Abstract— We study multi-robot routing problems (MRLDR) where a team of robots has to visit a set of given targets with linear decreasing rewards over time, such as required for ...
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
A simple extension of the critical path method is presented which allows more accurate optimization of circuits with level-sensitive latches. The extended formulation provides a s...
We present new algorithms for inverse optimal control (or inverse reinforcement learning, IRL) within the framework of linearlysolvable MDPs (LMDPs). Unlike most prior IRL algorit...
Long design cycles due to the inability to predict silicon realities is a well-known problem that plagues analog/RF integrated circuit product development. As this problem worsens...