67,484 research outputs found
Effects of Diversity on Multi-agent Systems: Minority Games
We consider a version of large population games whose agents compete for
resources using strategies with adaptable preferences. The games can be used to
model economic markets, ecosystems or distributed control. Diversity of initial
preferences of strategies is introduced by randomly assigning biases to the
strategies of different agents. We find that diversity among the agents reduces
their maladaptive behavior. We find interesting scaling relations with
diversity for the variance and other parameters such as the convergence time,
the fraction of fickle agents, and the variance of wealth, illustrating their
dynamical origin. When diversity increases, the scaling dynamics is modified by
kinetic sampling and waiting effects. Analyses yield excellent agreement with
simulations.Comment: 41 pages, 16 figures; minor improvements in content, added
references; to be published in Physical Review
Parrondo Strategies for Artificial Traders
On markets with receding prices, artificial noise traders may consider
alternatives to buy-and-hold. By simulating variations of the Parrondo
strategy, using real data from the Swedish stock market, we produce first
indications of a buy-low-sell-random Parrondo variation outperforming
buy-and-hold. Subject to our assumptions, buy-low-sell-random also outperforms
the traditional value and trend investor strategies. We measure the success of
the Parrondo variations not only through their performance compared to other
kinds of strategies, but also relative to varying levels of perfect
information, received through messages within a multi-agent system of
artificial traders.Comment: 10 pages, 4 figure
Diversity and Adaptation in Large Population Games
We consider a version of large population games whose players compete for
resources using strategies with adaptable preferences. The system efficiency is
measured by the variance of the decisions. In the regime where the system can
be plagued by the maladaptive behavior of the players, we find that diversity
among the players improves the system efficiency, though it slows the
convergence to the steady state. Diversity causes a mild spread of resources at
the transient state, but reduces the uneven distribution of resources in the
steady state.Comment: 8 pages, 3 figure
Embedding agents in business applications using enterprise integration patterns
This paper addresses the issue of integrating agents with a variety of
external resources and services, as found in enterprise computing environments.
We propose an approach for interfacing agents and existing message routing and
mediation engines based on the endpoint concept from the enterprise integration
patterns of Hohpe and Woolf. A design for agent endpoints is presented, and an
architecture for connecting the Jason agent platform to the Apache Camel
enterprise integration framework using this type of endpoint is described. The
approach is illustrated by means of a business process use case, and a number
of Camel routes are presented. These demonstrate the benefits of interfacing
agents to external services via a specialised message routing tool that
supports enterprise integration patterns
Co-evolutionnary network approach to cultural dynamics controlled by intolerance
Starting from Axelrod's model of cultural dissemination, we introduce a
rewiring probability, enabling agents to cut the links with their unfriendly
neighbors if their cultural similarity is below a tolerance parameter. For low
values of tolerance, rewiring promotes the convergence to a frozen monocultural
state. However, intermediate tolerance values prevent rewiring once the network
is fragmented, resulting in a multicultural society even for values of initial
cultural diversity in which the original Axelrod model reaches globalization
Emergence of Hierarchy on a Network of Complementary Agents
Complementarity is one of the main features underlying the interactions in
biological and biochemical systems. Inspired by those systems we propose a
model for the dynamical evolution of a system composed by agents that interact
due to their complementary attributes rather than their similarities. Each
agent is represented by a bit-string and has an activity associated to it; the
coupling among complementary peers depends on their activity. The connectivity
of the system changes in time respecting the constraint of complementarity. We
observe the formation of a network of active agents whose stability depends on
the rate at which activity diffuses in the system. The model exhibits a
non-equilibrium phase transition between the ordered phase, where a stable
network is generated, and a disordered phase characterized by the absence of
correlation among the agents. The ordered phase exhibits multi-modal
distributions of connectivity and activity, indicating a hierarchy of
interaction among different populations characterized by different degrees of
activity. This model may be used to study the hierarchy observed in social
organizations as well as in business and other networks.Comment: 13 pages, 4 figures, submitte
- …