Evolving Best-Response Strategies for Market-Driven Agents Using Aggregative Fitness GA.

The article focuses on the use of aggregative fitness genetic algorithm (AFGA) to develop the most effective bargaining strategies of market-driven agents (MDAs) in the U.S. It presents a series of experiments that are formulated to determine the most successful strategies and compare the performance of MDAs against GA-MDAs. In addition, it compares the strengths and weaknesses of GA-MDAs with related systems. The authors concluded that GA-MDAs achieved higher expected utilities and higher success rates and they reached agreements with fewer negotiation rounds than MDAs.