Individual irrationality, network structure, and collective intelligence: An agent‐based simulation approach

Xu, Bo; Liu, Renjing; He, Zhengwen

doi:10.1002/cplx.21709

Cited by 10 publications

(12 citation statements)

References 51 publications

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“…Similar views are expressed by Xu et al. ( 2016 ) following the results of multi-agent computer simulations in a search task similar to that studied by Lazer and Friedman ( 2007 ). Their results suggest that an irrational, dogmatic adherence to certain kinds of belief can function to enhance the collective search performance of an agent community.…”

Section: Distrust Dogmatism and Dynamic Networksupporting

confidence: 67%

“…We have thus examined the results of studies that indicate a potentially positive role for factors like dogmatism (Xu et al. 2016 ; Zollman 2010 ), confirmation bias (Mercier and Sperber 2011 ) and mnemonic constraints (Bhattacharyya and Ohlsson 2010 ; Reitter and Lebiere 2012 ) in supporting the performance of teams, groups and communities.…”

Section: Discussionmentioning

confidence: 99%

“…This helps us understand the results of Zollman ( 2010 ) and Xu et al. ( 2016 ) with respect to the beneficial effects of individual cognitive vice (dogmatism and irrationality) on collective performance. The individual cognitive properties, in this case, are reshaping the effective structure of the communication network in a manner that befits the processing demands of a particular task.…”

Section: Distrust Dogmatism and Dynamic Networkmentioning

confidence: 93%

“…2010 ; Xu et al. 2016 ). As is noted by Mason ( 2013 ), many of the tasks used in these studies can be usefully viewed as a form of collective search task.…”

Section: Collective Searchmentioning

confidence: 99%

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Mandevillian intelligence

Smart

2017

Synthese

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Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive vices (i.e., shortcomings, limitations, constraints and biases) are seen to play a positive functional role in yielding collective forms of cognitive success. The present paper introduces the concept of mandevillian intelligence and reviews a number of strands of empirical research that help to shed light on the phenomenon. The paper also attempts to highlight the value of the concept of mandevillian intelligence from a philosophical, scientific and engineering perspective. Inasmuch as we accept the notion of mandevillian intelligence, then it seems that the cognitive and epistemic value of a specific social or technological intervention will vary according to whether our attention is focused at the individual or collective level of analysis. This has a number of important implications for how we think about the design and evaluation of collective cognitive systems. For example, the notion of mandevillian intelligence forces us to take seriously the idea that the exploitation (or even the accentuation) of individual cognitive shortcomings could, in some situations, provide a productive route to collective forms of cognitive and epistemic success.

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Section: Distrust Dogmatism and Dynamic Networksupporting

confidence: 67%

Section: Discussionmentioning

confidence: 99%

Section: Distrust Dogmatism and Dynamic Networkmentioning

confidence: 93%

“…2010 ; Xu et al. 2016 ). As is noted by Mason ( 2013 ), many of the tasks used in these studies can be usefully viewed as a form of collective search task.…”

Section: Collective Searchmentioning

confidence: 99%

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Mandevillian intelligence

Smart

2017

Synthese

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“…Creating simulation mathematical models allows us to use a variety of methods and approaches. This could include a multiagents approach [17,18], Petri nets [19], object-oriented approach [20], or many others. For the purposes of logistics and production systems, which are the main focus of this article, heuristic approaches can be effectively used.…”

Section: Introductionmentioning

confidence: 99%

Modelling Decision-Making Processes in the Management Support of the Manufacturing Element in the Logistic Supply Chain

Bucki

Suchánek

2017

Complexity

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This paper highlights the problems of mathematical modelling for a specific element of the logistic supply chain, that is, the manufacturing system. The complex manufacturing system consisting of a determined number of parallel subsystems is modelled. The fact that the same manufacturing procedure can be carried out in various locations is emphasised. Control algorithms as well as manufacturing strategies are explained. The equations of state are introduced. The two-stage criterion lets us use the result data generated by the simulator of the production system as the initial data for further processing; however, the main goal remains to minimise the time of the course of production. The precisely elaborated case study implements initial data obtained by preceding simulation procedures carried out in manufacturing systems consisting of three, four, and five subsystems.

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Modeling networked systems using the topologically distributed bounded rationality framework

2016

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In networked systems research, game theory is increasingly used to model a number of scenarios where distributed decision making takes place in a competitive environment. These scenarios include peer‐to‐peer network formation and routing, computer security level allocation, and TCP congestion control. It has been shown, however, that such modeling has met with limited success in capturing the real‐world behavior of computing systems. One of the main reasons for this drawback is that, whereas classical game theory assumes perfect rationality of players, real world entities in such settings have limited information, and cognitive ability which hinders their decision making. Meanwhile, new bounded rationality models have been proposed in networked game theory which take into account the topology of the network. In this article, we demonstrate that game‐theoretic modeling of computing systems would be much more accurate if a topologically distributed bounded rationality model is used. In particular, we consider (a) link formation on peer‐to‐peer overlay networks (b) assigning security levels to computers in computer networks (c) routing in peer‐to‐peer overlay networks, and show that in each of these scenarios, the accuracy of the modeling improves very significantly when topological models of bounded rationality are applied in the modeling process. Our results indicate that it is possible to use game theory to model competitive scenarios in networked systems in a way that closely reflects real world behavior, topology, and dynamics of such systems. © 2016 Wiley Periodicals, Inc. Complexity 21: 123–137, 2016

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Individual irrationality, network structure, and collective intelligence: An agent‐based simulation approach

Cited by 10 publications

References 51 publications

Mandevillian intelligence

Mandevillian intelligence

Modelling Decision-Making Processes in the Management Support of the Manufacturing Element in the Logistic Supply Chain

Modeling networked systems using the topologically distributed bounded rationality framework

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