scholarly journals Cognitive agency in sociocultural evolution

2022 ◽  
Author(s):  
Avel GUÉNIN--CARLUT

Models of sociocultural evolution generally study the population dynamics of cultural traits given known biases in social learning. Cognitive agency, understood as the dynamics underlying a specific agent’s adoption of a given trait, is essentially irrelevant in this framework. This article argues that although implementing and instrumenting agency in computational models is fundamentally challenging, it is ultimately possible and would help us overcome major limitations in our understanding of sociocultural dynamics.Indeed, the behaviour of humans is not causally generated by a set of predefined behavioural laws, but by the situated activity of their cognitive architecture. Idealised models of biased transmission certainly help us understand specific features of population dynamics. However, they distract us from the deep intrication of the cognitive and ecological processes underlying sociocultural evolution, and erase their embodied, subjective nature.In line with the earlier “Thinking Through Other Minds” account of sociocultural evolution, this article highlights how the Active Inference framework can help us implement and instrument computational models that address these limitations. Such models would not only help ground our understanding of sociocultural evolution in the underlying cognitive dynamics, but also help solve (or frame) open questions in the study of ritual, relation between cultural transmission and innovation, as well as scales of cultural evolution.

Author(s):  
Alireza Soltani ◽  
Etienne Koechlin

AbstractThe real world is uncertain, and while ever changing, it constantly presents itself in terms of new sets of behavioral options. To attain the flexibility required to tackle these challenges successfully, most mammalian brains are equipped with certain computational abilities that rely on the prefrontal cortex (PFC). By examining learning in terms of internal models associating stimuli, actions, and outcomes, we argue here that adaptive behavior relies on specific interactions between multiple systems including: (1) selective models learning stimulus–action associations through rewards; (2) predictive models learning stimulus- and/or action–outcome associations through statistical inferences anticipating behavioral outcomes; and (3) contextual models learning external cues associated with latent states of the environment. Critically, the PFC combines these internal models by forming task sets to drive behavior and, moreover, constantly evaluates the reliability of actor task sets in predicting external contingencies to switch between task sets or create new ones. We review different models of adaptive behavior to demonstrate how their components map onto this unifying framework and specific PFC regions. Finally, we discuss how our framework may help to better understand the neural computations and the cognitive architecture of PFC regions guiding adaptive behavior.


2016 ◽  
Vol 78 (5) ◽  
pp. 396-403 ◽  
Author(s):  
Samuel Potter ◽  
Rebecca M. Krall ◽  
Susan Mayo ◽  
Diane Johnson ◽  
Kim Zeidler-Watters ◽  
...  

With the looming global population crisis, it is more important now than ever that students understand what factors influence population dynamics. We present three learning modules with authentic, student-centered investigations that explore rates of population growth and the importance of resources. These interdisciplinary modules integrate biology, mathematics, and computer-literacy concepts aligned with the Next Generation Science Standards. The activities are appropriate for middle and high school science classes and for introductory college-level biology courses. The modules incorporate experimentation, data collection and analysis, drawing conclusions, and application of studied principles to explore factors affecting population dynamics in fruit flies. The variables explored include initial population structure, food availability, and space of the enclosed population. In addition, we present a computational simulation in which students can alter the same variables explored in the live experimental modules to test predictions on the consequences of altering the variables. Free web-based graphing (Joinpoint) and simulation software (NetLogo) allows students to work at home or at school.


Author(s):  
Sergio Castellanos ◽  
Luis-Felipe Rodríguez ◽  
J. Octavio Gutierrez-Garcia

Autonomous agents (AAs) are capable of evaluating their environment from an emotional perspective by implementing computational models of emotions (CMEs) in their architecture. A major challenge for CMEs is to integrate the cognitive information projected from the components included in the AA's architecture. In this chapter, a scheme for modulating emotional stimuli using appraisal dimensions is proposed. In particular, the proposed scheme models the influence of cognition on appraisal dimensions by modifying the limits of fuzzy membership functions associated with each dimension. The computational scheme is designed to facilitate, through input and output interfaces, the development of CMEs capable of interacting with cognitive components implemented in a given cognitive architecture of AAs. A proof of concept based on real-world data to provide empirical evidence that indicates that the proposed mechanism can properly modulate the emotional process is carried out.


