In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. We introduce a hierarchical multi-a...
Rajbala Makar, Sridhar Mahadevan, Mohammad Ghavamz...
Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to potential ap...
We present a novel, efficient, initializationfree approach to the problem of epipolar geometry estimation, by formulating it as one of hyperplane inference from a sparse and noisy...
In a fundamental paradigm shift in system design, entire systems are being built on a single chip, using multiple embedded cores. Though the newest system design methodology has s...
Abstract. A formal, representation-independent form of a memetic algorithm-a genetic algorithm incorporating local search--is introduced. A generalisedform of N-point crossover is ...