Motion planning for mobile agents, such as robots, acting in the physical world is a challenging task, which traditionally concerns safe obstacle avoidance. We are interested in p...
— This paper shows that the distributed representation found in Learning Vector Quantization (LVQ) enables reinforcement learning methods to cope with a large decision search spa...
Partially-observable Markov decision processes (POMDPs) provide a powerful model for sequential decision-making problems with partially-observed state and are known to have (appro...
A method is presented for e cient and reliable object recognition within noisy, cluttered, and occluded range images. The method is based on a strategy which hypothesizes the inte...
Symbolic techniques based on Binary Decision Diagrams (BDDs) are widely employed for reasoning about temporal properties of hardware circuits and synchronous controllers. However, ...