[October 3, 2021: University of Groningen]
These are Dr. Mengbin Ye (current position Senior Research Fellow at Curtin University in Australia) and Ming Cao, Professor of Networks and Robotics at the Faculty of Science and Engineering at the University of Groningen, the Netherlands. (Credit: Curtin University / University of Groningen)
How does complex human behaviour take shape? This is studied in many ways, mostly relying on lots of data from observations and experiments. Ming Cao, Professor of Networks and Robotics at the Faculty of Science and Engineering at the University of Groningen, has studied complex group behaviour in robots by using agent-based simulations, among other methods. These agents follow a limited number of simple rules, often inspired by nature, which can lead to realistic complex behaviour. ‘Swarming birds or schools of fish are a good example’, Cao explains, ‘their movements can be reproduced by agents that follow a few simple rules on keeping a certain distance and heading in the same direction as their neighbours.’
In parallel, the Marketing research group at the Faculty of Economics and Business, led by Dr Jan Willem Bolderdijk, Dr Hans Risselada, and Prof. Bob Fennis, has carried out various research projects into human behaviour, but not so many using these kinds of agent-based models. After a discussion with Cao and his colleagues, both groups saw possibilities for such models. Consequently, marketing PhD student Zan Mlakar and the two post-doc researchers in Cao’s group, Mengbin Ye and Lorenzo Zino, worked together creating an online experiment to gather data on the social diffusion of new behavioural trends.
They developed an online game in which 12 participants act as board members of a company that plans to launch one of two potential products. The participants have to vote on which product to launch. The catch is that the decision has to be taken unanimously. The participants cannot discuss their choice, they vote in 24 consecutive rounds, and they only see the distribution of votes at the end of each round. If unanimity is reached, the participants receive a reward.
Unknown to the participants, between two to four participants in the groups studied were computer bots, programmed to stick to their choice. ‘If the majority voted for product A in the first round, the bots were set to vote for B to try and overturn the majority’, explains Ye, who now works as Senior Research Fellow at Curtin University in Australia. Meanwhile, the votes of the human participants over all the rounds studied were registered. The vast majority of over 20 of these online game rounds resulted in a unanimous vote, with humans eventually siding with the bots to vote for product B. The results of all the games were then analysed to look for patterns in the voting decisions of the human participants.
Ye: ‘In quite few cases, we saw a delay before the votes started changing, but when they did, the group would reach unanimity in just a few voting rounds.’ The overall voting behaviour was able to be reproduced in an agent-based model with three simple rules: do as the majority does, stick to your previous decision, and follow the trend. ‘These rules are acknowledged in the literature as group coordination, inertia, and trend-seeking’, explains Ye. ‘They have been separately studied in human behaviour, but never combined in one model; this combination was critical in capturing social change.’
The results of the experiments and the simulations show that new conventions can suddenly arise when the influence of a committed minority reaches a threshold. A small group of ‘activists’ can therefore change social conventions. Cao: ‘However, this only happens if the minority is also able to influence others in their network. And this depends on the amount of risk-taking present among the other voters.’ The team are now interested in exploring what might enhance or inhibit this risk-taking behaviour. ‘We now have a solid framework and a model, which can be used to examine environmental factors that might make people have greater inertia, or be more susceptible to trends’, says Ye.
The three basic rules could help in steering the behaviour of large groups. ‘Of course, we can’t control people’, stresses Cao. ‘But we can provide guidelines, for example on how to nudge people to change their behaviour.’ This could be useful in the energy transition, or in getting people to reduce their meat consumption. ‘Governments already spend money to convince people to adopt more sustainable behaviour. Our research can help them to spend it in a more effective way.’
For more science stories check out our New Discoveries section at The Brighter Side of News.
