M
Mauricio Cecilio Magnaguagno
Researcher at Pontifícia Universidade Católica do Rio Grande do Sul
Publications - 18
Citations - 129
Mauricio Cecilio Magnaguagno is an academic researcher from Pontifícia Universidade Católica do Rio Grande do Sul. The author has contributed to research in topics: Domain knowledge & Automated planning and scheduling. The author has an hindex of 6, co-authored 17 publications receiving 96 citations.
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Proceedings ArticleDOI
Goal Recognition in Latent Space
Leonardo Amado,Ramon Fraga Pereira,João Paulo Aires,Mauricio Cecilio Magnaguagno,Roger Granada,Felipe Meneguzzi +5 more
TL;DR: This work combines goal recognition techniques from automated planning, and deep autoencoders to carry out unsupervised learning to generate domain theories from data streams and use the resulting domain theories to deal with incomplete and noisy observations.
Posted Content
LSTM-Based Goal Recognition in Latent Space
Leonardo Amado,João Paulo Aires,Felipe Meneguzzi,Mauricio Cecilio Magnaguagno,Roger Granada,Ramon Fraga Pereira +5 more
TL;DR: This work develops an approach that leverages advances in recurrent neural networks to perform goal recognition as a classification task, using encoded plan traces for training, and discusses under which conditions this approach is superior to previous ones.
Proceedings Article
Towards Online Goal Recognition Combining Goal Mirroring and Landmarks
TL;DR: This work develops an online approach to goal recognition which operates in both continuous and discrete domains using a combination of Goal Mirroring and a generalized notion of landmarks adapted from the planning literature.
Journal ArticleDOI
GoCo: planning expressive commitment protocols
Felipe Meneguzzi,Mauricio Cecilio Magnaguagno,Munindar P. Singh,Pankaj R. Telang,Neil Yorke-Smith +4 more
TL;DR: This article develops a multi-agent plan in the form of a commitment protocol that allows the agents to coordinate in a flexible manner, retaining their autonomy in terms of the goals they adopt so long as their actions adhere to the commitments they have made.
Journal ArticleDOI
Team PUCRS: a decentralised multi-agent solution for the agents in the city scenario
Rafael C. Cardoso,Ramon Fraga Pereira,Guilherme Krzisch,Mauricio Cecilio Magnaguagno,Tulio L. Basegio,Felipe Meneguzzi +5 more
TL;DR: The 2016 edition of the multi-agent programming contest used the agents in the city as its new scenario, which consisted on the execution of various logistics tasks within a realistic city topology using a number of different vehicle types.