5 citations · 11 across the 7 of their papers we have counts for
10 papers
Limited depth bandit-based strategy for Monte Carlo planning in continuous action spaces
Ricardo Quinteiro, Francisco S. Melo, Pedro A. Santos
This paper addresses the problem of optimal control using search trees. We start by considering multi-armed bandit problems with continuous action spaces and propose LD-HOO, a limi…
A Methodology for the Development of RL-Based Adaptive Traffic Signal Controllers
Guilherme S. Varela, Pedro P. Santos, Alberto Sardinha +1
This article proposes a methodology for the development of adaptive traffic signal controllers using reinforcement learning. Our methodology addresses the lack of standardization i…
A Game AI Competition to foster Collaborative AI research and development
Ana Salta, Rui Prada, Francisco S. Melo
Game AI competitions are important to foster research and development on Game AI and AI in general. These competitions supply different challenging problems that can be translated…
MHVAE: a Human-Inspired Deep Hierarchical Generative Model for Multimodal Representation Learning
Miguel Vasco, Francisco S. Melo, Ana Paiva
Humans are able to create rich representations of their external reality. Their internal representations allow for cross-modality inference, where available perceptions can induce…
Class Teaching for Inverse Reinforcement Learners
Manuel Lopes, Francisco Melo
In this paper we propose the first machine teaching algorithm for multiple inverse reinforcement learners. Specifically, our contributions are: (i) we formally introduce the proble…
Playing Games in the Dark: An approach for cross-modality transfer in reinforcement learning
Rui Silva, Miguel Vasco, Francisco S. Melo +2
In this work we explore the use of latent representations obtained from multiple input sensory modalities (such as images or sounds) in allowing an agent to learn and exploit polic…