Speaker
Prof.
Bing-Hong Wang
(University of Science and Technology of China)
Description
Since the spatial structure is introduced into the
evolutionary games by Nowak and May, there has been a
continuous effort on exploring effects of spatial structures
on the cooperation. It has been found that the spatial
structure promotes evolution of cooperation in the
prisoner's dilemma game (PDG), while in contrast often
inhibits cooperative behavior in the snowdrift game (SG). In
recent years, extensive studies indicate that many real
networks are far different from regular lattices, instead,
show small-world and scale-free topological properties.
Hence, it is naturally to consider evolutionary games on
networks with these kinds of properties. An interesting
result found by Santos and Pacheco is that “Scale-free
networks provide a unifying framework for the emergence of
cooperation”.
First, I will review some of our works in the field of
evolutionary games. By means of some simple models, we have
studied how an important topological structural feature, the
average degree, affects the cooperative behavior. We found
there is a highest cooperation level induced by an optimal
value of average degree for different types of networks.
Besides, we investigate the randomness effect on the
cooperative behavior by introducing both topological and
dynamical randomness. We found a resonance type phenomena
reflected by the existence of highest level of cooperation
in the case of appropriate randomness. Moreover, we propose
a memory-based snowdrift game over complex networks. Some
very interesting behaviors are observed, such as the
nonmonotonous behavior of frequency of cooperation as a
function of payoff parameter, spatial pattern transition and
so on.
Then, I shall discuss about a structured language game, the
naming game. We propose an asymmetric negotiation strategy
to investigate the influence of high-degree agents on the
agreement dynamics in the naming game. We introduce a model
parameter, which governs the frequency of high-degree agents
acting as speakers in communication. It is found that there
exists an optimal value of the parameter that induces the
fastest convergence to a global consensus on naming an
object for both scale-free and small-world naming games.
This phenomenon indicates that, although a strong influence
of high-degree agents favors consensus achievement, very
strong influences inhibit the convergence process, making it
even slower than in the absence of influence of high-degree
agents. Investigation of the total memory used by agents
implies that there is some trade-off between the convergence
speed and the required total memory. Other quantities,
including the evolution of the number of different names and
the relationship between agents’ memories and their degrees,
are also studied. The results are helpful for better
understanding of the dynamics of the naming game with
asymmetric negotiation strategy.
