31,560 research outputs found
The Networked Common Goods Game
We introduce a new class of games called the networked common goods game
(NCGG), which generalizes the well-known common goods game. We focus on a
fairly general subclass of the game where each agent's utility functions are
the same across all goods the agent is entitled to and satisfy certain natural
properties (diminishing return and smoothness). We give a comprehensive set of
technical results listed as follows.
* We show the optimization problem faced by a single agent can be solved
efficiently in this subclass. The discrete version of the problem is however
NP-hard but admits an fully polynomial time approximation scheme (FPTAS).
* We show uniqueness results of pure strategy Nash equilibrium of NCGG, and
that the equilibrium is fully characterized by the structure of the network and
independent of the choices and combinations of agent utility functions.
* We show NCGG is a potential game, and give an implementation of best/better
response Nash dynamics that lead to fast convergence to an
-approximate pure strategy Nash equilibrium.
* Lastly, we show the price of anarchy of NCGG can be as large as
(for any ), which means selfish behavior
in NCGG can lead to extremely inefficient social outcomes
Cooperation and Contagion in Web-Based, Networked Public Goods Experiments
A longstanding idea in the literature on human cooperation is that
cooperation should be reinforced when conditional cooperators are more likely
to interact. In the context of social networks, this idea implies that
cooperation should fare better in highly clustered networks such as cliques
than in networks with low clustering such as random networks. To test this
hypothesis, we conducted a series of web-based experiments, in which 24
individuals played a local public goods game arranged on one of five network
topologies that varied between disconnected cliques and a random regular graph.
In contrast with previous theoretical work, we found that network topology had
no significant effect on average contributions. This result implies either that
individuals are not conditional cooperators, or else that cooperation does not
benefit from positive reinforcement between connected neighbors. We then tested
both of these possibilities in two subsequent series of experiments in which
artificial seed players were introduced, making either full or zero
contributions. First, we found that although players did generally behave like
conditional cooperators, they were as likely to decrease their contributions in
response to low contributing neighbors as they were to increase their
contributions in response to high contributing neighbors. Second, we found that
positive effects of cooperation were contagious only to direct neighbors in the
network. In total we report on 113 human subjects experiments, highlighting the
speed, flexibility, and cost-effectiveness of web-based experiments over those
conducted in physical labs
Application of the war of attrition game to the analysis of intellectual property disputes
In many developing countries intellectual property infringement and the
commerce of pirate goods is an entrepreneurial activity. Digital piracy is very
often the only media for having access to music, cinema, books and software. At
the same time, bio-prospecting and infringement of indigenous knowledge rights
by international consortiums is usual in places with high biodiversity. In
these arenas transnational actors interact with local communities. Accusations
of piracy often go both ways. This article analyzes the case of southeast
Mexico. Using a war of attrition game theory model it explains different
situations of intellectual property rights piracy and protection. It analyzes
different levels of interaction and institutional settings from the global to
the very local. The article proposes free IP zones as a solution of IP
disputes. The formation of technological local clusters through Free
Intellectual Property Zones (FIPZ) would allow firms to copy and share de facto
public domain content for developing new products inside the FIPZ. Enforcement
of intellectual property could be pursuit outside of the FIPZ. FIPZ are
envisioned as a new type of a sui generis intellectual property regime
Response to Privacy as a Public Good
In the spirit of moving forward the theoretical and empirical scholarship on privacy as a public good, this response addresses four issues raised by Professors Fairfield and Engel’s article: first, their depiction of individuals in groups; second, suggestions for clarifying the concept of group; third, an explanation of why the platforms on which groups exist and interact needs more analysis; and finally, the question of what kind of government intervention might be necessary to protect privacy as a public good
Domestic Outsourcing, Rent Seeking, and Increasing Inequality
An increasing share of the economy is organized around financial capitalism, where, in contrast to the past, capital market actors actively assert and manage their claims on wealth creation and distribution. These new actors challenge prior assumptions of managerial capitalism about the goals and governance of firms. The focus on shareholder value is credited with increasing firm efficiency and shareholder returns. This lecture analyzes the changes in organizational behavior and value extraction under financial capitalism
Emergence of communities and diversity in social networks
Communities are common in complex networks and play a significant role in the functioning of social, biological, economic,
and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the
effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social
networks is still lacking. Addressing this fundamental problem
is of paramount importance in understanding, predicting, and
controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here,
we answer this question using the ultimatum game, which has
been a paradigm for characterizing altruism and fairness. We
experimentally show that stable local communities with different
internal agreements emerge spontaneously and induce social
diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social
norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community
leaders. This result indicates that networks are significant in the
emergence and stabilization of communities and social diversity.
