The Dynamics of Peer-to-Peer Tasks: An Agent-Based Perspective

2005 ◽  
pp. 173-184 ◽  
Author(s):  
Xiaolong Jin ◽  
Jiming Liu ◽  
Zhen Yang
Keyword(s):  
Peer To Peer ◽  
Agent Based

Agent-Based Modeling of Peer-to-Peer Energy Trading in a Smart Grid Environment

2021 ◽  
Author(s):  
Diogo V. Guimaraes ◽  
Matthew B Gough ◽  
Sergio F. Santos ◽  
Ines F.G. Reis ◽  
Juan M. Home-Ortiz ◽  
...  
Keyword(s):  
Smart Grid ◽  
Peer To Peer ◽  
Agent Based Modeling ◽  
Grid Environment ◽  
Energy Trading ◽  
Agent Based

Leveraging peer-to-peer farmer learning to facilitate better strategies in smallholder dairy husbandry

2020 ◽  
pp. 105971232097136
Author(s):  
Devotha G Nyambo ◽  
Edith T Luhanga ◽  
Zaipuna O Yonah ◽  
Fidalis DN Mujibi ◽  
Thomas Clemen
Keyword(s):  
Milk Yield ◽  
Peer Learning ◽  
Peer To Peer ◽  
Inexpensive Method ◽  
Dairy Farmers ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Farmer Groups ◽  
Using Data ◽  
New Strategies

Peer-to-peer learning paradigm is seldom used in studying how farmers can increase yield. In this article, agent-based modelling has been applied to study the chances of dairy farmers increasing annual milk yield by learning better farming strategies from each other. Two sets of strategies were considered; in one set ( S), each farmer agent would possess a number of farming strategies based on their knowledge, and in a second set [Formula: see text], farmer agents would possess farming strategies that they have adopted from their peers. Regression models were used to determine litres of milk that could be produced whenever new strategies were applied. By using data from Ethiopia and Tanzania, 28 and 25 determinants for increase in milk yield were fitted for the two countries, respectively. There was a significant increase in average milk yield as the farmer agents interacted and updated their [Formula: see text]– from baseline data, average milk yield of 12.7 ± 4.89 and 13.62 ± 4.47 to simulated milk yield average of 17.57 ± 0.72 and 20.34 ± 1.16 for Tanzania and Ethiopia, respectively. The peer-to-peer learning approach details an inexpensive method manageable by the farmers themselves. Its implementation could range from physical farmer groups to online interactions.

scholarly journals Cascades across networks are sufficient for the formation of echo chambers: An agent-based model

2020 ◽  
Author(s):  
Jan-Philipp Fränken ◽  
Toby Pilditch
Keyword(s):  
Climate Change ◽  
Social Networks ◽  
Social Network ◽  
Individual Differences ◽  
Peer To Peer ◽  
Psychological Explanation ◽  
Agent Based ◽  
Echo Chambers ◽  
Core Components ◽  
Echo Chamber

Investigating how echo chambers emerge in social networks is increasingly crucial, given their role in facilitating the retention of misinformation, inducing intolerance towards opposing views, and misleading public and political discourse (e.g., disbelief in climate change). Previously, the emergence of echo chambers has been attributed to psychological biases and inter-individual differences, requiring repeated interactions among network-users. In the present work we show that two core components of social networks—users self-select their networks, and information is shared laterally (i.e. peer-to-peer)—are causally sufficient to produce echo chambers. Crucially, we show that this requires neither special psychological explanation (e.g., bias or individual differences), nor repeated interactions—though these may be exacerbating factors. In fact, this effect is made increasingly worse the more generations of peer-to-peer transmissions it takes for information to permeate a network. This raises important questions for social network architects, if truly opposed to the increasing prevalence of deleterious societal trends that stem from echo chamber formation.

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