In previous work we have developed a syntactic reduction of repeated reachability to reachability for finite state systems. This may lead to simpler and more uniform proofs for mo...
How can we get such reliable behavior from the mind when the brain is made up of such unreliable elements as neurons? We propose that the answer is related to the emergence of stab...
The existing reinforcement learning approaches have been suffering from the curse of dimension problem when they are applied to multiagent dynamic environments. One of the typical...
—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
We introduce a formalism for optimal sensor parameter selection for iterative state estimation in static systems. Our optimality criterion is the reduction of uncertainty in the st...