Online auctions are increasingly being used as a medium to procure goods and services. As the number of auction sites increases, however, consumers will inevitably want to track and bid in multiple auctions (with multiple protocols) in or- der to get the best deal for their desired goods. To this end, this paper reports on the development of a heuristic decision making framework that an autonomous agent can exploit to tackle the problem of bidding across multiple heterogeneous auctions. The framework enables the agent to adopt varying tactics and strategies that attempt to ensure that the user’s objectives are satis?ed. Through empirical evaluation, the agent’s performance is shown to be e?ective even when there are multiple such agents in the environment at the same time and when the agent cannot accurately determine the type of environment that it is situated in.