91,224 research outputs found
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
An investigation of the trading agent competition : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University, Albany, New Zealand
The Internet has swept over the whole world. It is influencing almost every aspect of society. The blooming of electronic commerce on the back of the Internet further increases globalisation and free trade. However, the Internet will never reach its full potential as a new electronic media or marketplace unless agents are developed. The trading Agent Competition (TAC), which simulates online auctions, was designed to create a standard problem in the complex domain of electronic marketplaces and to inspire researchers from all over the world to develop distinctive software agents to a common exercise. In this thesis, a detailed study of intelligent software agents and a comprehensive investigation of the Trading Agent Competition will be presented. The design of the Risker Wise agent and a fuzzy logic system predicting the bid increase of the hotel auction in the TAC game will be discussed in detail
An Investigation Report on Auction Mechanism Design
Auctions are markets with strict regulations governing the information
available to traders in the market and the possible actions they can take.
Since well designed auctions achieve desirable economic outcomes, they have
been widely used in solving real-world optimization problems, and in
structuring stock or futures exchanges. Auctions also provide a very valuable
testing-ground for economic theory, and they play an important role in
computer-based control systems.
Auction mechanism design aims to manipulate the rules of an auction in order
to achieve specific goals. Economists traditionally use mathematical methods,
mainly game theory, to analyze auctions and design new auction forms. However,
due to the high complexity of auctions, the mathematical models are typically
simplified to obtain results, and this makes it difficult to apply results
derived from such models to market environments in the real world. As a result,
researchers are turning to empirical approaches.
This report aims to survey the theoretical and empirical approaches to
designing auction mechanisms and trading strategies with more weights on
empirical ones, and build the foundation for further research in the field
ATTac-2000: An Adaptive Autonomous Bidding Agent
The First Trading Agent Competition (TAC) was held from June 22nd to July
8th, 2000. TAC was designed to create a benchmark problem in the complex domain
of e-marketplaces and to motivate researchers to apply unique approaches to a
common task. This article describes ATTac-2000, the first-place finisher in
TAC. ATTac-2000 uses a principled bidding strategy that includes several
elements of adaptivity. In addition to the success at the competition, isolated
empirical results are presented indicating the robustness and effectiveness of
ATTac-2000's adaptive strategy
Capturing benefits from water entitlement trade in salinity affected areas: A role for trading houses?
While there is potential for substantial benefits from water entitlement trade, external effects such as salinity may mean that traders cannot capture these benefits. This paper demonstrates that by creating a trading house as a single seller of water entitlements, with trade profits distributed to buyers, it is possible to achieve an allocation of entitlements which gives a social outcome higher than that possible from atomistic competition for entitlements. Such an outcome may be comparable to an optimally set uniform charge for water entitlements, but the trading house mechanism has the advantage that it makes use of trade to generate information on the optimal level of charging in the presence of salinity.Resource /Energy Economics and Policy,
Unique Equilibrium in Two-Part Tariff Competition between Two-Sided Platforms
Two-sided market models in which platforms compete via two-part tariffs, i.e. a subscription and a per-transaction fee, are often plagued by a continuum of equilibria. This paper augments existing models by allowing for heterogeneous rading behavior of agents on both sides. We show that this simple method yields a unique equilibrium even in the limit as the heterogeneity vanishes. In case of competitive bottlenecks we find that in this equilibrium platforms benefit from the possibility to price discriminate if per-transaction costs are relatively large. This is the case because two-part tariffs allow platforms to better distribute these costs among the two sides. Under two-sided single-homing price discrimination hurts platforms if per-transaction fees can be negative
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
Nash Social Welfare Approximation for Strategic Agents
The fair division of resources is an important age-old problem that has led
to a rich body of literature. At the center of this literature lies the
question of whether there exist fair mechanisms despite strategic behavior of
the agents. A fundamental objective function used for measuring fair outcomes
is the Nash social welfare, defined as the geometric mean of the agent
utilities. This objective function is maximized by widely known solution
concepts such as Nash bargaining and the competitive equilibrium with equal
incomes. In this work we focus on the question of (approximately) implementing
the Nash social welfare. The starting point of our analysis is the Fisher
market, a fundamental model of an economy, whose benchmark is precisely the
(weighted) Nash social welfare. We begin by studying two extreme classes of
valuations functions, namely perfect substitutes and perfect complements, and
find that for perfect substitutes, the Fisher market mechanism has a constant
approximation: at most 2 and at least e1e. However, for perfect complements,
the Fisher market does not work well, its bound degrading linearly with the
number of players.
Strikingly, the Trading Post mechanism---an indirect market mechanism also
known as the Shapley-Shubik game---has significantly better performance than
the Fisher market on its own benchmark. Not only does Trading Post achieve an
approximation of 2 for perfect substitutes, but this bound holds for all
concave utilities and becomes arbitrarily close to optimal for Leontief
utilities (perfect complements), where it reaches for every
. Moreover, all the Nash equilibria of the Trading Post mechanism
are pure for all concave utilities and satisfy an important notion of fairness
known as proportionality
A Grey-Box Approach to Automated Mechanism Design
Auctions play an important role in electronic commerce, and have been used to
solve problems in distributed computing. Automated approaches to designing
effective auction mechanisms are helpful in reducing the burden of traditional
game theoretic, analytic approaches and in searching through the large space of
possible auction mechanisms. This paper presents an approach to automated
mechanism design (AMD) in the domain of double auctions. We describe a novel
parametrized space of double auctions, and then introduce an evolutionary
search method that searches this space of parameters. The approach evaluates
auction mechanisms using the framework of the TAC Market Design Game and
relates the performance of the markets in that game to their constituent parts
using reinforcement learning. Experiments show that the strongest mechanisms we
found using this approach not only win the Market Design Game against known,
strong opponents, but also exhibit desirable economic properties when they run
in isolation.Comment: 18 pages, 2 figures, 2 tables, and 1 algorithm. Extended abstract to
appear in the proceedings of AAMAS'201
Walverine: A Walrasian Trading Agent
TAC-02 was the third in a series of Trading Agent Competition events fostering research in automating trading strategies by showcasing alternate approaches in an open-invitation market game. TAC presents a challenging travel-shopping scenario where agents must satisfy client preferences for complementary and substitutable goods by interacting through a variety of market types. Michigan's entry, Walverine, bases its decisions on a competitive (Walrasian) analysis of the TAC travel economy. Using this Walrasian model, we construct a decision-theoretic formulation of the optimal bidding problem, which Walverine solves in each round of bidding for each good. Walverine's optimal bidding approach, as well as several other features of its overall strategy, are potentially applicable in a broad class of trading environments.trading agent, trading competition, tatonnement, competitive equilibrium
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