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Beyond goal-rationality: Traditional action can reduce volatility in socially situated agents
Abstract
Systems that pursue their own goals in shared environments can indirectly affect one another in unanticipated ways, such that the actions of other systems can interfere with goal-achievement. As humans have evolved to achieve goals despite interference from others in society, we thus endow socially situated agents with the capacity for social action as a means of mitigating interference in co-existing systems. We demonstrate that behavioural and evolutionary volatility caused by indirect interactions of goal-rational agents can be reduced by designing agents in a more socially-sensitive manner. We therefore challenge the assumption that designers of intelligent systems typically make, that goal-rationality is sufficient for achieving goals in shared environments.
... The work presented in [20] puts these mutual influences into the subsystems' social context and argues about the goal of volatility reduction. Namely, based on the observation that systems pursuing their own goals in shared environments can indirectly affect one another in unanticipated ways (having a certain impact on their trustworthiness [21]), the authors demonstrate that behavioural and evolutionary volatility caused by indirect interactions of goal-rational agents can be reduced by designing social-aware agents. ...
“Self-improving system integration” (SISSY) is a research initiative that aims to master the ever-changing demands of system organisation in the presence of highly-dynamic autonomous subsystems, evolving architectures, and unpredictable open environments. In contrast to traditional system modelling, design and development – typically performed by engineers, offline – the SISSY vision promotes automated integration-related decisions, performed during run-time. This implies a change of responsibilities, from engineers to the system itself, which must now find ways to restructure and reassemble itself so as to achieve its objectives. In addition to self-integrating and self-improving internally, such systems must equally be able to cooperate or co-exist with other autonomous systems, which may dynamically join a shared environment. In this editorial, we briefly introduce the ‘self-improving system integration’ initiative and summarise the contents of this special issue.
... Composed of many components of interaction, where humans are responsible for making decisions and delegating action to intelligent machines (Barnes et al., 2020). way to manage quality within the Industry also needs to adapt and follow these changes, that is, make intelligent use of all these available technologies to optimize how quality is monitored by the people who are part of the organization. ...
The purpose of this article is to explore the new concept of TQM 4.0 as a way of adapting quality management (QM) in Industry 4.0 (I4.0), guiding industries to this new phase, which has generated adaptations in numerous areas, one of which is QM and human resources.
A systematic review of the literature was carried out. Methodi Ordinatio was applied to build the portfolio of articles with scientific relevance, which is the source of data collections and content analysis. To help out in the analysis, NVivo 12 and VOSviewer software programs were used.
The results demonstrate that when adapting the QM to the technologies of I4.0, the result is an ecosystem that supports the integration between technology, quality and people in the industrial scenario.
This article presents a systematic review of the literature, but without delving into specific issues such as the different industrial sectors and the culture of countries in which industries may be inserted, for example, which characterizes a limitation of this research.
This study provides an ecosystem model that can guide future research, regarding the concept of TQM 4.0, in addition to pointing out some ways of combining technologies, quality and people in the industrial context.
This is one of the first articles to employ a systematic review of the literature using Methodi Ordinatio to build a bibliographic panorama on the intertwining of the themes total QM (TQM) and I4.0, focusing on the emerging concept of TQM 4.0.
Neural networks have been widely used in agent learning architectures; however, learnings for one task might nullify learnings for another. Behavioural plasticity enables humans and animals alike to respond to environmental changes without degrading learned knowledge; this can be achieved by regulating behaviour with neuromodulation—a biological process found in the brain. We demonstrate that by modulating activity-propagating signals, neurally trained agents evolving to solve tasks in dynamic environments that are prone to change can expect a significantly higher fitness than non-modulatory agents and also achieve their goals more often. Further, we show that while behavioural plasticity can help agents to achieve goals in these variable environments, this ability to overcome environmental changes with greater success comes at the cost of highly volatile evolution.
Two systems pursuing their own goals in a shared world can interact in ways that are not so explicit-such that the presence of another system alone can interfere with how one is able to achieve its own goals. Drawing inspiration from human psychology and the theory of social action, we propose the notion of employing social action in socially situated agents as a means of alleviating interference in interacting systems. Here we demonstrate that these specific issues of behavioural and evolutionary instability caused by the unintended consequences of interactions can be addressed with agents capable of a fusion of goal-rationality and traditional action, resulting in a stable society capable of achieving goals during the course of evolution.
In the last few million years, the hominin brain more than tripled in size. Comparisons across evolutionary lineages suggest that this expansion may be part of a broader trend toward larger, more complex brains in many taxa. Efforts to understand the evolutionary forces driving brain expansion have focused on climatic, ecological, and social factors. Here, building on existing research on learning, we analytically and computationally model the predictions of two closely related hypotheses: The Cultural Brain Hypothesis and the Cumulative Cultural Brain Hypothesis. The Cultural Brain Hypothesis posits that brains have been selected for their ability to store and manage information, acquired through asocial or social learning. The model of the Cultural Brain Hypothesis reveals relationships between brain size, group size, innovation, social learning, mating structures, and the length of the juvenile period that are supported by the existing empirical literature. From this model, we derive a set of predictions—the Cumulative Cultural Brain Hypothesis—for the conditions that favor an autocatalytic take-off characteristic of human evolution. This narrow evolutionary pathway, created by cumulative cultural evolution, may help explain the rapid expansion of human brains and other aspects of our species’ life history and psychology.
This section presents the third volume of Max Weber's fundamental work Economy and Society which has been translated into Russian for the first time. The third volume includes two works devoted to the sociology of law. The first, 'The Economy and Laws', discusses differences between sociological and juridical approaches to studies of social processes. It describes peculiarities of normative power arenas (orders) at different levels and demonstrates how they influence the economy. The second, 'Economy and Law' ('Sociology of Law'), reviews the evolution of law orders (primarily, the three "greatest systems of law" including Roman Law, Anglo-American Law, and European Continental Law) in the context of changes in the organization of economy and structures of dominancy. Law is considered an influential factor of the rationalization of social life which in turn is affected by a rationalized economy and social management. The Journal of Economic Sociology here publishes an excerpt from the chapter 'Law, Convention and Custom' in this third volume, which shows the role of the habitual in the formation of law; explains the importance of intuition and empathy for the emergence of new orders; and discusses the changeable borders between law, convention and custom. The translation is edited by Leonid Ionin and the chapter is published with the permission of HSE Publishing House. © 2018 National Research University Higher School of Economics. All rights reserved.
In human society, individuals have long voluntarily organized themselves in groups, which embody, provide and/or facilitate a range of different social concepts, such as governance, justice, or mutual aid. These social groups vary in form, size, and permanence, but in different ways provide benefits to their members. In turn, members of these groups use their understanding and awareness of group expectations to help determine their own actions, to the benefit of themselves, each other, and the health of the group.