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HOTSPOT - Human-robOt TeamS without PrecoOrdinaTion Webpage icon

Collaborators: Alberto Sardinha, Francisco S. Melo, João Ribeiro
Keywords: ad hoc teamwork, multiagent decision making


Ad hoc teamwork aims to build learning agents, such as softbots or robots, that engage in cooperative tasks with other unknown agents. A typical assumption within the decision-making algorithms is to assume that the agent does rely on any predefined coordination strategy and communication protocols. Ad hoc teamwork with human teammates is one of the most promising topics within the multiagent research community; however, it largely remains unexplored. We envisage an exciting research work that explores the challenges posed by the collaborative interaction between robots and humans to build novel decision-making algorithms, which is HOTSPOT's fundamental goal.


Optimal price subsidies under uncertainty
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Luciana Barbosa and Artur Rodrigues and Alberto Sardinha, European Journal of Operational Research, February, 2022
Ad Hoc Teamwork in the Presence of Non-Stationary Teammates
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Pedro M. Santos and João Ribeiro and Alberto Sardinha and Francisco S. Melo, 20th EPIA Conference on Artificial Intelligence, September, 2021
Helping People On The Fly: Ad Hoc Teamwork for Human-Robot Teams
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João Ribeiro and Miguel Faria and Alberto Sardinha and Francisco S. Melo, 20th EPIA Conference on Artificial Intelligence, September, 2021
MARE: an Active Learning Approach for Requirements Classification
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Cláudia Magalhães and Alberto Sardinha and João Araújo, RE@Next! track of the 29th IEEE International Requirements Engineering Conference, September, 2021
One Arm to Rule Them All: Online Learning with Multi-armed Bandits for Low-resource Conversational Agents
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Vânia Mendonça and Luísa Coheur and Alberto Sardinha, 20th EPIA Conference on Artificial Intelligence, September, 2021
Online Learning Meets Machine Translation Evaluation: Finding the Best Systems with the Least Human Effort
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Vânia Mendonça and Ricardo Rei and Luísa Coheur and Alberto Sardinha and Ana Lúcia Santos, The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), August, 2021
Use of Learning Mechanisms to Improve the Condition Monitoring of Wind Turbine Generators: A Review
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Ana Rita Nunes and Hugo Morais and Alberto Sardinha, Energies, Vol. 14, No. 21, pg. 7129, MDPI, November, 2021