27 citations · 35 across the 4 of their papers we have counts for
4 papers
A Greedy Approximation of Bayesian Reinforcement Learning with Probably Optimistic Transition Model
Kenji Kawaguchi, Mauricio Araya
Bayesian Reinforcement Learning (RL) is capable of not only incorporating domain knowledge, but also solving the exploration-exploitation dilemma in a natural way. As Bayesian RL i…
Near-Optimal BRL using Optimistic Local Transitions
Mauricio Araya, Olivier Buffet, Vincent Thomas
Model-based Bayesian Reinforcement Learning (BRL) allows a found formalization of the problem of acting optimally while facing an unknown environment, i.e., avoiding the exploratio…
Combining a Probabilistic Sampling Technique and Simple Heuristics to solve the Dynamic Path Planning Problem
Nicolas A. Barriga, Mauricio Araya-López, Mauricio Solar
Probabilistic sampling methods have become very popular to solve single-shot path planning problems. Rapidly-exploring Random Trees (RRTs) in particular have been shown to be very…
A Multi-stage Probabilistic Algorithm for Dynamic Path-Planning
Nicolas A. Barriga, Mauricio Araya-López
Probabilistic sampling methods have become very popular to solve single-shot path planning problems. Rapidly-exploring Random Trees (RRTs) in particular have been shown to be effic…