In this paper, a discrimination and robusmess oriented adaptive learning procedure is proposed to deal with the task of syntactic ambiguity resolution. Owing to the problem of ins...
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
This paper considers online stochastic optimization problems where time constraints severely limit the number of offline optimizations which can be performed at decision time and/...
This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. This approach is based on a direct approximation of AIXI, a Bayesian...
Joel Veness, Kee Siong Ng, Marcus Hutter, David Si...
Abstract. We consider the self-deployment problem in a ring for a network of identical sensors: starting from some initial random placement in the ring, the sensors in the network ...
Paola Flocchini, Giuseppe Prencipe, Nicola Santoro