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publications.bib
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@ENTRY{
FAVOR MANTER EM ORDEM CRONOLOGICA. MAIS NOVOS 1o
}
@Article{s19051068,
AUTHOR = {Paravisi, Marcelo and H. Santos, Davi and Jorge, Vitor and Heck, Guilherme and Gonçalves, Luiz Marcos and Alexandre M. Amory},
TITLE = {Unmanned Surface Vehicle Simulator with Realistic Environmental Disturbances},
JOURNAL = {Sensors},
VOLUME = {19},
YEAR = {2019},
NUMBER = {5},
ARTICLE-NUMBER = {1068},
URL = {http://www.mdpi.com/1424-8220/19/5/1068},
ISSN = {1424-8220},
ABSTRACT = {The use of robotics in disaster scenarios has become a reality. However, an Unmanned Surface Vehicle (USV) needs a robust navigation strategy to face unpredictable environmental forces such as waves, wind, and water current. A starting step toward this goal is to have a programming environment with realistic USV models where designers can assess their control strategies under different degrees of environmental disturbances. This paper presents a simulation environment integrated with robotic middleware which models the forces that act on a USV in a disaster scenario. Results show that these environmental forces affect the USV’s trajectories negatively, indicating the need for more research on USV control strategies considering harsh environmental conditions. Evaluation scenarios were presented to highlight specific features of the simulator, including a bridge inspection scenario with fast water current and winds.},
keywords={robotics},
DOI = {10.3390/s19051068}
}
@Article{s19030702,
AUTHOR = {Jorge, Vitor A. M. and Granada, Roger and Maidana, Renan G. and Jurak, Darlan A. and Heck, Guilherme and Negreiros, Alvaro P. F. and dos Santos, Davi H. and Gonçalves, Luiz M. G. and Alexandre M. Amory},
TITLE = {A Survey on Unmanned Surface Vehicles for Disaster Robotics: Main Challenges and Directions},
JOURNAL = {Sensors},
VOLUME = {19},
YEAR = {2019},
NUMBER = {3},
ARTICLE-NUMBER = {702},
URL = {http://www.mdpi.com/1424-8220/19/3/702},
ISSN = {1424-8220},
ABSTRACT = {Disaster robotics has become a research area in its own right, with several reported cases of successful robot deployment in actual disaster scenarios. Most of these disaster deployments use aerial, ground, or underwater robotic platforms. However, the research involving autonomous boats or Unmanned Surface Vehicles (USVs) for Disaster Management (DM) is currently spread across several publications, with varying degrees of depth, and focusing on more than one unmanned vehicle—usually under the umbrella of Unmanned Marine Vessels (UMV). Therefore, the current importance of USVs for the DM process in its different phases is not clear. This paper presents the first comprehensive survey about the applications and roles of USVs for DM, as far as we know. This work demonstrates that there are few current deployments in disaster scenarios, with most of the research in the area focusing on the technological aspects of USV hardware and software, such as Guidance Navigation and Control, and not focusing on their actual importance for DM. Finally, to guide future research, this paper also summarizes our own contributions, the lessons learned, guidelines, and research gaps.},
keywords={robotics},
DOI = {10.3390/s19030702}
}
@article{Madhavan2017,
title={The 2017 Humanitarian Robotics and Automation Technology Challenge [Humanitarian Technology]},
author={Raj Madhavan and Alexandre Amory and Edson Prestes and Renan Guedes and Augusto Bergamin and Renata Neuland and Mathias Mantelli and Diego Kindin and Fernanda Rodrigues},
journal={IEEE Robotics \& Automation Magazine},
volume={24},
number={4},
pages={127--129},
year={2017},
publisher={IEEE}
}
@inproceedings{paravisi18icinco,
author={Marcelo Paravisi and Vitor {A. M. Jorge} and Alexandre Amory},
title={Toward an Accurate Hydrologic Urban Flooding Simulations for Disaster Robotics},
booktitle={Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2018},
pages={425-431},
doi={10.5220/0006904704350441},
isbn={978-989-758-321-6},
keywords = {robotics}
}
@inproceedings{oliveira2017teaching,
title={Teaching Robot Programming Activities for Visually Impaired Students: A Systematic Review},
