The Agent-Based Double Auction Markets: 15 Years On

@inproceedings{Chen2008TheAD,
  title={The Agent-Based Double Auction Markets: 15 Years On},
  author={Shu-Heng Chen and Chung-Ching Tai},
  booktitle={WCSS},
  year={2008}
}
Novelties discovering as a source of constant change is the essence of economics. However, most economic models do not have the kind of novelties-discovering agents required for constant changes. This silence was broken by Andrews and Prager 15 years ago when they placed GP (genetic programming)-driven agents in the double auction market. The work was, however, neither economically well interpreted nor complete; hence the silence remains in economics. In this article, we revisit their model and… 

Zero-intelligence agents looking for a job

We study a simple agent-based model of a decentralized matching market game in which agents (workers or job seekers) make proposals to other agents (firms) in order to be matched to a position within

Agents learned, but do we? Knowledge discovery using the agent-based double auction markets

TLDR
An autonomous-agent-inspired economic theory with regard to the optimal procrastination is derived from first dispatch autonomous agents, built by genetic programming, to double auction markets.

Herbert Simon and Agent-Based Computational Economics

Herbert Simon was a quintessential interdisciplinary scholar who made pioneering contributions concerning the notion of bounded rationality, built models based on it, and made important advances in

Granularity in Economic Decision Making: An Interdisciplinary Review

TLDR
The review will cover the perspectives from different disciplines, including psychology, cognitive science, complex science, and behavioral and experimental economics, and various learning models frequently used in agent-based computational economics, such as reinforcement learning and evolutionary computation.

Strategies in the Tallinn School Choice Mechanism

In the first 20 years of the market economy in Estonia, the public school market was decentralised in Tallinn. Recently, a hybrid market was established by centralising the school allocations to

Toward an Autonomous-Agents Inspired Economic Analysis

This paper demonstrates the potential role of autonomous agents in economic theory. We first dispatch autonomous agents, built by genetic programming, to double auction markets. We then study the

Agent-based modeling of knowledge sharing and used-car market

This paper resents a preliminary Agent-based Model for modeling the interaction between knowledge sharing repository, such as forum or feedback system, and used-car market, and introduces knowledge

Price Dynamics in an Order-Driven Market with Bayesian Learning

TLDR
In this model, continuous Bayesian learning is introduced to describe the dynamics of self-adjusting learning mechanism of agents, which can result in some important stylized facts of limit order markets.

Algorithmic Social Sciences Research Unit

Stephen Wolfram’s A New Kind of Science should have made a greater impact in economics at least in its theorising and computational modes than it seems to have. There are those who subscribe to

References

SHOWING 1-10 OF 27 REFERENCES

Agent-Based Models of Financial Markets: A Comparison with Experimental Markets

We construct a computer simulation of a repeated double-auction market, designed to match those in experimental-market settings with human subjects, to model complex interactions among

Co-Evolving Trading Strategies to Analyze Bounded Rationality in Double Auction Markets

We investigate double-auction (DA) market behavior under traders with different degrees of rationality (intelligence or cognitive ability). The rationality of decision making is implemented using

Zero is Not Enough: On The Lower Limit of Agent Intelligence For Continuous Double Auction Markets†

agent continuous double auction, trade Gode and Sunder's (1993) results from using "zero-intelligence" (ZI) traders, that act randomly within a structured market, appear to imply that convergence to

On the convergence of genetic learning in a double auction market

Trading Restrictions, Price Dynamics and allocative Efficiency in Double Auction Markets: Analysis Based on Agent-Based Modeling and Simulations

TLDR
The results are largely consistent with the stylized facts observed in experimental economics with human subjects and from the amelioration of price deviation and allocative efficiency, the effect of learning is vividly seen.

Toward an Agent-Based Computational Modeling of Bargaining Strategies in Double Auction Markets with Genetic Programming

Using genetic programming, this paper proposes an agent-based computational modeling of double auction (DA) markets in the sense that a DA market is modeled as an evolving market of autonomous

Price Formation in Double Auctions We Thank Vernon Smith and Arlington Williams for Providing Data for Comparison with the Model in This Paper. We Thank

We develop a model of information processing and strategy choice for participants in a double auction. Sellers in this model form beliefs that an o er will be accepted by some buyer. Similarly,

Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality

We report market experiments in which human traders are replaced by "zero-intelligence" programs that submit random bids and offers. Imposing a budget constraint (i.e., not permitting traders to sell