9,518 research outputs found
Statistical Physics of the Spatial Prisoner's Dilemma with Memory-Aware Agents
We introduce an analytical model to study the evolution towards equilibrium
in spatial games, with `memory-aware' agents, i.e., agents that accumulate
their payoff over time. In particular, we focus our attention on the spatial
Prisoner's Dilemma, as it constitutes an emblematic example of a game whose
Nash equilibrium is defection. Previous investigations showed that, under
opportune conditions, it is possible to reach, in the evolutionary Prisoner's
Dilemma, an equilibrium of cooperation. Notably, it seems that mechanisms like
motion may lead a population to become cooperative. In the proposed model, we
map agents to particles of a gas so that, on varying the system temperature,
they randomly move. In doing so, we are able to identify a relation between the
temperature and the final equilibrium of the population, explaining how it is
possible to break the classical Nash equilibrium in the spatial Prisoner's
Dilemma when considering agents able to increase their payoff over time.
Moreover, we introduce a formalism to study order-disorder phase transitions in
these dynamics. As result, we highlight that the proposed model allows to
explain analytically how a population, whose interactions are based on the
Prisoner's Dilemma, can reach an equilibrium far from the expected one; opening
also the way to define a direct link between evolutionary game theory and
statistical physics.Comment: 7 pages, 5 figures. Accepted for publication in EPJ-
The impact of the termination rule on cooperation in a prisoner's dilemma experiment
Cooperation in prisoner's dilemma games can usually be sustained only if the game has an infinite horizon. We analyze to what extent the theoretically crucial distinction of finite vs. infinite-horizon games is reflected in the outcomes of a prisoner's dilemma experiment. We compare three different experimental termination rules in four treatments: a known finite end, an unknown end, and two variants with a random termination rule (with a high and with a low continuation probability, where cooperation can occur in a subgame-perfect equilibrium only with the high probability). We find that the termination rules do not significantly affect average cooperation rates. Specifically, employing a random termination rule does not cause significantly more cooperation compared to a known finite horizon, and the continuation probability does not significantly affect average cooperation rates either. However, the termination rules may influence cooperation over time and end-game behavior. Further, the (expected) length of the game significantly increases cooperation rates. The results suggest that subjects may need at least some learning opportunities (like repetitions of the supergame) before significant backward induction arguments in finitely repeated game have force. --Prisoner's dilemma,Repeated games,Infinite-horizon games,Experimental economics
Decisions and disease: a mechanism for the evolution of cooperation
In numerous contexts, individuals may decide whether they take actions to
mitigate the spread of disease, or not. Mitigating the spread of disease
requires an individual to change their routine behaviours to benefit others,
resulting in a 'disease dilemma' similar to the seminal prisoner's dilemma. In
the classical prisoner's dilemma, evolutionary game dynamics predict that all
individuals evolve to 'defect.' We have discovered that when the rate of
cooperation within a population is directly linked to the rate of spread of the
disease, cooperation evolves under certain conditions. For diseases which do
not confer immunity to recovered individuals, if the time scale at which
individuals receive information is sufficiently rapid compared to the time
scale at which the disease spreads, then cooperation emerges. Moreover, in the
limit as mitigation measures become increasingly effective, the disease can be
controlled, and the rate of infections tends to zero. Our model is based on
theoretical mathematics and therefore unconstrained to any single context. For
example, the disease spreading model considered here could also be used to
describe social and group dynamics. In this sense, we may have discovered a
fundamental and novel mechanism for the evolution of cooperation in a broad
sense
Different perceptions of social dilemmas: Evolutionary multigames in structured populations
Motivated by the fact that the same social dilemma can be perceived
differently by different players, we here study evolutionary multigames in
structured populations. While the core game is the weak prisoner's dilemma, a
fraction of the population adopts either a positive or a negative value of the
sucker's payoff, thus playing either the traditional prisoner's dilemma or the
snowdrift game. We show that the higher the fraction of the population adopting
a different payoff matrix, the more the evolution of cooperation is promoted.
The microscopic mechanism responsible for this outcome is unique to structured
populations, and it is due to the payoff heterogeneity, which spontaneously
introduces strong cooperative leaders that give rise to an asymmetric strategy
imitation flow in favor of cooperation. We demonstrate that the reported
evolutionary outcomes are robust against variations of the interaction network,
and they also remain valid if players are allowed to vary which game they play
over time. These results corroborate existing evidence in favor of
heterogeneity-enhanced network reciprocity, and they reveal how different
perceptions of social dilemmas may contribute to their resolution.Comment: 7 two-column pages, 5 figures; accepted for publication in Physical
Review
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