High-performance bidding agents for the continuous double auction

ABSTRACT

We develop two bidding algorithms for real-time Continuous Double Auctions (CDAs) using a variety of market rules that offer what we believe to be the strongest known performance of any published bidding strategy. Our algorithms are based on extensions of the "ZIP" (Cliff, 1997) and "GD" (Gjerstad and Dickhaut, 1998) strategies: we have made essential modifications to these strategies which enable trading multiple units in real-time markets. We test these strategies against each other and against the sniping strategy of (Rust et al., 1992) and the baseline "Zero Intelligence" strategy of (Gode and Sunder, 1992), using both a discrete-time simulator and a genuine real-time multi-agent environment called MAGENTA (Das et al., 2001). Under various market rules and limit price distributions, our modified Gjerstad-Dickhaut ("MGD") strategy outperforms the original GD, and generally ominates the other strategies.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search
          Subjects: Heuristic methods

Additional Classification:
  G. Mathematics of Computing
  G.2 DISCRETE MATHEMATICS
      G.2.1 Combinatorics
          Subjects: Combinatorial algorithms

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Multiagent systems

General Terms:
Algorithms, Design, Performance