activity
20182026
most citedGoal Recognition as Reinforcement Learning

13 citations · 24 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Online Goal Recognition using Path Signature and Dynamic Time Warping

Douglas Tesch, Nathan Gavenski, Leonardo Amado +2

Online goal recognition in continuous domains poses two central challenges: efficiently encoding large trajectories and effectively comparing them. Recent work addresses these chal…

cs.AI2025

Automated Planning for Optimal Data Pipeline Instantiation

Leonardo Rosa Amado, Adriano Vogel, Dalvan Griebler +3

Data pipeline frameworks provide abstractions for implementing sequences of data-intensive transformation operators, automating the deployment and execution of such transformations…

cs.AI2023

Real-time goal recognition using approximations in Euclidean space

Douglas Tesch, Leonardo Rosa Amado, Felipe Meneguzzi

While recent work on online goal recognition efficiently infers goals under low observability, comparatively less work focuses on online goal recognition that works in both discret…

cs.AI2022★ 13 cited

Goal Recognition as Reinforcement Learning

Leonardo Rosa Amado, Reuth Mirsky, Felipe Meneguzzi

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…

cs.AI2020★ 1 cited

HAPRec: Hybrid Activity and Plan Recognizer

Roger Granada, Ramon Fraga Pereira, Juarez Monteiro +4

Computer-based assistants have recently attracted much interest due to its applicability to ambient assisted living. Such assistants have to detect and recognize the high-level act…

cs.AI2018★ 10 cited

LSTM-Based Goal Recognition in Latent Space

Leonardo Amado, João Paulo Aires, Ramon Fraga Pereira +3

Approaches to goal recognition have progressively relaxed the requirements about the amount of domain knowledge and available observations, yielding accurate and efficient algorith…