Fasli / Shehory Agent-Mediated Electronic Commerce. Automated Negotiation and Strategy Design for Electronic Markets

Automated Negotiation and Strategy Design for Electronic Markets. AAMAS 2006 Workshop, TADA/AMEC 2006, Hakodate, Japan, May 9, 2006, Selected and Revised Papers
2007
ISBN: 978-3-540-72502-2
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 257 Seiten, eBook

Reihe: Lecture Notes in Artificial Intelligence

Thedesignandanalysisoftradingagentsandelectronictradingsystemsinwhich they are deployed involve ?nding solutions to a diverse set of problems, invo- ing individual behaviors, interaction, and collective behavior in the context of trade. A wide variety of trading scenarios and systems, and agent approaches to these, have been studied in recent years. The present volume includes a number of papers that were presented as part of the Joint International Workshop on Trading Agent Design and Analysis and Agent-Mediated Electronic Commerce which was collocated with the Autonomous Agents and Multi-agent Systems (AAMAS) Conference in Hakodate, Japan, in May 2006. The Joint TADA/AMEC Workshop brought together the two successful and well-established events of the Trading Agent Design and Analysis (TADA) and Agent-Mediated Electronic Commerce (AMEC) Workshops. The TADA series of workshops serves as a forum for presenting work on trading agent design and technologies, theoretical and empirical evaluation of strategies in complex trading scenarios as well as mechanism design. TADA also serves as the main forum for the Trading Agent Competition (TAC) research community. TAC is an annual tournament whose purpose is to stimulate research in trading agents and market mechanisms by providing a platform for agents competing in we- de?ned market scenarios (http://www. sics. se/tac). The AMEC series of wo- shops presents interdisciplinary researchon both theoretical and practical issues of agent-mediated electronic commerce ranging from the design of electronic marketplaces and e?cient protocols to behavioral aspects of agents operating in suchenvironments.

Zielgruppe

Research

Autoren/Hrsg.

Fasli, Maria

Shehory, Onn

Inhaltsverzeichnis

Evolutionary Optimization of ZIP60: A Controlled Explosion in Hyperspace.- Savings in Combinatorial Auctions Through Transformation Relationships.- On Efficient Procedures for Multi-issue Negotiation.- TacTex-05: An Adaptive Agent for TAC SCM.- Market Efficiency, Sales Competition, and the Bullwhip Effect in the TAC SCM Tournaments.- Agent Compatibility and Coalition Formation: Investigating Two Interacting Negotiation Strategies.- TAC-REM – The Real Estate Market Game: A Proposal for the Trading Agent Competition.- Evolutionary Stability of Behavioural Types in the Continuous Double Auction.- A Fast Method for Learning Non-linear Preferences Online Using Anonymous Negotiation Data.- Adaptive Pricing for Customers with Probabilistic Valuations.- Agents’ Bidding Strategies in a Combinatorial Auction Controlled Grid Environment.- A Comparison of Sequential and Simultaneous Auctions.- A Market-Pressure-Based Performance Evaluator for TAC-SCM.- Competing Sellers in Online Markets: Reserve Prices, Shill Bidding, and Auction Fees.- Robust Incentive-Compatible Feedback Payments.- The CrocodileAgent 2005: An Overview of the TAC SCM Agent.- A Fuzzy Constraint Based Model for Automated Purchase Negotiations.

Leseproben

Market Efficiency, Sales Competition, and the Bullwhip Effect in the TAC SCM Tournaments (p. 62-63)

Patrick R. Jordan, Christopher Kiekintveld, Jason Miller, and Michael P. Wellman
University of Michigan
Computer Science & Engineering
Ann Arbor, MI 48109-2121, USA

Abstract. The TAC SCM tournament is moving into its fourth year. In an e.ort to track agent progress, we present a benchmark market efficiency comparison for the tournament, in addition to prior measures of agent competency through customer bidding. Using these benchmarks we find statistically significant increases in intratournament market efficiency, whereas agents are generally decreasing in manufacturer market power. We find that agent market share and bid e.ciency have increased while the variance of average sales prices has been significantly reduced. Additionally, we test for a statistical relationship between agent pro.ts and the bullwhip effect.

1 Introduction

The supply chain management (SCM) game of the Trading Agent Competition (TAC) has provided three years of rich competition among a diverse pool of participants. We seek to evaluate progress and changes in the field of agents, and employ a variety of measures for this evaluation. These include measures of both social welfare and individual performance. We also raise the issue of bullwhip effects in the TAC SCM game, since this is a commonly discussed phenomenon in other supply chain settings. Our analysis is complicated by the strategic interactions that played out in the component procurement markets on day 0 during the early years of competition, and the subsequent changes to the game specification. We will discuss the possible e.ects of these changes at relevant points in the discussion.

In Section 3 we discuss a method for calculating market e.ciency and the division of surplus in the SCM-game. Using this measure of efficiency as a benchmark, we compare agent performance between rounds in each of the three tournaments and note interesting trends between tournaments. Section 4 gives results comparing several measures of sales performance in the customer market. Since the specification of the customer market has changed less drastically than the supply market, comparisons across tournaments on these metrics hold more weight. In Section 5 we apply a basic measure of the bullwhip effect to the SCM market and consider the relationship of this measure with market e.ciency and the division of surplus. We conclude with a summary of the results and discussion of the usefulness of the various measures.

2 TAC SCM Game

The TAC supply chain management game ([1], [2], [3]) consists of six manufacturing agents competing simultaneously in two separate markets over a period of 220 simulated days to assemble and sell PCs to customers. The manufacturing agents attempt to procure processors, motherboards, memory, and hard drives from eight suppliers at low cost, while assembling and selling 16 di.erent types of PCs to customers at a high price. Each agent is assigned an identical factory for production. Factories have a limited number of cycles each day for production. PC types vary in the number of cycles necessary for production.

Supplier prices are determined by available capacity and inventory levels. The available capacity is driven by a mean reverting random walk, while inventory is determined by past excess capacity and orders already on the books. In 2005, a reputation component was added to the supplier pricing equation. An agent’s reputation determines the order in which the agent’s request for quotes will be considered. Lower reputations result in higher price offers. The agent’s reputation is assigned by considering the ratio of requested amounts to actual amounts purchased. If that ratio is within some acceptable range (acceptable purchase ratio) the agent is designated as having a perfect reputation.

Daily customer demand is Poisson distributed about a mean for each market segment. The mean evolves according to a random walk with an evolving trend parameter. Each customer request for quote contains the requested PC type, quantity, due date, reserve price, and penalty amount. An agent receives an order if the agent issues the lowest bid that meets the reserve price. Agents pay the assigned daily penalty if they faily to deliver by the due date.