Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Abstract— The mapping and localization problems have received considerable attention in robotics recently. The exploration problem that drives mapping has started to generate sim...
Reinforcement learning (RL) algorithms attempt to assign the credit for rewards to the actions that contributed to the reward. Thus far, credit assignment has been done in one of t...
The potentially catastrophic impact of a bioterrorist attack makes developing effective detection methods essential for public health. In the case of anthrax attack, a delay of ho...
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...