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"Mwanzoni mwa mwaka huu, Dr. Meng Bin Ye, Mtafiti Mkuu wa Chuo Kikuu cha Curtin huko Australia, na Ming Cao, Profesa wa Mitandao na Robotics katika Chuo Kikuu cha Sayansi na Uhandisi cha Chuo Kikuu cha Groningen, Uholanzi, walijumuisha ""mfano wa teknolojia.""" (Curtin University, Groningen) Utendaji wa binadamu tata hufanyizwaje? Hii inachunguzwa kwa njia nyingi, hasa kwa kutegemea data nyingi kutoka kwa uchunguzi na majaribio. Cao Ming, profesa wa mitandao na roboti katika Chuo Kikuu cha Groningen, amesoma tabia tata ya kikundi katika roboti kwa kutumia mfano wa wakala, kati ya mbinu zingine. Wakala hawa kufuata idadi ndogo ya sheria rahisi, mara nyingi aliongoza na asili, ambayo inaweza kusababisha tabia ya kweli tata. "Kama vile, ""Mgambo ya ndege au samaki ni mfano mzuri,"" anaeleza Cao, ""mabadiliko yao yanaweza kuzalishwa na waendeshaji ambao hufuata sheria chache rahisi za kuweka umbali fulani na kuelekea upande mmoja na majirani zao.""Kwa upande mwingine, kikundi cha utafiti wa uuzaji katika Kitivo cha Uchumi na Biashara, kilichoongozwa na Dk Jan Willem-Bolderdijk, Dk Hans Risselaer na Profesa Bob Fenniss, kimefanya miradi mbalimbali ya utafiti juu ya tabia ya binadamu." Baada ya majadiliano na Cao na wenzake, vikundi vyote viwili viliona uwezekano wa mifano kama hiyo. Kwa hivyo, mwanafunzi wa PhD wa uuzaji Zan Mlakar na watafiti wawili wa baada ya PhD katika kikundi cha Cao, Meng Bin Ye na Lorenzo Zino, walifanya kazi pamoja kuunda jaribio la mtandaoni kukusanya data juu ya kuenea kwa kijamii kwa mwenendo mpya wa tabia. Mchezo wa mtandaoni unaojumuisha washiriki 12 wanaofanya kazi kama wanachama wa bodi ya kampuni ambayo inapanga kuzindua moja ya bidhaa mbili zinazowezekana. Washiriki wanapaswa kupiga kura juu ya bidhaa gani ya kuzindua. Tatizo ni kwamba uamuzi lazima uchukuliwe kwa umoja. Washiriki hawawezi kujadili uchaguzi wao, wao kupiga kura katika raundi 24 mfululizo, na wao tu kuona usambazaji wa kura mwishoni mwa kila raundi. Ikiwa makubaliano yamefikiwa, washiriki hupokea thawabu. Haijulikani kwa washiriki, kati ya washiriki wawili hadi wanne katika vikundi vilivyochunguzwa walikuwa roboti za kompyuta, zilizopangwa kushikamana na chaguo lao. "Ikiwa wengi walipiga kura kwa bidhaa A katika raundi ya kwanza, roboti ziliwekwa kupiga kura kwa B kujaribu kuondoa wengi, ""anaeleza Ye, ambaye sasa anafanya kazi kama Mtafiti Mkuu katika Chuo Kikuu cha Curtin nchini Australia." Wakati huohuo, kura za washiriki wa kibinadamu katika raundi zote zilizochunguzwa zilirekodiwa. Katika zaidi ya raundi 20 za mchezo huu wa mtandaoni, watu walipiga kura kwa umoja, na hatimaye wanadamu waliunga mkono roboti kupiga kura kwa bidhaa B. Matokeo ya michezo yote yalichambuliwa ili kutafuta mifumo katika maamuzi ya kupiga kura ya washiriki wa kibinadamu. """Katika visa vichache, tuliona kucheleweshwa kabla ya kura kuanza kubadilika, lakini wakati walipofanya hivyo, kikundi hicho kilikuwa na umoja katika raundi chache tu za kupiga kura,"" alisema Ye, ambaye pia ni mwanzilishi wa kikundi cha watazamaji wa maoni, akisema: ""Fanya kama wengi hufanya, shikilia uamuzi wako wa awali, na fuata mwelekeo.""" <unk>Sheria hizi zinatambuliwa katika fasihi kama uratibu wa kikundi, inertia, na kutafuta mwelekeo<unk>, anaelezea Ye. "Hizi zimekuwa kuchunguzwa kando katika tabia ya binadamu, lakini kamwe pamoja katika mfano mmoja; mchanganyiko huu ilikuwa muhimu katika kukamata mabadiliko ya kijamii. "" Matokeo ya majaribio na simulations kuonyesha kwamba mikataba mpya inaweza ghafla kutokea wakati ushawishi wa wachache kujitolea kufikia kizingiti." Kwa hiyo kikundi kidogo cha "wafanya kazi" wanaweza kubadilisha mikataba ya kijamii. Cao: ‘Hata hivyo, hii hutokea tu kama wachache pia ni uwezo wa kushawishi wengine katika mtandao wao. Hii inategemea kiasi cha kuchukua hatari ya sasa miongoni mwa wapiga kura wengine. <unk> Timu sasa ni nia ya kuchunguza nini inaweza kuongeza au kuzuia tabia hii ya kuchukua hatari. "Sasa tuna mfumo thabiti na mfano, ambao unaweza kutumika kuchunguza mambo ya mazingira ambayo inaweza kufanya watu kuwa na inertia kubwa, au kuwa zaidi nyeti kwa mwenendo, "anasema Ye. Kanuni hizo tatu za msingi zaweza kusaidia kuongoza tabia ya vikundi vikubwa. "Bila shaka, hatuwezi <unk>kudhibiti watu<unk>", Cao anasisitiza. "Lakini tunaweza kutoa miongozo, kwa mfano juu ya jinsi ya kusukuma watu kubadilisha tabia yao. "" Hii inaweza kuwa na manufaa katika mabadiliko ya nishati, au katika kupata watu kupunguza matumizi yao ya nyama. """ "Serikali tayari hutumia pesa kuwashawishi watu kufuata tabia endelevu zaidi. Utafiti wetu unaweza kuwasaidia kutumia kwa njia bora zaidi. <unk> Kwa hadithi zaidi za sayansi angalia sehemu yetu ya Ugunduzi Mpya kwenye Upande Mwangavu wa Habari. Kama aina hii ya kuhisi hadithi nzuri? Kupata Brighter Side ya Habari 'newsletter.