This work presents a multi-agent system to trade in simultaneous auctions of related goods. The dissertation describes the multi-agent architecture, and also the analysis and development of strategies for trading in simultaneous auctions, where the purchase of combined goods is required. Some well known problems in trading were identified in order to design the architecture, such as price prediction, good allocation, decision making, reasoning under uncertainty, and demand segmentation. Each agent that composes the system is concerned with one of those trading subproblems. This makes possible to apply different computational techniques to separately solve the subproblems and then combine the solutions. The Trading Agent Competition (TAC) is used to illustrate our approach. TAC was chosen to test the developed heuristics since it presents a set of characteristics that adequately fits the problem domain. Each heurist developed was tested and had its results compared to TAC previous editions. Finally, the system shows a high performance on very competitive scenarios tested by using the TAC server environment.