Zobrazeno 1 - 10
of 267
pro vyhledávání: '"Loutfi, Amy"'
Designing effective reward functions is crucial to training reinforcement learning (RL) algorithms. However, this design is non-trivial, even for domain experts, due to the subjective nature of certain tasks that are hard to quantify explicitly. In r
Externí odkaz:
http://arxiv.org/abs/2406.01309
Publikováno v:
In Urban Forestry & Urban Greening July 2024 97
This article presents the results from a video-based evaluation study of a social robotic telepresence solution for elderly. The evaluated system is a mobile teleoperated robot called Giraff that allows caregivers to virtually enter a home and conduc
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-23315
Caregivers in eldercare can benefit from telepresence robots that allow them to perform a variety of tasks remotely. In order for such robots to be operated effectively and efficiently by non-technical users, it is important to examine if and how the
Externí odkaz:
http://arxiv.org/abs/2107.09992
Safety in human-robot interaction can be divided into physical safety and perceived safety, where the latter is still under-addressed in the literature. Investigating perceived safety in human-robot interaction requires a multidisciplinary perspectiv
Externí odkaz:
http://arxiv.org/abs/2106.05854
Publikováno v:
In Applied Computing and Geosciences March 2024 21
In a pandemic contact between humans needs to be avoided wherever possible. Robots can take over an increasing number of tasks to protect people from being exposed to others. One such task is the disinfection of environments in which infection spread
Externí odkaz:
http://arxiv.org/abs/2102.01551
Autor:
Akalin, Neziha, Loutfi, Amy
This article surveys reinforcement learning approaches in social robotics. Reinforcement learning is a framework for decision-making problems in which an agent interacts through trial-and-error with its environment to discover an optimal behavior. Si
Externí odkaz:
http://arxiv.org/abs/2009.09689
Publikováno v:
European Conference on Ambient Intelligence (pp. 74-89). Springer, Cham, 2018
Smart home environments equipped with distributed sensor networks are capable of helping people by providing services related to health, emergency detection or daily routine management. A backbone to these systems relies often on the system's ability
Externí odkaz:
http://arxiv.org/abs/2003.06347
Robotic agents should be able to learn from sub-symbolic sensor data, and at the same time, be able to reason about objects and communicate with humans on a symbolic level. This raises the question of how to overcome the gap between symbolic and sub-
Externí odkaz:
http://arxiv.org/abs/2002.10373