325,056 research outputs found
Distinguishing humans from computers in the game of go: a complex network approach
We compare complex networks built from the game of go and obtained from
databases of human-played games with those obtained from computer-played games.
Our investigations show that statistical features of the human-based networks
and the computer-based networks differ, and that these differences can be
statistically significant on a relatively small number of games using specific
estimators. We show that the deterministic or stochastic nature of the computer
algorithm playing the game can also be distinguished from these quantities.
This can be seen as tool to implement a Turing-like test for go simulators.Comment: 7 pages, 6 figure
Gaming on and off the social graph: the social structure of Facebook games
Games built on Online Social Networks (OSNs) have become a phenomenon since 3rd party developer tools were released by OSNs such as Facebook. However, apart from their explosive popularity, little is known about the nature of the social networks that are built during play. In this paper, we present the findings of a network analysis study carried out on two Facebook applications, in comparison with a similar but stand-alone game. We found that games built both on and off a social graph exhibit similar social properties. Specifically, the distribution of player-to-player interactions decays as a power law with a similar exponent for the majority of players. For games built on the social network platform however, we find that the networks are characterised by a sharp cut-off, compared with the classically scale-free nature of the social network for the game not built on an existing social graph
Evolutionary games on multilayer networks: A colloquium
Networks form the backbone of many complex systems, ranging from the Internet
to human societies. Accordingly, not only is the range of our interactions
limited and thus best described and modeled by networks, it is also a fact that
the networks that are an integral part of such models are often interdependent
or even interconnected. Networks of networks or multilayer networks are
therefore a more apt description of social systems. This colloquium is devoted
to evolutionary games on multilayer networks, and in particular to the
evolution of cooperation as one of the main pillars of modern human societies.
We first give an overview of the most significant conceptual differences
between single-layer and multilayer networks, and we provide basic definitions
and a classification of the most commonly used terms. Subsequently, we review
fascinating and counterintuitive evolutionary outcomes that emerge due to
different types of interdependencies between otherwise independent populations.
The focus is on coupling through the utilities of players, through the flow of
information, as well as through the popularity of different strategies on
different network layers. The colloquium highlights the importance of pattern
formation and collective behavior for the promotion of cooperation under
adverse conditions, as well as the synergies between network science and
evolutionary game theory.Comment: 14 two-column pages, 8 figures; accepted for publication in European
Physical Journal
A condition of cooperation. Games on network
Natural selection is often regarded as a result of severe competition. Defect seems beneficial for a single individual in many cases.However, cooperation is observed in many levels of biological systems ranging from single cells to animals, including human society. We have yet known that in unstructured populations, evolution favors defectors over cooperators. On the other hand, there have been much interest on evolutionary games^1,2^ on structured population and on graphs^3-16^. Structures of biological systems and societies of animals can be taken as networks. They discover that network structures determine results of the games. Together with the recent interest of complex networks^17,18^, many researchers investigate real network structures. Recently even economists study firms' transactions structure^19^. Seminal work^11^ derives the condition of favoring cooperation for evolutionary games on networks, that is, benefit divided by cost, _b/c_, exceeds average degree, (_k_). Although this condition has been believed so far^20^, we find the condition is _b/c_ (_k~nm~_) instead. _k~nm~_ is the mean nearest neighbor degree. Our condition enables us to compare how network structure enhances cooperation across different kinds of networks. Regular network favors most, scale free network least. On ideal scale free networks, cooperation is unfeasible. We could say that (_k_) is the degree of itself, while _k~nm~_ is that of others. One of the most interesting points in network theory is that results depend not only on itself but also on others. In evolutionary games on network, we find the same characteristic
Connected Coordination: Network Structure and Group Coordination
Networks can affect a groupâs ability to solve a coordination problem. We utilize laboratory experiments to study the conditions under which groups of subjects can solve coordination games. We investigate a variety of different network structures, and we also investigate coordination games with symmetric and asymmetric payoffs. Our results show that network connections facilitate coordination in both symmetric and asymmetric games. Most significantly, we find that increases in the number of network connections encourage coordination even when payoffs are highly asymmetric. These results shed light on the conditions that may facilitate coordination in real-world networks
A Comprehensive Survey of Potential Game Approaches to Wireless Networks
Potential games form a class of non-cooperative games where unilateral
improvement dynamics are guaranteed to converge in many practical cases. The
potential game approach has been applied to a wide range of wireless network
problems, particularly to a variety of channel assignment problems. In this
paper, the properties of potential games are introduced, and games in wireless
networks that have been proven to be potential games are comprehensively
discussed.Comment: 44 pages, 6 figures, to appear in IEICE Transactions on
Communications, vol. E98-B, no. 9, Sept. 201
Move ordering and communities in complex networks describing the game of go
We analyze the game of go from the point of view of complex networks. We
construct three different directed networks of increasing complexity, defining
nodes as local patterns on plaquettes of increasing sizes, and links as actual
successions of these patterns in databases of real games. We discuss the
peculiarities of these networks compared to other types of networks. We explore
the ranking vectors and community structure of the networks and show that this
approach enables to extract groups of moves with common strategic properties.
We also investigate different networks built from games with players of
different levels or from different phases of the game. We discuss how the study
of the community structure of these networks may help to improve the computer
simulations of the game. More generally, we believe such studies may help to
improve the understanding of human decision process.Comment: 14 pages, 21 figure
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