We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy, but may behave di erently due to position-dependent inputs. All...
In order to claim fully general intelligence in an autonomous agent, the ability to learn is one of the most central capabilities. Classical machine learning techniques have had ma...
GSAT is a randomized greedy local repair procedure that was introduced for solving propositional satis ability and constraint satisfaction problems. We present an improvement to G...
A novel technique to search for functional modules in a protein-protein interaction network is presented. The network is represented by the adjacency matrix associated with the und...
In this paper, an efficient edge-based approach, including implementation of a hardware system, for locating car license plate area from images taken under relatively complex cond...