no code implementations • 15 Jul 2023 • 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 discrete and continuous domains.
no code implementations • 14 Jun 2023 • Ramon Fraga Pereira, Francesco Fuggitti, Felipe Meneguzzi, Giuseppe De Giacomo
We develop the first approach capable of recognizing goals in such settings and evaluate it using different LTLf and PLTLf goals over six FOND planning domain models.
2 code implementations • 21 Apr 2023 • Juarez Monteiro, Nathan Gavenski, Felipe Meneguzzi, Rodrigo C. Barros
We address this limitation by incorporating a discriminator into the original framework, offering two key advantages and directly solving a learning problem previous work had.
no code implementations • 1 Jul 2022 • Maurício Cecílio Magnaguagno, Felipe Meneguzzi, Lavindra de Silva
Hierarchical Task Networks (HTN) planners generate plans using a decomposition process with extra domain knowledge to guide search towards a planning task.
1 code implementation • 13 Feb 2022 • Leonardo Rosa Amado, Reuth Mirsky, Felipe Meneguzzi
In this paper, we develop a framework that combines model-free reinforcement learning and goal recognition to alleviate the need for careful, manual domain design, and the need for costly online executions.
no code implementations • 2 Nov 2021 • Alexandre Yukio Ichida, Felipe Meneguzzi
Contracts underlie most modern commercial transactions defining define the duties and obligations of the related parties in an agreement.
1 code implementation • 27 Feb 2021 • Daniela Kuinchtner, Afonso Sales, Felipe Meneguzzi
Markov Decision Process (MDP) is the underlying model for optimal planning for decision-theoretic agents in stochastic environments.
no code implementations • 23 Feb 2021 • Kin Max Gusmão, Ramon Fraga Pereira, Felipe Meneguzzi
Recent approaches to goal recognition have leveraged planning landmarks to achieve high-accuracy with low runtime cost.
no code implementations • 6 Oct 2020 • Nir Oren, Felipe Meneguzzi
Societal rules, as exemplified by norms, aim to provide a degree of behavioural stability to multi-agent societies.
2 code implementations • 13 Aug 2020 • Nathan Gavenski, Juarez Monteiro, Roger Granada, Felipe Meneguzzi, Rodrigo C. Barros
Behavioral cloning is an imitation learning technique that teaches an agent how to behave through expert demonstrations.
no code implementations • 25 Jul 2020 • Gabriel Paludo Licks, Felipe Meneguzzi
Configuring databases for efficient querying is a complex task, often carried out by a database administrator.
no code implementations • 17 Jul 2020 • Laura Tomaz Da Silva, Nathalia Bianchini Esper, Duncan D. Ruiz, Felipe Meneguzzi, Augusto Buchweitz
However, the success of machine learning classification algorithms on neurofunctional data has been limited to more homogeneous data sets of dozens of participants.
no code implementations • 6 May 2020 • Kin Max Piamolini Gusmão, Ramon Fraga Pereira, Felipe Meneguzzi
Recent approaches to goal and plan recognition using classical planning domains have achieved state of the art results in terms of both recognition time and accuracy by using heuristics based on planning landmarks.
no code implementations • 28 Apr 2020 • Roger Granada, Ramon Fraga Pereira, Juarez Monteiro, Leonardo Amado, Rodrigo C. Barros, Duncan Ruiz, Felipe Meneguzzi
Computer-based assistants have recently attracted much interest due to its applicability to ambient assisted living.
2 code implementations • 28 Apr 2020 • Juarez Monteiro, Nathan Gavenski, Roger Granada, Felipe Meneguzzi, Rodrigo Barros
Imitation from observation is a computational technique that teaches an agent on how to mimic the behavior of an expert by observing only the sequence of states from the expert demonstrations.
no code implementations • 13 May 2019 • João Paulo Aires, Roger Granada, Juarez Monteiro, Rodrigo C. Barros, Felipe Meneguzzi
While most social norms are informal, they are often formalized by companies in contracts to regulate trades of goods and services.
no code implementations • 10 May 2019 • Luísa R. de A. Santos, Felipe Meneguzzi, Ramon Fraga Pereira, André Grahl Pereira
Goal recognition aims to recognize the set of candidate goals that are compatible with the observed behavior of an agent.
no code implementations • 26 Apr 2019 • Ramon Fraga Pereira, Nir Oren, Felipe Meneguzzi
Assessing whether an agent has abandoned a goal or is actively pursuing it is important when multiple agents are trying to achieve joint goals, or when agents commit to achieving goals for each other.
no code implementations • 26 Apr 2019 • Ramon Fraga Pereira, Nir Oren, Felipe Meneguzzi
The task of recognizing goals and plans from missing and full observations can be done efficiently by using automated planning techniques.
no code implementations • 15 Aug 2018 • Leonardo Amado, João Paulo Aires, Ramon Fraga Pereira, Maurício C. Magnaguagno, Roger Granada, Felipe Meneguzzi
Approaches to goal recognition have progressively relaxed the requirements about the amount of domain knowledge and available observations, yielding accurate and efficient algorithms capable of recognizing goals.
no code implementations • 16 Apr 2018 • Ramon Fraga Pereira, Felipe Meneguzzi
Recent approaches to goal recognition have progressively relaxed the assumptions about the amount and correctness of domain knowledge and available observations, yielding accurate and efficient algorithms.
1 code implementation • 5 Apr 2016 • Ramon Fraga Pereira, Felipe Meneguzzi
Recognition of goals and plans using incomplete evidence from action execution can be done efficiently by using planning techniques.