41,024 research outputs found
From supply chains to demand networks. Agents in retailing: the electrical bazaar
A paradigm shift is taking place in logistics. The focus is changing from operational effectiveness to adaptation. Supply Chains will develop into networks that will adapt to consumer demand in almost real time. Time to market, capacity of adaptation and enrichment of customer experience seem to be the key elements of this new paradigm. In this environment emerging technologies like RFID (Radio Frequency ID), Intelligent Products and the Internet, are triggering a reconsideration of methods, procedures and goals. We present a Multiagent System framework specialized in retail that addresses these changes with the use of rational agents and takes advantages of the new market opportunities. Like in an old bazaar, agents able to learn, cooperate, take advantage of gossip and distinguish between collaborators and competitors, have the ability to adapt, learn and react to a changing environment better than any other structure. Keywords: Supply Chains, Distributed Artificial Intelligence, Multiagent System.Postprint (published version
The Predictive Power of Zero Intelligence in Financial Markets
Standard models in economics stress the role of intelligent agents who
maximize utility. However, there may be situations where, for some purposes,
constraints imposed by market institutions dominate intelligent agent behavior.
We use data from the London Stock Exchange to test a simple model in which zero
intelligence agents place orders to trade at random. The model treats the
statistical mechanics of order placement, price formation, and the accumulation
of revealed supply and demand within the context of the continuous double
auction, and yields simple laws relating order arrival rates to statistical
properties of the market. We test the validity of these laws in explaining the
cross-sectional variation for eleven stocks. The model explains 96% of the
variance of the bid-ask spread, and 76% of the variance of the price diffusion
rate, with only one free parameter. We also study the market impact function,
describing the response of quoted prices to the arrival of new orders. The
non-dimensional coordinates dictated by the model approximately collapse data
from different stocks onto a single curve. This work is important from a
practical point of view because it demonstrates the existence of simple laws
relating prices to order flows, and in a broader context, because it suggests
that there are circumstances where institutions are more important than
strategic considerations
Characteristics of Real Futures Trading Networks
Futures trading is the core of futures business, and it is considered as one
of the typical complex systems. To investigate the complexity of futures
trading, we employ the analytical method of complex networks. First, we use
real trading records from the Shanghai Futures Exchange to construct futures
trading networks, in which nodes are trading participants, and two nodes have a
common edge if the two corresponding investors appear simultaneously in at
least one trading record as a purchaser and a seller respectively. Then, we
conduct a comprehensive statistical analysis on the constructed futures trading
networks. Empirical results show that the futures trading networks exhibit
features such as scale-free behavior with interesting odd-even-degree
divergence in low-degree regions, small-world effect, hierarchical
organization, power-law betweenness distribution, disassortative mixing, and
shrinkage of both the average path length and the diameter as network size
increases. To the best of our knowledge, this is the first work that uses real
data to study futures trading networks, and we argue that the research results
can shed light on the nature of real futures business.Comment: 18 pages, 9 figures. Final version published in Physica
Evolution of a supply chain management game for the trading agent competition
TAC SCM is a supply chain management game for the Trading Agent Competition (TAC). The purpose of TAC is to spur high quality research into realistic trading agent problems. We discuss TAC and TAC SCM: game and competition design, scientific impact, and lessons learnt
Implementing an Agent Trade Server
An experimental server for stock trading autonomous agents is presented and
made available, together with an agent shell for swift development. The server,
written in Java, was implemented as proof-of-concept for an agent trade server
for a real financial exchange.Comment: 14 pages, 7 figures, intended for B/W printin
Building an Artificial Stock Market Populated by Reinforcement-Learning Agents
In this paper we propose an artificial stock market model based on interaction of heterogeneous agents whose forward-looking behaviour is driven by the reinforcement learning algorithm combined with some evolutionary selection mechanism. We use the model for the analysis of market self-regulation abilities, market efficiency and determinants of emergent properties of the financial market. Distinctive and novel features of the model include strong emphasis on the economic content of individual decision making, application of the Q-learning algorithm for driving individual behaviour, and rich market setup.agent-based financial modelling, artificial stock market, complex dynamical system, emergent properties, market efficiency, agent heterogeneity, reinforcement learning
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