1 citations · 3 across the 8 of their papers we have counts for
9 papers
Evaluating XAI Support From A Hierarchical Reinforcement Learning Policy in Human-Agent Collaboration
Mateus Levi Simões Fernandes, Alberto Sardinha
Explainable AI (XAI) has shown promise for human-agent collaboration, yet results rely on hand-crafted policies in custom environments, limiting generalizability to state-of-the-ar…
Learning to Perceive in Deep Model-Free Reinforcement Learning
Gonçalo Querido, Alberto Sardinha, Francisco S. Melo
This work proposes a novel model-free Reinforcement Learning (RL) agent that is able to learn how to complete an unknown task having access to only a part of the input observation.…
Centralized Training with Hybrid Execution in Multi-Agent Reinforcement Learning
Pedro P. Santos, Diogo S. Carvalho, Miguel Vasco +4
We introduce hybrid execution in multi-agent reinforcement learning (MARL), a new paradigm in which agents aim to successfully complete cooperative tasks with arbitrary communicati…
Learning to Cooperate with Completely Unknown Teammates
Alexandre Neves, Alberto Sardinha
A key goal of ad hoc teamwork is to develop a learning agent that cooperates with unknown teams, without resorting to any pre-coordination protocol. Despite a vast number of ad hoc…
Perceive, Represent, Generate: Translating Multimodal Information to Robotic Motion Trajectories
Fábio Vital, Miguel Vasco, Alberto Sardinha +1
We present Perceive-Represent-Generate (PRG), a novel three-stage framework that maps perceptual information of different modalities (e.g., visual or sound), corresponding to a seq…
Assisting Unknown Teammates in Unknown Tasks: Ad Hoc Teamwork under Partial Observability
João G. Ribeiro, Cassandro Martinho, Alberto Sardinha +1
In this paper, we present a novel Bayesian online prediction algorithm for the problem setting of ad hoc teamwork under partial observability (ATPO), which enables on-the-fly colla…
Online Learning Meets Machine Translation Evaluation: Finding the Best Systems with the Least Human Effort
Vânia Mendonça, Ricardo Rei, Luisa Coheur +2
In Machine Translation, assessing the quality of a large amount of automatic translations can be challenging. Automatic metrics are not reliable when it comes to high performing sy…
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…
Feed-in Tariff Contract Schemes and Regulatory Uncertainty
Luciana Barbosa, Cláudia Nunes, Artur Rodrigues +1
This paper presents a novel analysis of two feed-in tariffs (FIT) under market and regulatory uncertainty, namely a sliding premium with cap and floor and a minimum price guarantee…