Meta-control of social learning strategies

Yaman, Anil; Bredèche, Nicolas; Çaylak, Onur; Leibo, Joel Z.; Lee, Sang Wan

doi:10.1371/journal.pcbi.1009882

Cited by 3 publications

(4 citation statements)

References 62 publications

(112 reference statements)

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“…Most evolutionary game theory-based models share a common assumption that individuals make one choice and stick with it throughout their lives [ 53 ]. Others model the evolution and spread of successful strategies [ 54 , 55 ] through social learning over a population of individuals. By contrast, the cultural evolutionary process in our model operates on the social norm level.…”

Section: Discussionmentioning

confidence: 99%

The emergence of division of labour through decentralized social sanctioning

Yaman,

Leibo,

Iacca

et al. 2023

Proc. R. Soc. B.

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Human ecological success relies on our characteristic ability to flexibly self-organize into cooperative social groups, the most successful of which employ substantial specialization and division of labour. Unlike most other animals, humans learn by trial and error during their lives what role to take on. However, when some critical roles are more attractive than others, and individuals are self-interested, then there is a social dilemma: each individual would prefer others take on the critical but unremunerative roles so they may remain free to take one that pays better. But disaster occurs if all act thus and a critical role goes unfilled. In such situations learning an optimum role distribution may not be possible. Consequently, a fundamental question is: how can division of labour emerge in groups of self-interested lifetime-learning individuals? Here, we show that by introducing a model of social norms, which we regard as emergent patterns of decentralized social sanctioning, it becomes possible for groups of self-interested individuals to learn a productive division of labour involving all critical roles. Such social norms work by redistributing rewards within the population to disincentivize antisocial roles while incentivizing prosocial roles that do not intrinsically pay as well as others.

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Section: Discussionmentioning

confidence: 99%

The emergence of division of labour through decentralized social sanctioning

Yaman,

Leibo,

Iacca

et al. 2023

Proc. R. Soc. B.

Self Cite

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“…Interview at Sekolah Menengah Pertama (SMP) Negeri I Tobelo was done with headmaster and head of curricullum section. Recapitulation at 10 September 2022, there are 1107 students [6,7] with 3 (three) teacher with information and communication technolgy (ICT) background. This school are lucky while they have three teachers with ICT background, two of them graduated from my institution, Universitas Negeri Manado.…”

Section: Methodsmentioning

confidence: 99%

Optimizing the Digital Education Technology in Learning Management System Design During and Post-Covid-19 Pandemic in Society 5.0

Kenap¹,

Kembuan²,

Usoh³

et al. 2023

Proceedings of the Unima International Conference on Social Sciences and Humanities (UNICSSH 2022)

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The use of digital devices has increased since the global pandemic was officially declared by the world health agency on March 11, 2020. The increase in the use of digital devices is marked by an increase in internet use by up to 40% where virtual services and activities are urgently needed during the Covid-19 pandemic. The community's economic is also affected by the pandemic, but on the other hand all needs must be fulfill including the use of digital devices, smartphones which have become ubiquitios in the current digital era. Basic knowledge of the use of digital devices is needed to maximize the use of digital devices in daily use. Digital devices such as mobile phones, tablets, laptops, personal computers became ubiqutos in a short time which also became part of the technology driven force. As ubiquitos in life, the current digital device of society must be optimized than change with new one while the impact of pandemic affect the economic's society. In this case, the society 5.0 define that human and technolgy will live side by side to improve the human life quality on sustainable based. The specifications of the processor, memory, input and output devices, data transmission technology in terms of hardware, software updates used need to be understood including developments and updates of devices that needed, so all digital activities can run well. This digital interaction occurs in almost all human life activities, include the essensial sector like education, health, work, business, banking, shopping and many more.To fulfill the need for using digital devices in the pandemic era, analyzes the needs and specifications for usage requirements, including interactions the using of icon on digital devices, especially in education interaction. Learning management need to apply at all level of education during the complex obstacles such as digital devides, human resources that related to computer and internet literacy. The optimization use of digital device could give many advantages to community, especially in education as one of priority target. During and post covid-19 pandemic, education could be one of the best way to recover the community health and prepare entering the new normal which many field dominated by digitalization.

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“…In a recent work, the performance of success-based social learning strategies versus conformity in different levels of environmental volatility and uncertainty was investigated [11]. They also developed a meta-control of individual and social learning strategies that affords agents the leverage to resolve environmental uncertainty with minimal exploration cost, by exploiting others' learning as an external knowledge base.…”

Section: Related Workmentioning

confidence: 99%

“…The agents independently pursue their own rewards without any direct incentive to teach one another, and we make no assumptions about their expertise or the relevance of their policy to our SA's task. Therefore, in absence of any social evaluations and norms [11] and due to reward privacy, the SA should mainly evaluate other agents' relevance as well as the levels and scope of their expertise based on a self-referenced evaluation.…”

Section: Introductionmentioning

confidence: 99%

Exploiting Expertise of Non-Expert and Diverse Agents in Social Bandit Learning: A Free Energy Approach

Mirzaei,

Tavakoli,

Shariatpanahi

et al. 2024

Preprint

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Personalized AI-based services involve a population of individual reinforcement learning agents. However, most reinforcement learning algorithms focus on harnessing individual learning and fail to leverage the social learning capabilities commonly exhibited by humans and animals. Social learning integrates individual experience with observing others’ behavior, presenting opportunities for improved learning outcomes. In this study, we focus on a social bandit learning scenario where a social agent observes other agents’ actions without knowledge of their rewards. The agents independently pursue their own rewards without any explicit motivation for teaching one another. We propose a free energy-based social bandit learning algorithm over policy space, where the social agent evaluates others’ expertise levels without resorting to any oracle or social norms. Accordingly, the social agent integrates its direct experiences in the environment and others’ estimated policies. The theoretical convergence of our algorithm to the optimal policy is proven. Empirical evaluations validate the superiority of our social learning method over alternative approaches in diverse scenarios. Our algorithm strategically identifies the relevant agents, even in the presence of random or sub-optimal agents, and skillfully exploiters their behavioral information. Extra to societies including expert agents, in the presence of relevant but non-expert agents, our algorithm significantly enhances individual learning performance, where most related methods fail. Importantly, it maintains logarithmic regret.

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Meta-control of social learning strategies

Cited by 3 publications

References 62 publications

The emergence of division of labour through decentralized social sanctioning

The emergence of division of labour through decentralized social sanctioning

Optimizing the Digital Education Technology in Learning Management System Design During and Post-Covid-19 Pandemic in Society 5.0

Exploiting Expertise of Non-Expert and Diverse Agents in Social Bandit Learning: A Free Energy Approach

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