author={Oliveira, Juliana Damasio and de Borba Campos, M{\'a}rcia and de Morais Amory, Alexandre and Manssour, Isabel Harb},
booktitle={International Conference on Universal Access in Human-Computer Interaction},
pages={155--167},
year={2017},
organization={Springer}
}
@inproceedings{renan2017deep,
title={Deep Neural Networks for Handwritten Chinese Character Recognition},
author={Renan G. Maidana, Juarez Monteiro, Roger Granada, Alexandre M. Amory and Rodrigo C. Barros},
booktitle={BRACIS},
year={2017}
}
@inproceedings{guilherme2017donnie,
title={Donnie Robot: Towards an Accessible And Educational Robot for Visually Impaired People},
author={Guilherme H. M. Marques, Daniel C. Einloft, Augusto C. P. Bergamin, Joice A. Marek, Renan G. Maidana Marcia B. Campos, Isabel H. Manssour, Alexandre M. Amory},
booktitle={Latin American Robotics Symposium (LARS)},
year={2017}
}
@inproceedings{maidana2017odometria,
title={Odometria Visual Monocular para Localiza{\c{c}}{\~a}o de Rob{\^o} Terrestre},
author={Maidana, Renan Guedes and Salton, Aurelio Tergolina and de Morais Amory, Alexandre},
booktitle={SBAI},
year={2017}
}
@inproceedings{Magnaguagno2017a,
author = {Mauricio Magnaguagno and Felipe Meneguzzi},
title = {Method Composition through Operator Pattern Identification},
booktitle = {ICAPS Workshop on Knowledge Engineering for Planning and Scheduling},
year = {2017},
keywords = {Planning, Hierarchical Task Network},
abstract = {Classical planning is a computationally expensive task, especially when tackling real world problems.
To overcome such limitations, most realistic applications of planning rely on domain knowledge configured by a domain expert, such as the hierarchy of tasks and methods used by Hierarchical Task Network (HTN) planning.
Thus, the efficiency of HTN approaches relies heavily on human-driven domain design.
In this paper, we aim to address this limitation by developing an approach to generate useful methods based on classical domains.
Our work does not require annotations in the classical planning operators or training examples, and instead, relies solely on operator descriptions to identify task patterns and the sub-problems related to each pattern.
We propose the use of methods that solve common sub-problems to obtain HTN methods automatically.}
}
@Inbook{Silva2016,
author={de Silva, Lavindra
and Meneguzzi, Felipe
and Sanderson, David
and Chaplin, Jack C.
and Bakker, Otto J.
and Antzoulatos, Nikolas
and Ratchev, Svetan",
editor="Borangiu, Theodor
and Trentesaux, Damien
and Thomas, Andr{\'e}
and McFarlane, Duncan},
chapter={Interfacing Belief-Desire-Intention Agent Systems with Geometric Reasoning for Robotics and Manufacturing},
title={Service Orientation in Holonic and Multi-Agent Manufacturing},
year={2016},
publisher={Springer International Publishing},
pages={179--188},
isbn={978-3-319-30337-6},
doi={10.1007/978-3-319-30337-6_17},
url={http://dx.doi.org/10.1007/978-3-319-30337-6_17}
}
@inproceedings{moraes2016comparing,
title={Comparing Approaches to Subjectivity Classification: A Study on Portuguese Tweets},
author={Moraes, Silvia MW and Santos, Andr{\'e} LL and Redecker, Matheus and Machado, Rackel M and Meneguzzi, Felipe R},
booktitle={International Conference on Computational Processing of the Portuguese Language},
pages={86--94},
year={2016},
organization={Springer}
}
@Article{CameronCraddock2016,
author="Cameron Craddock, R.
and S. Margulies, Daniel
and Bellec, Pierre
and Nolan Nichols, B.
and Alcauter, Sarael
and A. Barrios, Fernando
and Burnod, Yves
and J. Cannistraci, Christopher
and Cohen-Adad, Julien
and De Leener, Benjamin
and Dery, Sebastien
and Downar, Jonathan
and Dunlop, Katharine
and R. Franco, Alexandre
and Seligman Froehlich, Caroline
and J. Gerber, Andrew
and S. Ghosh, Satrajit
and J. Grabowski, Thomas@inproceedings{moraes2016comparing,
title={Comparing Approaches to Subjectivity Classification: A Study on Portuguese Tweets},
author={Moraes, Silvia MW and Santos, Andr{\'e} LL and Redecker, Matheus and Machado, Rackel M and Meneguzzi, Felipe R},
booktitle={International Conference on Computational Processing of the Portuguese Language},
pages={86--94},
year={2016},
organization={Springer}
}
and Hill, Sean
and S{\'o}lon Heinsfeld, Anibal
and Matthew Hutchison, R.
