Search Results for author: Diogo S. Carvalho

Found 4 papers, 2 papers with code

Centralized Training with Hybrid Execution in Multi-Agent Reinforcement Learning

1 code implementation12 Oct 2022 Pedro P. Santos, Diogo S. Carvalho, Miguel Vasco, Alberto Sardinha, Pedro A. Santos, Ana Paiva, Francisco S. Melo

We introduce hybrid execution in multi-agent reinforcement learning (MARL), a new paradigm in which agents aim to successfully perform cooperative tasks with any communication level at execution time by taking advantage of information-sharing among the agents.

Multi-agent Reinforcement Learning reinforcement-learning +1

Hierarchically Structured Scheduling and Execution of Tasks in a Multi-Agent Environment

no code implementations6 Mar 2022 Diogo S. Carvalho, Biswa Sengupta

In this work, we set ourselves on a problem that presents itself with a hierarchical structure: the task-scheduling, by a centralised agent, in a dynamic warehouse multi-agent environment and the execution of one such schedule, by decentralised agents with only partial observability thereof.

Management reinforcement-learning +2

The Impact of Data Distribution on Q-learning with Function Approximation

1 code implementation23 Nov 2021 Pedro P. Santos, Diogo S. Carvalho, Alberto Sardinha, Francisco S. Melo

We provide a unified theoretical and empirical analysis as to how different properties of the data distribution influence the performance of Q-learning-based algorithms.


CHARET: Character-centered Approach to Emotion Tracking in Stories

no code implementations15 Feb 2021 Diogo S. Carvalho, Joana Campos, Manuel Guimarães, Ana Antunes, João Dias, Pedro A. Santos

Autonomous agents that can engage in social interactions witha human is the ultimate goal of a myriad of applications.

Cannot find the paper you are looking for? You can Submit a new open access paper.