Goal recognition as reinforcement learning
Most approaches for goal recognition rely on specifications of the possible dynamics of the
actor in the environment when pursuing a goal. These specifications suffer from two key …
actor in the environment when pursuing a goal. These specifications suffer from two key …
Enhancing Kitchen Activity Recognition: A Benchmark Study of the Rostock KTA Dataset
With the global population aging, the demand for technologies facilitating independent
living, especially for those with cognitive impairments, is increasing. This paper addresses …
living, especially for those with cognitive impairments, is increasing. This paper addresses …
Detecting Activities of Daily Living in Egocentric Video to Contextualize Hand Use at Home in Outpatient Neurorehabilitation Settings
Wearable egocentric cameras and machine learning have the potential to provide clinicians
with a more nuanced understanding of patient hand use at home after stroke and spinal cord …
with a more nuanced understanding of patient hand use at home after stroke and spinal cord …
Goal Recognition using Actor-Critic Optimization
B Nageris, F Meneguzzi, R Mirsky - arXiv preprint arXiv:2501.01463, 2024 - arxiv.org
Goal Recognition aims to infer an agent's goal from a sequence of observations. Existing
approaches often rely on manually engineered domains and discrete representations. Deep …
approaches often rely on manually engineered domains and discrete representations. Deep …
Resilience, reliability, and coordination in autonomous multi-agent systems
Multi-agent systems is an evolving discipline that encompasses many different branches of
research. The long-standing Agents at Aberdeen (A 3) group undertakes research across …
research. The long-standing Agents at Aberdeen (A 3) group undertakes research across …