Incorporating Variance in Impact-Based Search

We present a simple modification to the idea of impact-based search which has proven highly effective for several applications. Impacts measure the average reduction in search space due to propagation after a variable assignment has been committed. Rather than considering the mean reduction only, we consider the idea of incorporating the variance in reduction. Experimental results show that using variance can result in improved search performance.

• Type: Journal
• Year: 2011
• Where: CP
• Authors: Serdar Kadioglu, Eoin O'Mahony, Philippe Refalo, Meinolf Sellmann
• Keywords: Artificial Intelligence, CP 2011, Search Performance, Search Space, Variable Assignment