35 research outputs found
Wealth distribution across communities of adaptive financial agents
This paper studies the trading volumes and wealth distribution of a novel
agent-based model of an artificial financial market. In this model,
heterogeneous agents, behaving according to the Von Neumann and Morgenstern
utility theory, may mutually interact. A Tobin-like tax (TT) on successful
investments and a flat tax are compared to assess the effects on the agents'
wealth distribution. We carry out extensive numerical simulations in two
alternative scenarios: i) a reference scenario, where the agents keep their
utility function fixed, and ii) a focal scenario, where the agents are adaptive
and self-organize in communities, emulating their neighbours by updating their
own utility function. Specifically, the interactions among the agents are
modelled through a directed scale-free network to account for the presence of
community leaders, and the herding-like effect is tested against the reference
scenario. We observe that our model is capable of replicating the benefits and
drawbacks of the two taxation systems and that the interactions among the
agents strongly affect the wealth distribution across the communities.
Remarkably, the communities benefit from the presence of leaders with
successful trading strategies, and are more likely to increase their average
wealth. Moreover, this emulation mechanism mitigates the decrease in trading
volumes, which is a typical drawback of TTs.Comment: 18 pages, 7 figures, published in New Journal of Physic
Partial containment control over signed graphs
In this paper, we deal with the containment control problem in presence of
antagonistic interactions. In particular, we focus on the cases in which it is
not possible to contain the entire network due to a constrained number of
control signals. In this scenario, we study the problem of selecting the nodes
where control signals have to be injected to maximize the number of contained
nodes. Leveraging graph condensations, we find a suboptimal and computationally
efficient solution to this problem, which can be implemented by solving an
integer linear problem. The effectiveness of the selection strategy is
illustrated through representative simulations.Comment: 6 pages, 3 figures, accepted for presentation at the 2019 European
Control Conference (ECC19), Naples, Ital
Estimation of communication-delays through adaptive synchronization of chaos
This paper deals with adaptive synchronization of chaos in the presence of
time-varying communication-delays. We consider two bidirectionally coupled
systems that seek to synchronize through a signal that each system sends to the
other one and is transmitted with an unknown time-varying delay. We show that
an appropriate adaptive strategy can be devised that is successful in
dynamically identifying the time-varying delay and in synchronizing the two
systems. The performance of our strategy with respect to the choice of the
initial conditions and the presence of noise in the communication channels is
tested by using numerical simulations. Another advantage of our approach is
that in addition to estimating the communication-delay, the adaptive strategy
could be used to simultaneously identify other parameters, such as e.g., the
unknown time-varying amplitude of the received signal.Comment: Accepted for publication in Chaos, Solitons & Fractal