We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a wide variety of r...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
Creating artificial life forms through evolutionary robotics faces a “chicken and egg” problem: learning to control a complex body is dominated by problems specific to its s...
We have developed an evolutionary approach for the flexible docking that is now an important component of a rational drug design. This automatic docking tool, referred to as the G...
Computing unique input-output sequences (UIOs) from finite state machines (FSMs) is important for conformance testing in software engineering, where evolutionary algorithms (EAs)...
Background: The protein folding problem remains one of the most challenging open problems in computational biology. Simplified models in terms of lattice structure and energy func...