Author(s):  
Alberto Acerbi

This chapter takes a broad view of misinformation: the spread of factually false claims is as old as cultural transmission itself, and to assess the real danger represented by social media we need to understand what kind of cognitive triggers are activated by successful information, online or offline. The chapter critically reviews some hypotheses for which digital media are especially suited for the spreading of misinformation, and then it explores in detail the idea that some cultural traits possess features that make them particularly well suited to be retained and transmitted, conferring on them a selective advantage relative to other traits. From this perspective, misinformation can be manufactured building on features that make it attractive in an almost unconstrained way, whereas true news cannot, simply because it needs to correspond to reality. Misinformation can be designed to spread more than real information does,—whether this is consciously planned or not.


Author(s):  
Daniel Oro

Sociality appears in many life histories during evolution. Some eusocial bees show evolutionary reversions to solitary behaviour, and populations of the same species can be solitary or social, likely depending on local environmental features. Social species need a minimum size to perform adaptive behaviours, such as the search for resources, which is crucial especially under perturbations. This minimum size may become a threshold, setting a phase transition for separating two stable states, from disorganized and maladaptive to organized and adaptive, which also shows hysteresis. The chapter also explores evolution via facilitation or cooperation (e.g. social information) under the theoretical framework of multilevel selection, by which there is likely an effect of the social group’s genes on individual fitness. Perturbations appear as a strong source of evolutionary processes. In humans, warfare acts as a very powerful selective pressure for competition between groups and thus for cooperation. Sociality has also many costs, such as a higher risk for the spread of infectious disease, the appearance of traps by social haunting philopatry, stronger aggression and competition, and a higher risk of being attacked by predators. Finally, the evolution of cultures is explored; optimization of social learning, social copying, and cultural transmission may have nonlinear consequences for population dynamics.


Author(s):  
Volkan Ustun ◽  
Paul S. Rosenbloom

Realism is required not only for how synthetic characters look but also for how they behave. Many applications, such as simulations, virtual worlds, and video games, require computational models of intelligence that generate realistic and credible behavior for the participating synthetic characters. Sigma (S) is being built as a computational model of general intelligence with a long-term goal of understanding and replicating the architecture of the mind; i.e., the fixed structure underlying intelligent behavior. Sigma leverages probabilistic graphical models towards a uniform grand unification of not only traditional cognitive capabilities but also key non-cognitive aspects, creating unique opportunities for the construction of new kinds of non-modular behavioral models. These ambitions strive for the complete control of synthetic characters that behave as humanly as possible. In this paper, Sigma is introduced along with two disparate proof-of-concept virtual humans – one conversational and the other a pair of ambulatory agents – that demonstrate its diverse capabilities.


2020 ◽  
Vol 71 (1) ◽  
pp. 107-138 ◽  
Author(s):  
Michael J. Kahana

The capacity to search memory for events learned in a particular context stands as one of the most remarkable feats of the human brain. How is memory search accomplished? First, I review the central ideas investigated by theorists developing models of memory. Then, I review select benchmark findings concerning memory search and analyze two influential computational approaches to modeling memory search: dual-store theory and retrieved context theory. Finally, I discuss the key theoretical ideas that have emerged from these modeling studies and the open questions that need to be answered by future research.


2006 ◽  
Vol 29 (4) ◽  
pp. 357-358
Author(s):  
R. Lee Lyman

Modern efforts to model cultural transmission have struggled to identify a unit of cultural transmission and particular transmission processes. Anthropologists of the early twentieth century discussed cultural traits as units of transmission equivalent to recipes (rules and ingredients) and identified integration as a signature process and effect of transmission.


2001 ◽  
Vol 1 (3) ◽  
pp. 251-258 ◽  
Author(s):  
William Michael Brown

AbstractGenomic imprinting may be implicated in the origin and maintenance of the cognitive architecture required for cultural transmission. Relatedness asymmetries are expected to lead to increases in the receptibility of matrilineally transmitted information. This may help explain why maternal genes contribute preferentially to the neocortex. That is, maternal genes could influence biases in the transmission and/or acquisition of information. This perspective is complementary to gene-culture coevolutionary approaches.


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