Agent-based simulation of dynamic online auctions

Mizuta, Hideyuki; Steiglitz, K.

doi:10.1109/wsc.2000.899168

Cited by 28 publications

(19 citation statements)

References 5 publications

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“…Similar "onepass" issues arise in on-line auctions and it is necessary to develop and model bidding strategies in such situations, taking into account the effect of uncertainty, subjective judgments about the value of an item, learning in repeated auctions, etc. [290].…”

Section: Streaming Data In Game Theorymentioning

confidence: 99%

Computer science and decision theory

Roberts

2008

Ann Oper Res

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This paper reviews applications in computer science that decision theorists have addressed for years, discusses the requirements posed by these applications that place great strain on decision theory/social science methods, and explores applications in the social and decision sciences of newer decision-theoretic methods developed with computer science applications in mind. The paper deals with the relation between computer science and decision-theoretic methods of consensus, with the relation between computer science and game theory and decisions, and with "algorithmic decision theory."

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Section: Streaming Data In Game Theorymentioning

confidence: 99%

Computer science and decision theory

Roberts

2008

Ann Oper Res

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“…Scholars have, however, simulated the effectiveness of trading agents (Haddawy et al, 2004), investigating the effectiveness of auctions (Bohte et al, 2001;Mizuta and Steiglitz, 2000;Mizuta and Yamagata, 2001), buyer coalition schemes (Yamamoto and Sycara, 2001) and trade brokering (Alkemade et al, 2003). Agents mimic brokering by representing an exchange of information between parties to a decision.…”

Section: Introductionmentioning

confidence: 99%

Regulators as agents: Modelling personality and power as evidence is brokered to support decisions on environmental risk

Davies

Kendall

Soane

et al. 2014

Science of The Total Environment

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Complex regulatory decisions about risk rely on the brokering of evidence between providers and recipients, and involve personality and power relationships that influence the confidence that recipients may place in the sufficiency of evidence and, therefore, the decision outcome. We explore these relationships in an agent-based model; drawing on concepts from environmental risk science, decision psychology and computer simulation. A two-agent model that accounts for the sufficiency of evidence is applied to decisions about salt intake, animal carcass disposal and radioactive waste. A dynamic version of the model assigned personality traits to agents, to explore their receptivity to evidence. Agents with 2 'aggressor' personality sets were most able to imbue fellow agents with enhanced receptivity (with 'avoider' personality sets less so) and clear confidence in the sufficiency of evidence.In a dynamic version of the model, when both recipient and provider were assigned the 'aggressor' personality set, this resulted in 10 successful evidence submissions in 71 days, compared with 96 days when both agents were assigned the 'avoider' personality set. These insights suggest implications for improving the efficiency and quality of regulatory decision making by understanding the role of personality and power.

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“…We applied ZASE to the agent-based auction simulation described in [8]. In the simulation, there are two types of bidder agents: An EarlyBidder or a Sniper.…”

Section: An Application Examplementioning

confidence: 99%

“…This is a Vickrey auction, so the auction model is that the agent bidding at the highest price wins, but only pays a price equal to the second highest bid. In [8], the number of agents was fixed at ten. We ran six trials for 10^x agents, with x ranging from 1 to 6 (10 to 1,000,000 agents).…”

Section: An Application Examplementioning

confidence: 99%

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A Platform for Massive Agent-Based Simulation and Its Evaluation

Yamamoto

Mizuta

Massively Multi-Agent Technology

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There are many studies on ABS and several frameworks for ABS have already been published. However, there are few frameworks that can enable agent-based simulation using large numbers of agents. We have been developing a Java-based platform for Massive Agent-Based Simulation (MABS) called "Zillions of Agents-based Simulation Environment" or ZASE. The purpose of ZASE is to develop MABS applications on multiple computers. ZASE is designed to host over millions of agents. We introduce ZASE in this paper. We evaluated ZASE for the agent-based auction simulation where the number of agents varied from ten to a million. The results indicate that the number of agents affects the final bid prices and their distributions. Performance measurement results on both an SMP computer environment and a multiple-computer environment are shown.

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Agent-based simulation of dynamic online auctions

Cited by 28 publications

References 5 publications

Computer science and decision theory

Computer science and decision theory

Regulators as agents: Modelling personality and power as evidence is brokered to support decisions on environmental risk

A Platform for Massive Agent-Based Simulation and Its Evaluation

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