Trade-off between learning and exploitation: The Pareto-optimal versus evolutionarily stable learning schedule in cumulative cultural evolution

2014 ◽  
Vol 91 ◽  
pp. 37-43 ◽  
Author(s):  
Joe Yuichiro Wakano ◽  
Chiaki Miura
Keyword(s):  
Cultural Evolution ◽  
Pareto Optimal ◽  
Trade Off ◽  
Cumulative Cultural Evolution ◽  
Stable Learning ◽  
Evolutionarily Stable

Multiobjective optimization of the flaxseed mucilage extraction process using normal-boundary intersection approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mariana Souza Rocha ◽  
Luiz Célio Souza Rocha ◽  
Marcia Barreto da Silva Feijó ◽  
Paula Luiza Limongi dos Santos Marotta ◽  
Samanta Cardozo Mourão
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Method ◽  
Extraction Process ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Fiber Concentration ◽  
Trade Off ◽  
Content Type ◽  
Normal Boundary

PurposeThe mucilage of the Linum usitatissimum L. seed (Linseed) is one of the natural mucilages that presents a great potential to provide a food hydrocolloid with potential applications in both food and pharmaceutical industries. To increase the yield and quality of linseed oil during its production process, it is necessary to previously extract its polysaccharides. Because of this, flax mucilage production can be made viable as a byproduct of oil extraction process, which is already a product of high commercial value consolidated in the market. Thus, the purpose of this work is to optimize the mucilage extraction process of L. usitatissimum L. using the normal-boundary intersection (NBI) multiobjective optimization method.Design/methodology/approachCurrently, the variables of the process of polysaccharide extraction from different sources are optimized using the response surface methodology. However, when the optimal points of the responses are conflicting it is necessary to study the best conditions to achieve a balance between these conflicting objectives (trade-offs) and to explore the available options it is necessary to formulate an optimization problem with multiple objectives. The multiobjective optimization method used in this work was the NBI developed to find uniformly distributed and continuous Pareto optimal solutions for a nonlinear multiobjective problem.FindingsThe optimum extraction point to obtain the maximum fiber concentration in the extracted material was pH 3.81, temperature of 46°C, time of 13.46 h. The maximum extraction yield of flaxseed was pH 6.45, temperature of 65°C, time of 14.41 h. This result confirms the trade-off relationship between the objectives. NBI approach was able to find uniformly distributed Pareto optimal solutions, which allows to analyze the behavior of the trade-off relationship. Thus, the decision-maker can set extraction conditions to achieve desired characteristics in mucilage.Originality/valueThe novelty of this paper is to confirm the existence of a trade-off relationship between the productivity parameter (yield) and the quality parameter (fiber concentration in the extracted material) during the flaxseed mucilage extraction process. The NBI approach was able to find uniformly distributed Pareto optimal solutions, which allows us to analyze the behavior of the trade-off relationship. This allows the decision-making to the extraction conditions according to the desired characteristics of the final product, thus being able to direct the extraction for the best applicability of the mucilage.

Copy the In-group: Group Membership Trumps Perceived Reliability, Warmth, and Competence in a Social-Learning Task

2021 ◽  
pp. 095679762110322
Author(s):  
Marcel Montrey ◽  
Thomas R. Shultz
Keyword(s):  
Social Learning ◽  
Cultural Evolution ◽  
Learning Strategy ◽  
Group Membership ◽  
Social Groups ◽  
Learning Task ◽  
Minimal Group Paradigm ◽  
Learning Game ◽  
Group Members ◽  
Cumulative Cultural Evolution

Surprisingly little is known about how social groups influence social learning. Although several studies have shown that people prefer to copy in-group members, these studies have failed to resolve whether group membership genuinely affects who is copied or whether group membership merely correlates with other known factors, such as similarity and familiarity. Using the minimal-group paradigm, we disentangled these effects in an online social-learning game. In a sample of 540 adults, we found a robust in-group-copying bias that (a) was bolstered by a preference for observing in-group members; (b) overrode perceived reliability, warmth, and competence; (c) grew stronger when social information was scarce; and (d) even caused cultural divergence between intermixed groups. These results suggest that people genuinely employ a copy-the-in-group social-learning strategy, which could help explain how inefficient behaviors spread through social learning and how humans maintain the cultural diversity needed for cumulative cultural evolution.

scholarly journals Understanding cumulative cultural evolution

2016 ◽  
Vol 113 (44) ◽  
pp. E6724-E6725 ◽  
Author(s):  
Joseph Henrich ◽  
Robert Boyd ◽  
Maxime Derex ◽  
Michelle A. Kline ◽  
Alex Mesoudi ◽  
...  
Keyword(s):  
Cultural Evolution ◽  
Cumulative Cultural Evolution

scholarly journals Analisis Perbandingan Aggregat Of Function (AOF) dengan Non-Dominated Sorting Genetic Algorithm (NSGA-II) dalam Menentukan Optimasi Multi-Objective pada Penjadwalan Mesin Produksi Flow Shop

2018 ◽  
Vol 17 (2) ◽  
pp. 158
Author(s):  
Fifin Sonata ◽  
Dede Prabowo Wiguna
Keyword(s):  
Genetic Algorithm ◽  
Flow Shop ◽  
Total Tardiness ◽  
Pareto Optimal ◽  
Nsga Ii ◽  
Trade Off ◽  
Multi Objective

