The Trading Agent CAT Market Design Competition aims to implement intelligent adaptive systems for controlling the operations of an abstract double auction market on a day to day basis whereby simulated software trading agents participate to buy and sell according to special constraints and rules. In the competition, the given agent, called market specialist, runs in direct competition to other market agents in a highly uncertain environment which is characterized by lack of knowledge of the exact parameters of traders' strategies, their cost and budget preferences and the behavior of competing markets. In this paper, we will present a novel agent which is based on the use type-2 fuzzy systems to implement the agent charging policy. Through several experiments, it will be shown that the type-2 fuzzy based agent will be able to outperform the existing agents as well as its type-1 counterparts under high uncertainty conditions.