Our experimental results also provide valuable information about
strategies for developing network models and theories of evolutionary games and social dynamics.This work was supported by the National Nature Science Foundation of China under Grants 61573064, 71631002, 71401037, and 11301032; the Fundamental Research Funds for the Central Universities and Beijing Nova Programme; and the Natural Sciences and Engineering Research Council of Canada (Individual Discovery Grant). The Boston University work was supported by NSF Grants PHY-1505000, CMMI-1125290, and CHE- 1213217, and by Defense Threat Reduction Agency Grant HDTRA1-14-1-0017, and Department of Energy Contract DE-AC07-05Id14517. (61573064 - National Nature Science Foundation of China; 71631002 - National Nature Science Foundation of China; 71401037 - National Nature Science Foundation of China; 11301032 - National Nature Science Foundation of China; Fundamental Research Funds for the Central Universities and Beijing Nova Programme; Natural Sciences and Engineering Research Council of Canada (Individual Discovery Grant); PHY-1505000 - NSF; CMMI-1125290 - NSF; CHE-1213217 - NSF; HDTRA1-14-1-0017 - Defense Threat Reduction Agency; DE-AC07-05Id14517 - Department of Energy)Published versio
A Mechanism for Fair Distribution of Resources without Payments
We design a mechanism for Fair and Efficient Distribution of Resources
(FEDoR) in the presence of strategic agents. We consider a multiple-instances,
Bayesian setting, where in each round the preference of an agent over the set
of resources is a private information. We assume that in each of r rounds n
agents are competing for k non-identical indivisible goods, (n > k). In each
round the strategic agents declare how much they value receiving any of the
goods in the specific round. The agent declaring the highest valuation receives
the good with the highest value, the agent with the second highest valuation
receives the second highest valued good, etc. Hence we assume a decision
function that assigns goods to agents based on their valuations. The novelty of
the mechanism is that no payment scheme is required to achieve truthfulness in
a setting with rational/strategic agents. The FEDoR mechanism takes advantage
of the repeated nature of the framework, and through a statistical test is able
to punish the misreporting agents and be fair, truthful, and socially
efficient. FEDoR is fair in the sense that, in expectation over the course of
the rounds, all agents will receive the same good the same amount of times.
FEDoR is an eligible candidate for applications that require fair distribution
of resources over time. For example, equal share of bandwidth for nodes through
the same point of access. But further on, FEDoR can be applied in less trivial
settings like sponsored search, where payment is necessary and can be given in
the form of a flat participation fee. To this extent we perform a comparison
with traditional mechanisms applied to sponsored search, presenting the
advantage of FEDoR
Quantity Competition in Networked Markets Outflow and Inflow Competition
This paper investigates how quantity competition operates in economies in which a network describes the set of feasible trades. A general equilibrium model is presented in which prices and .ows of goods are endogenously determined. In such economies equilibrium dictates whether an individual buys, sells or does both (which is possible). The first part of the analysis provides sufficient conditions for pure strategy equilibrium existence; characterizes equilibrium prices, flows and markups; and details negative effects on welfare of changes in the network structure. The main contributions show that goods do not cycle, since prices strictly increase along the supply chains; that not all connected players with different marginal rates of substitution trade; and that adding trading relationships may decrease individual and social welfare. The second part of the analysis provides necessary and sufficient conditions for a networked economy to become competitive as the number of players grows large. In this context it shown that no economy in which goods are resold can ever be competitive; and that large well connected economies are competitive.
Leaders should not be conformists in evolutionary social dilemmas
The most common assumption in evolutionary game theory is that players should
adopt a strategy that warrants the highest payoff. However, recent studies
indicate that the spatial selection for cooperation is enhanced if an
appropriate fraction of the population chooses the most common rather than the
most profitable strategy within the interaction range. Such conformity might be
due to herding instincts or crowd behavior in humans and social animals. In a
heterogeneous population where individuals differ in their degree, collective
influence, or other traits, an unanswered question remains who should conform.
Selecting conformists randomly is the simplest choice, but it is neither a
realistic nor the optimal one. We show that, regardless of the source of
heterogeneity and game parametrization, socially the most favorable outcomes
emerge if the masses conform. On the other hand, forcing leaders to conform
significantly hinders the constructive interplay between heterogeneity and
coordination, leading to evolutionary outcomes that are worse still than if
conformists were chosen randomly. We conclude that leaders must be able to
create a following for network reciprocity to be optimally augmented by
conformity. In the opposite case, when leaders are castrated and made to
follow, the failure of coordination impairs the evolution of cooperation.Comment: 7 two-column pages, 4 figures; accepted for publication in Scientific
Reports [related work available at arXiv:1412.4113
Rethinking network reciprocity over social ties: local interactions make direct reciprocity possible and pave the rational way to cooperation
Since Nowak & May's (1992) influential paper, network reciprocity--the fact
that individuals' interactions repeated within a local neighborhood support the
evolution of cooperation--has been confirmed in several theoretical models.
Essentially, local interactions allow cooperators to stay protected from
exploiters by assorting into clusters, and the heterogeneity of the network of
contacts--the co-presence of low- and high-connected nodes--has been shown to
further favor cooperation. The few available large-scale experiments on humans
have however missed these effects. The reason is that, while models assume that
individuals update strategy by imitating better performing neighbors,
experiments showed that humans are more prone to reciprocate cooperation than
to compare payoffs. Inspired by the empirical results, we rethink network
reciprocity as a rational form of direct reciprocity on networks--networked
rational reciprocity--indeed made possible by the locality of interactions. We
show that reciprocal altruism in a networked prisoner's dilemma can invade and
fixate in any network of rational agents, profit-maximizing over an horizon of
future interactions. We find that networked rational reciprocity works better
at low average connectivity and we unveil the role of network heterogeneity.
Only if cooperating hubs invest in the initial cost of exploitation, the
invasion of cooperation is boosted; it is otherwise hindered. Although humans
might not be as rational as here assumed, our results could help the design and
interpretation of new experiments in social and economic network
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