Zobrazeno 1 - 10
of 93
pro vyhledávání: '"Francisco S Melo"'
Publikováno v:
International Journal of Serious Games, Vol 5, Iss 3 (2018)
This paper provides a short introduction to the field of machine learning for interactive pedagogical systems. Departing from different examples encountered in interactive pedagogical systems—such as intelligent tutoring systems or serious games—
Externí odkaz:
https://doaj.org/article/830711eeb391419680275d10f124056f
Publikováno v:
Frontiers in Robotics and AI, Vol 9 (2022)
Social robots have been shown to be promising tools for delivering therapeutic tasks for children with Autism Spectrum Disorder (ASD). However, their efficacy is currently limited by a lack of flexibility of the robot’s social behavior to successfu
Externí odkaz:
https://doaj.org/article/b1c4690c892d4e3eab0a225b59b38f9c
Autor:
Francisco S. Melo, Manuel Lopes
Publikováno v:
Frontiers in Artificial Intelligence, Vol 4 (2021)
In this paper, we propose the first machine teaching algorithm for multiple inverse reinforcement learners. As our initial contribution, we formalize the problem of optimally teaching a sequential task to a heterogeneous class of learners. We then co
Externí odkaz:
https://doaj.org/article/a32b7f8257de4e87aeb6a34bec208ad7
Publikováno v:
International Journal of Social Robotics. 15:27-36
Publikováno v:
Operations Research Perspectives, Vol 6, Iss , Pp - (2019)
This paper discusses the problem of room usage optimization for university timetables: given a timetable, we want to optimize the room occupation by determining the events allocated to each room, while ensuring that the rooms have enough capacity to
Externí odkaz:
https://doaj.org/article/327c61a72dd6425988759ab640b0ab4e
Publikováno v:
Topics in cognitive scienceReferences.
Creating effective teamwork between humans and robots involves not only addressing their performance as a team but also sustaining the quality and sense of unity among teammates, also known as cohesion. This paper explores the research problem of: ho
Publikováno v:
Proceedings of the International Conference on Automated Planning and Scheduling. 29:455-463
This paper analyzes, from theoretical and algorithmic perspectives, a class of problems recently introduced in the literature of Markov decision processes—configurable Markov decision processes. In this new class of problems we jointly optimize the
Our research effort takes inspiration from human social learning mechanisms to focus on situations in which an expert guides a learner through explanations. The proposed approach incorporates explanations into maximum likelihood inverse reinforcement
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::345a1dc6c63d296fd94bde627bbef8a9
https://doi.org/10.21203/rs.3.rs-1439366/v1
https://doi.org/10.21203/rs.3.rs-1439366/v1
Publikováno v:
Progress in Artificial Intelligence ISBN: 9783031164736
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f73ac476d0a8dfecf551fa7126a7c6c
https://doi.org/10.1007/978-3-031-16474-3_36
https://doi.org/10.1007/978-3-031-16474-3_36
Autor:
Alberto Sardinha, Ruy Luiz Milidiú, Francisco S. Melo, Julio Cesar Duarte, Sérgio Colcher, Luis Müller Henriques, João G. Ribeiro
Ad hoc teamwork is a research topic in multi-agent systems whereby an agent (the "ad hoc agent") must successfully collaborate with a set of unknown agents (the "teammates") without any prior coordination or communication protocol. However, research
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed534d4ff327868389d97b29947794e5
https://doi.org/10.36227/techrxiv.17026013.v1
https://doi.org/10.36227/techrxiv.17026013.v1