Open AccessThe 2002 Trading Agent Competition: An Overview of Agent Strategies
Author(s) -
Greenwald Amy
Publication year - 2003
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v24i1.1691
Subject(s) - competition (biology) , heuristic , computer science , domain (mathematical analysis) , multi agent system , artificial intelligence , operations research , management science , engineering , mathematics , mathematical analysis , ecology , biology
This article summarizes 16 agent strategies that were designed for the 2002 Trading Agent Competition. Agent architects use numerous general‐purpose AI techniques, including machine learning, planning, partially observable Markov decision processes, Monte Carlo simulations, and multiagent systems. Ultimately, the most successful agents were primarily heuristic based and domain specific.