Penjadwalan mesin produksi dalam dunia industri memiliki peranan penting sebagai bentuk pengambilan keputusan. Salah satu jenis sistem penjadwalan mesin produksi adalah sistem penjadwalan mesin produksi tipe flow shop. Dalam penjadwalan flow shop, terdapat sejumlah pekerjaan (job) yang tiap-tiap job memiliki urutan pekerjaan mesin yang sama. Optimasi penjadwalan mesin produksi flow shop berkaitan dengan penyusunan penjadwalan mesin yang mempertimbangkan 2 objek yaitu makespan dan total tardiness. Optimasi kedua permasalahan tersebut merupakan optimasi yang bertolak belakang sehingga diperlukan model yang mengintegrasikan permasalahan tersebut dengan optimasi multi-objective A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimazitaion : NSGA-II. Dalam penelitian ini akan dibandingkan 2 buah metode yaitu Aggregat Of Function (AOF) dengan NSGA-II agar dapat terlihat nilai solusinya. Penyelesaian penjadwalan mesin produksi flow shop dengan algoritma NSGA-II untuk membangun jadwal dengan meminimalkan makespan dan total tardiness.Tujuan yang ingin dicapai adalah mengetahui bahwa model yang dikembangkan akan memberikan solusi penjadwalan mesin produksi flow shop yang efisien berupa solusi pareto optimal yang dapat memberikan sekumpulan solusi alternatif bagi pengambil keputusan dalam membuat penjadwalan mesin produksi yang diharapkan. Solusi pareto optimal yang dihasilkan merupakan solusi optimasi multi-objective yang optimal dengan trade-off terhadap seluruh objek, sehingga seluruh solusi pareto optimal sama baiknya.

scholarly journals Cultural accumulation and improvement in online fan fiction

2020 ◽  
Author(s):  
Federico Pianzola ◽  
Alberto Acerbi ◽  
Simone Rebora
Keyword(s):  
Digital Media ◽  
Cultural Evolution ◽  
Harry Potter ◽  
Fan Fiction ◽  
Cumulative Culture ◽  
Cultural Systems ◽  
Cultural Traits ◽  
Cumulative Cultural Evolution ◽  
Cultural Evolution Theory ◽  
Digital Literary Studies

We analyse stories in Harry Potter fan fiction published on Archive of Our Own (AO3), using concepts from cultural evolution. In particular, we focus on cumulative cultural evolution, that is, the idea that cultural systems improve with time, drawing on previous innovations. In this study we examine two features of cumulative culture: accumulation and improvement. First, we show that stories in Harry Potter’s fan fiction accumulate cultural traits—unique tags, in our analysis—through time, both globally and at the level of single stories. Second, more recent stories are also liked more by readers than earlier stories. Our research illustrates the potential of the combination of cultural evolution theory and digital literary studies, and it paves the way for the study of the effects of online digital media on cultural cumulation.

Cumulation

2019 ◽  
pp. 186-212
Author(s):  
Alberto Acerbi
Keyword(s):  
Digital Media ◽  
Cultural Evolution ◽  
Cultural Selection ◽  
Cultural Domain ◽  
Cumulative Cultural Evolution ◽  
Efficient Mechanisms

Chapter 8 considers what cultural evolutionists call cumulative cultural evolution, that is, the idea that culture increases in complexity. For a cultural domain being defined as cumulative, it needs to show accumulation (more traits), improvement (traits are more efficient), and ratcheting (new traits build on previous innovations). The author proposes that this is not a necessary outcome, and that different domains show different signs of cumulation. It is suggested that the fidelity and the hyper-availability provided by digital media allow for more cumulation in domains where it was limited before. Not surprisingly, they also allow for the retention of vast amounts of useless information—junk culture. A central challenge for the coming years is thus finding efficient mechanisms of online cultural selection. Algorithmic selection is finally discussed, along with how mainstream criticisms, such as the fact that algorithms are biased or opaque to users, are not decisive arguments against their efficacy and utility.

scholarly journals Robustness, Sensitivity, and Sampling Variability of Pareto-Optimal Selection System Solutions to Address the Quality-Diversity Trade-Off

2019 ◽  
Vol 23 (3) ◽  
pp. 535-568
Author(s):  
Wilfried De Corte ◽  
Paul R. Sackett ◽  
Filip Lievens
Keyword(s):  
Simulation Study ◽  
Critical Issue ◽  
Pareto Optimal ◽  
Optimal Selection ◽  
Selection System ◽  
Trade Off ◽  
Sampling Variability ◽  
Optimal Balance ◽  
Selection Systems ◽  
System Designs

In case that both the goals of selection quality and diversity are important, a selection system is Pareto-optimal (PO) when its implementation is expected to result in an optimal balance between the levels achieved with respect to both these goals. The study addresses the critical issue whether PO systems, as computed from calibration conditions, continue to perform well when applied to a large variety of different validation selection situations. To address the key issue, we introduce two new measures for gauging the achievement of these designs and conduct a large simulation study in which we manipulate 10 factors (related to the selection situation, sensitivity/robustness, and the selection system) that cumulate in a design with 3,888 cells and 24 selection systems. Results demonstrate that PO systems are superior to other, non-PO systems (including unit weighed system designs) both in terms of the achievement measures as well as in terms of yielding more often a better quality/diversity trade-off. The study also identifies a number of conditions that favor the achievement of PO systems in realistic selection situations.

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