8,566 research outputs found
Network Formation with Adaptive Agents
In this paper, a reinforcement learning version of the connections game first analysed by Jackson and Wolinsky is presented and compared with benchmark results of fully informed and rational players. Using an agent-based simulation approach, the main nding is that the pattern of reinforcement learning process is similar, but does not fully converge to the benchmark results. Before these optimal results can be discovered in a learning process, agents often get locked in a state of random switching or early lock-in.agent-based computational economics; strategic network formation; network games; reinforcement learning
Games on graphs: A minor modification of payoff scheme makes a big difference
Various social dilemma games that follow different strategy updating rules
have been studied on many networks.The reported results span the entire
spectrum, from significantly boosting,to marginally affecting,to seriously
decreasing the level of cooperation.Experimental results that are qualitatively
different from theoretical prediction have also been reported.It is widely
believed that the results are largely determined by three elements,including
payoff matrices of the underlying 2*2 games,the way that the strategic states
of the players are updated and the structure of the networks.Here we discuss
the impact of a seemly non-essential mechanism -- what we refer to as a "payoff
scheme". Specifically, in each round after the states of all of the players are
determined,the payoff scheme is how each player's payoff is calculated.In
addition to the two conventions in which either the accumulated or the averaged
payoff is calculated from playing with all of the neighboring players,we here
study the effects of calculating the payoff from pairing up with one random
player from among the neighboring players. Based on probability theory, in a
situation of uncorrelated events, the average payoff that involves all of the
neighbors should,in principal,be equivalent to the payoff from pairing up with
one neighbor.However,our simulation of games on graphs shows that, in many
cases,the two payoff schemes lead to qualitatively different levels of
cooperation.This finding appears to provide a possible explanation for a wide
spectrum of observed behaviors in the literature.We have also observed that
results from the randomly-pairing-one mechanism are more robust than the
involving-all-neighbours mechanism because,in the former case, neither the
other three main elements nor the initial states of the players have a large
impact on the final level of cooperation compared with in the latter case.Comment: 23 pages,171 figure
Evolutionary games on graphs
Game theory is one of the key paradigms behind many scientific disciplines
from biology to behavioral sciences to economics. In its evolutionary form and
especially when the interacting agents are linked in a specific social network
the underlying solution concepts and methods are very similar to those applied
in non-equilibrium statistical physics. This review gives a tutorial-type
overview of the field for physicists. The first three sections introduce the
necessary background in classical and evolutionary game theory from the basic
definitions to the most important results. The fourth section surveys the
topological complications implied by non-mean-field-type social network
structures in general. The last three sections discuss in detail the dynamic
behavior of three prominent classes of models: the Prisoner's Dilemma, the
Rock-Scissors-Paper game, and Competing Associations. The major theme of the
review is in what sense and how the graph structure of interactions can modify
and enrich the picture of long term behavioral patterns emerging in
evolutionary games.Comment: Review, final version, 133 pages, 65 figure
Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics
Evolutionary game dynamics is one of the most fruitful frameworks for
studying evolution in different disciplines, from Biology to Economics. Within
this context, the approach of choice for many researchers is the so-called
replicator equation, that describes mathematically the idea that those
individuals performing better have more offspring and thus their frequency in
the population grows. While very many interesting results have been obtained
with this equation in the three decades elapsed since it was first proposed, it
is important to realize the limits of its applicability. One particularly
relevant issue in this respect is that of non-mean-field effects, that may
arise from temporal fluctuations or from spatial correlations, both neglected
in the replicator equation. This review discusses these temporal and spatial
effects focusing on the non-trivial modifications they induce when compared to
the outcome of replicator dynamics. Alongside this question, the hypothesis of
linearity and its relation to the choice of the rule for strategy update is
also analyzed. The discussion is presented in terms of the emergence of
cooperation, as one of the current key problems in Biology and in other
disciplines.Comment: Review, 48 pages, 26 figure
Advances in Negotiation Theory: Bargaining, Coalitions and Fairness
Bargaining is ubiquitous in real-life. It is a major dimension of political and business activities. It appears at the international level, when governments negotiate on matters ranging from economic issues (such as the removal of trade barriers), to global security (such as fighting against terrorism) to environmental and related issues (e.g. climate change control). What factors determine the outcome of negotiations such as those mentioned above? What strategies can help reach an agreement? How should the parties involved divide the gains from cooperation? With whom will one make alliances? This paper addresses these questions by focusing on a non-cooperative approach to negotiations, which is particularly relevant for the study of international negotiations. By reviewing non-cooperative bargaining theory, non-cooperative coalition theory, and the theory of fair division, this paper will try to identify the connection among these different facets of the same problem in an attempt to facilitate the progress towards a unified framework.Negotiation theory, Bargaining, Coalitions, Fairness, Agreements
Learning in Networks: a survey
This paper presents a survey of research on learning with a special focus on the structure of interaction between individual entities. The structure is formally modelled as a network: the nodes of the network are individuals while the arcs admit a variety of interpretations (ranging from information channels to social and economic ties). I first examine the nature of learning about optimal actions for a given network architecture. I then discuss learning about optimal links and actions in evolving networks.
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