Use of Markov Chains to Design an Agent Bidding Strategy for Continuous Double Auctions

TL;DR

This paper introduces a Markov chain-based bidding strategy for agents in continuous double auctions, enabling more effective decision-making under uncertainty and outperforming other heuristics in many scenarios.

Contribution

The paper presents a novel Markov chain model for agent bidding strategies in continuous double auctions, improving decision-making efficiency and effectiveness.

Findings

Performs well in seller's markets with many buy offers

Outperforms other heuristic strategies in most experiments

Effective approximation of optimal bidding performance

Abstract

As computational agents are developed for increasingly complicated e-commerce applications, the complexity of the decisions they face demands advances in artificial intelligence techniques. For example, an agent representing a seller in an auction should try to maximize the seller's profit by reasoning about a variety of possibly uncertain pieces of information, such as the maximum prices various buyers might be willing to pay, the possible prices being offered by competing sellers, the rules by which the auction operates, the dynamic arrival and matching of offers to buy and sell, and so on. A naive application of multiagent reasoning techniques would require the seller's agent to explicitly model all of the other agents through an extended time horizon, rendering the problem intractable for many realistically-sized problems. We have instead devised a new strategy that an agent can use to determine its bid price based on a more tractable Markov chain model of the auction process. We have experimentally identified the conditions under which our new strategy works well, as well as how well it works in comparison to the optimal performance the agent could have achieved had it known the future. Our results show that our new strategy in general performs well, outperforming other tractable heuristic strategies in a majority of experiments, and is particularly effective in a 'seller?s market', where many buy offers are available.