obtain macroscopic models from monokinetics solutions of those. The derivation naturally leads to systems of nonlocal reaction-diffusion equations (or in a suitable limit local versions thereof), which can explain spatial phase separation phenomena found to emerge from the microscopic interactions. We will highlight the approach in three examples, namely the evolution and coarsening of dialects in human language, the construction of social norms, and the spread of an epidemic.

scholarly journals Variability of signal sequences in turn-taking exchanges induces agency attribution in 10.5-mo-olds

2019 ◽  
Vol 116 (31) ◽  
pp. 15441-15446 ◽  
Author(s):  
Tibor Tauzin ◽  
György Gergely
Keyword(s):  
Information Transfer ◽  
Gaze Following ◽  
Relevant Feature ◽  
Acoustic Features ◽  
Signal Sequences ◽  
Single Entity ◽  
Turn Taking ◽  
Intentional Agency ◽  
Preverbal Infants ◽  
Communicative Abilities

Infants’ sensitivity to contingent reactivity as an indicator of intentional agency has been demonstrated by numerous referential gaze-following studies. Here we propose that variability of signal sequences in a turn-taking exchange provides an informative cue for infants to recognize interactions that may involve communicative information transfer between agents. Our experiment demonstrates that based on the abstract structural cue of variability of exchanged signal sequences, 10.5-mo-olds gaze-followed an entity’s subsequent object-orienting action to fixate the same object. This gaze-following effect did not depend on the specific acoustic features of the sound signals produced. However, no orientation following to target was induced when the exchanged signal sequences were identical, or when only a single entity produced the variable sound sequences. These results demonstrate infants’ early sensitivity to detect signal variability in turn-taking interactions as a relevant feature of communicative information transfer, which induces them to attribute intentional agency and communicative abilities to the participating entities. However, when no variability was present in the exchanged signals, or when the variable signal sequences were produced by a single entity alone, infants showed no evidence of attributing agency. In sum, we argue that perceiving contingent turn-taking exchange of variable signal sequences induce 10.5-mo-old preverbal infants to recognize such interactions as potentially involving communicative information transmission and attribute agency to the participating entities even if both the entities and the signals they produce are unfamiliar to them.

Herd behavior, bubbles and social interactions in financial markets

2014 ◽  
Vol 18 (1) ◽  
Author(s):  
Sheng-Kai Chang
Keyword(s):  
Financial Markets ◽  
Social Interactions ◽  
Individual Investors ◽  
Herd Behavior ◽  
Pricing Models ◽  
Interacting Agents ◽  
Asset Pricing Models ◽  
The Social ◽  
The Relationship ◽  
Heterogeneous Interacting Agents

AbstractThis paper studies herd behavior, bubbles and social interactions in financial markets through the asset pricing models with heterogeneous interacting agents. The relationship between social interactions, herd behavior and bubbles is examined. It is found that herd behavior arises naturally when there are strong enough social interactions among individual investors. In addition, an extremely small bubble may cause a sufficiently large number of traders to engage in herd behavior when the social interactions among traders are strong.

What Does It Mean to Be Social? Defining the Social Landscape for Children With Childhood Apraxia of Speech

2020 ◽  
Vol 5 (4) ◽  
pp. 843-852 ◽  
Author(s):  
Nancy Tarshis ◽  
Michelle Garcia Winner ◽  
Pamela Crooke
Keyword(s):  
Social Development ◽  
Social Goals ◽  
Apraxia Of Speech ◽  
Childhood Apraxia Of Speech ◽  
Social Competencies ◽  
The Social ◽  
Social Landscape ◽  
Communication Challenges ◽  
Primary Focus ◽  
Speech Motor

Purpose What does it mean to be social? In addition, how is that different from behaving socially appropriately? The purpose of this clinical focus article is to tackle these two questions along with taking a deeper look into how communication challenges in childhood apraxia of speech impact social competencies for young children. Through the lens of early social development and social competency, this clinical focus article will explore how speech motor challenges can impact social development and what happens when young learners miss early opportunities to grow socially. While not the primary focus, the clinical focus article will touch upon lingering issues for individuals diagnosed with childhood apraxia of speech as they enter the school-aged years. Conclusion Finally, it will address some foundational aspects of intervention and offer ideas and suggestions for structuring therapy to address both speech and social goals.

Sign in / Sign up

Export Citation Format

Share Document