Zobrazeno 1 - 10
of 477
pro vyhledávání: '"Pereira, Andre P"'
Intelligent assistants powered by Large Language Models (LLMs) can generate program and test code with high accuracy, boosting developers' and testers' productivity. However, there is a lack of studies exploring LLMs for testing Web APIs, which const
Externí odkaz:
http://arxiv.org/abs/2409.03838
Autor:
Irfan, Bahar, Miniota, Jura, Thunberg, Sofia, Lagerstedt, Erik, Kuoppamäki, Sanna, Skantze, Gabriel, Pereira, André
Understanding user enjoyment is crucial in human-robot interaction (HRI), as it can impact interaction quality and influence user acceptance and long-term engagement with robots, particularly in the context of conversations with social robots. Howeve
Externí odkaz:
http://arxiv.org/abs/2405.01354
Goal Recognition is the task by which an observer aims to discern the goals that correspond to plans that comply with the perceived behavior of subject agents given as a sequence of observations. Research on Goal Recognition as Planning encompasses r
Externí odkaz:
http://arxiv.org/abs/2404.07934
Autor:
Messa, Frederico, Pereira, André Grahl
Fully-observable non-deterministic (FOND) planning is at the core of artificial intelligence planning with uncertainty. It models uncertainty through actions with non-deterministic effects. A* with Non-Determinism (AND*) (Messa and Pereira, 2023) is
Externí odkaz:
http://arxiv.org/abs/2403.19883
Autor:
Bazzan, Ana L. C., Tavares, Anderson R., Pereira, André G., Jung, Cláudio R., Scharcanski, Jacob, Carbonera, Joel Luis, Lamb, Luís C., Recamonde-Mendoza, Mariana, da Silveira, Thiago L. T., Moreira, Viviane
The thought-provoking analogy between AI and electricity, made by computer scientist and entrepreneur Andrew Ng, summarizes the deep transformation that recent advances in Artificial Intelligence (AI) have triggered in the world. This chapter present
Externí odkaz:
http://arxiv.org/abs/2310.18324
While we can see robots in more areas of our lives, they still make errors. One common cause of failure stems from the robot perception module when detecting objects. Allowing users to correct such errors can help improve the interaction and prevent
Externí odkaz:
http://arxiv.org/abs/2306.14589
Publikováno v:
HRI '23: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction
Many solutions tailored for intuitive visualization or teleoperation of virtual, augmented and mixed (VAM) reality systems are not robust to robot failures, such as the inability to detect and recognize objects in the environment or planning unsafe t
Externí odkaz:
http://arxiv.org/abs/2301.04919
Embodied Conversational Agents that make use of co-speech gestures can enhance human-machine interactions in many ways. In recent years, data-driven gesture generation approaches for ECAs have attracted considerable research attention, and related me
Externí odkaz:
http://arxiv.org/abs/2210.06974
Fully Observable Non-Deterministic (FOND) planning models uncertainty through actions with non-deterministic effects. Existing FOND planning algorithms are effective and employ a wide range of techniques. However, most of the existing algorithms are
Externí odkaz:
http://arxiv.org/abs/2204.04322
Autor:
Nagy, Rajmund, Kucherenko, Taras, Moell, Birger, Pereira, André, Kjellström, Hedvig, Bernardet, Ulysses
Embodied conversational agents (ECAs) benefit from non-verbal behavior for natural and efficient interaction with users. Gesticulation - hand and arm movements accompanying speech - is an essential part of non-verbal behavior. Gesture generation mode
Externí odkaz:
http://arxiv.org/abs/2102.12302