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...
Evolution of neural networks, as implemented in NEAT, has proven itself successful on a variety of low-level control problems such as pole balancing and vehicle control. Nonethele...
— Development in new radio technologies and increase in user demands are driving the deployment of a wide array of wireless networks, ranging from 802.11 networks in the local ar...
- Current industry trends in system design -- multiple clocks, clocks with arbitrary frequency ratios, multi-phased clocks, gated clocks, and level-sensitive latches, combined with...
Soft-error induced reliability problems have become a major challenge in designing new generation microprocessors. Due to the on-chip caches' dominant share in die area and tr...