Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
—Integrated Development Environments (IDEs) have come to perform a wide variety of tasks on behalf of the programmer, refactoring being a classic example. These operations have u...
Stephen R. Foster, William G. Griswold, Sorin Lern...
We introduce a novel multi-agent patrolling strategy. By assumption, the swarm of agents performing the task consists of very low capability ant-like agents. The agents have littl...
We propose a novel MRF-based model for deformable image matching (also known as registration). The deformation is described by a field of discrete variables, representing displace...
Consider a downlink multicast scenario where a base station equipped with multiple antennas wishes to simultaneously broadcast a number of signals to some given groups of users ove...