There is an increasing interest in complex automated negotiations, where agents negotiate about multiple, interdependent issues and agent utility functions exhibit low autocorrelation. In these scenarios, the negotiation mechanisms used to find agreement solutions among agents tend to fail due to the complexity of agents’ preference spaces, and this tendency increases as the degree of autocorrelation decreases. In this paper, we propose an automated negotiation model specially tailored for highly uncorrelated utility spaces based on weighted constraints. The model relies on a mediated, auction-based interaction protocol and a set of heuristic mechanisms for bidding and deal identification. To address the challenges raised by highly uncorrelated utility spaces, we propose to use a quality factor, which allows agents to balance utility and deal probability when placing their bids or when searching for agreement regions among these bids. Experiments show that the proposed negotiation model achieves high optimality results and low failure rates even in negotiation scenarios involving highly uncorrelated utility spaces, thus outperforming previous approaches.