Dynamic peer-to-peer competition

Caram, L. F.; Caiafa, César F.; Proto, A. N.; Ausloos, Marcel

doi:10.1016/j.physa.2010.02.032

Cited by 25 publications

(44 citation statements)

References 33 publications

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“…The same type of difficulty occurs in related problems, such as in opinion formation [59,60]. Moreover, it may also happen in certain cases that individuals do not believe in old strategies in order to avoid the disease.…”

Section: Introductionmentioning

confidence: 96%

Memory effects on epidemic evolution: The susceptible-infected-recovered epidemic model

et al. 2017

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Memory has a great impact on the evolution of every process related to human societies. Among them, the evolution of an epidemic is directly related to the individuals' experiences. Indeed, any real epidemic process is clearly sustained by a non-Markovian dynamics: memory effects play an essential role in the spreading of diseases. Including memory effects in the susceptible-infected-recovered (SIR) epidemic model seems very appropriate for such an investigation. Thus, the memory prone SIR model dynamics is investigated using fractional derivatives. The decay of long-range memory, taken as a power-law function, is directly controlled by the order of the fractional derivatives in the corresponding nonlinear fractional differential evolution equations. Here we assume "fully mixed" approximation and show that the epidemic threshold is shifted to higher values than those for the memoryless system, depending on this memory "length" decay exponent. We also consider the SIR model on structured networks and study the effect of topology on threshold points in a non-Markovian dynamics. Furthermore, the lack of access to the precise information about the initial conditions or the past events plays a very relevant role in the correct estimation or prediction of the epidemic evolution. Such a "constraint" is analyzed and discussed.

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Section: Introductionmentioning

confidence: 96%

Memory effects on epidemic evolution: The susceptible-infected-recovered epidemic model

et al. 2017

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“…Notice that the model goes well away for the two-player prisoner (dilemma) game [24]. Thus, a mixed type of interactions between agents, made possible through the network effect in the generalized Verhulst-Lotka-Volterra model, markedly differs from previous works [17][18][19], and seems more realistic. This paper is organized as follows: in Sec.…”

Section: Introductionmentioning

confidence: 82%

“…The model is used in Ref. [17] to analyze a system of n agents in competition for some common resources with competition becoming more aggressive between agents with similar size. This is because as |s i − s j | → 0, the interaction function γ (s i ,s j ) → K for a constant parameter σ , its maximum value.…”

Section: Generalized Verhulst-lotka-volterra Modelmentioning

confidence: 99%

Effects of competition and cooperation interaction between agents on networks in the presence of a market capacity

et al. 2016

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A network effect is introduced taking into account competition, cooperation, and mixed-type interaction among agents along a generalized Verhulst-Lotka-Volterra model. It is also argued that the presence of a market capacity undoubtedly enforces a definite limit on the agent's size growth. The state stability of triadic agents, i.e., the most basic network plaquette, is investigated analytically for possible scenarios, through a fixed-point analysis. It is discovered that: (i) market demand is only satisfied for full competition when one agent monopolizes the market; (ii) growth of agent size is encouraged in full cooperation; (iii) collaboration among agents to compete against one single agent may result in the disappearance of this single agent out of the market; and (iv) cooperating with two rivals may become a growth strategy for an intelligent agent.

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“…Some previous agent-based models for cooperative and competitive small groups have modelled the effect of status comparisons as direct comparisons of the statuses of individual agents (Caram et al 2010(Caram et al , 2015. Also, in these cases, agents of similar statuses form sub-groups or cliques.…”

Section: Discussionmentioning

confidence: 99%

Formation of reciprocal appreciation patterns in small groups: an agent-based model

Koponen

Nousiainen

2016

Complex Adapt Syst Model

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Purpose In small cooperative and collaborative groups, patterns of interaction, discourse and dialogue are often strongly bidirectional; ties are reciprocal and reciprocated. This reciprocation of ties leads to the formation of interaction patterns that are reciprocated dyads (two individuals connected reciprocally) and triads (three individuals connected reciprocally). In this study, we use an agent-based model to explore how such reciprocated dyadic and triadic patterns emerge from self-reinforced appreciation between peers in a small group. Methods The model assumes that the agents’ decisions to interact depend on how their self-appreciation compares to their appreciations of their peers (peer-appreciation). These comparisons are competitive in that an agent seek to increase its appreciation in relation to its peers. As a consequence, agents change their self-appreciation and appreciation towards their peers depending on their sensitivity to the competitive comparison. Results When agents’ sensitivity to competitive comparisons is low, the most common patterns of appreciation are egalitarian triads (all three agents appreciate each other), while for moderate sensitivity, leadership-type patterns emerge (one agent connected strongly to two other unconnected agents). When sensitivity is high, strong reciprocally connected dyads emerge. The model thus predicts thus a transition from egalitarian triads to strong dyads as agents’ sensitivity to competitive comparisons increases. Conclusions The structural similarity between patterns emerging as model results and patterns reported in empirical research suggests that: (1) reciprocation based on appreciation is a strong candidate for explaining the formation of such patterns, and (2) individual sensitivity to competitive comparisons of appreciation may be a key factor that can be used to the tune dynamics of interaction in small groups.

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Dynamic peer-to-peer competition

Cited by 25 publications

References 33 publications

Memory effects on epidemic evolution: The susceptible-infected-recovered epidemic model

Memory effects on epidemic evolution: The susceptible-infected-recovered epidemic model

Effects of competition and cooperation interaction between agents on networks in the presence of a market capacity

Formation of reciprocal appreciation patterns in small groups: an agent-based model

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