and Kundu, Prantik
and R. Laird, Angela
and Liew, Sook-Lei
and J. Lurie, Daniel
and G. McLaren, Donald
and Meneguzzi, Felipe
and Mennes, Maarten
and Mesmoudi, Salma
and O'Connor, David
and H. Pasaye, Erick
and Peltier, Scott
and Poline, Jean-Baptiste
and Prasad, Gautam
and Fraga Pereira, Ramon
and Quirion, Pierre-Olivier
and Rokem, Ariel
and S. Saad, Ziad
and Shi, Yonggang
and C. Strother, Stephen
and Toro, Roberto
and Q. Uddin, Lucina
and D. Van Horn, John
and W. Van Meter, John
and C. Welsh, Robert
and Xu, Ting",
title="Brainhack: a collaborative workshop for the open neuroscience community",
journal="GigaScience",
year="2016",
volume="5",
number="1",
pages="1--8",
abstract="Brainhack events offer a novel workshop format with participant-generated content that caters to the rapidly growing open neuroscience community. Including components from hackathons and unconferences, as well as parallel educational sessions, Brainhack fosters novel collaborations around the interests of its attendees. Here we provide an overview of its structure, past events, and example projects. Additionally, we outline current innovations such as regional events and post-conference publications. Through introducing Brainhack to the wider neuroscience community, we hope to provide a unique conference format that promotes the features of collaborative, open science.",
issn="2047-217X",
doi="10.1186/s13742-016-0121-x",
url="http://dx.doi.org/10.1186/s13742-016-0121-x"
}
@book{Koch2015,
year={2015},
isbn={978-3-662-46240-9},
booktitle={Agent Technology for Intelligent Mobile Services and Smart Societies},
editor={Fernando Koch and Felipe Meneguzzi and Kiran Lakkaraju},
title={Agent Technology for Intelligent Mobile Services and Smart Societies},
url={http://www.springer.com/computer/information+systems+and+applications/book/978-3-662-46240-9},
publisher={Springer},
language={English}
}
@article{Meneguzzi2015,
title = "\{BDI\} reasoning with normative considerations ",
journal = "Engineering Applications of Artificial Intelligence ",
volume = "43",
number = "0",
pages = "127 - 146",
year = "2015",
note = "",
issn = "0952-1976",
doi = "http://dx.doi.org/10.1016/j.engappai.2015.04.011",
url = "http://www.sciencedirect.com/science/article/pii/S0952197615000925",
author = "Felipe Meneguzzi and Odinaldo Rodrigues and Nir Oren and Wamberto W. Vasconcelos and Michael Luck",
keywords = "Multi-agent systems",
keywords = "Norms",
keywords = "\{BDI\}",
keywords = "Constraints",
keywords = "Planning ",
abstract = "Abstract Systems of autonomous and self-interested agents interacting to achieve individual and collective goals may exhibit undesirable or unexpected behaviour if left unconstrained. Norms have been widely proposed as a means of defining and enforcing societal constraints by using the deontic concepts of obligations, permissions and prohibitions to describe what must, may and should not be done, respectively. However, recent efforts to provide norm-enabled agent architectures that guide plan choices suffer from interfering with an agent׳s reasoning process, and thus limit the agent׳s autonomy more than is required by the norms alone. In this paper we describe an extension of the Beliefs, Desires, Intentions (BDI) architecture that enables normative reasoning used to help agents choose and customise plans taking norms into account. The paper makes three significant contributions: we provide a formal framework to represent norms compactly and to manage them; we present a formal characterisation of the normative positions induced by norms of an agent׳s execution within a given time period; and finally, we put forth a mechanism for plan selection and ranking taking into consideration a set of normative restrictions. "
}
@article{Meneguzzi2015,
author = {Meneguzzi,Felipe and De Silva,Lavindra},
title = {Planning in BDI agents: a survey of the integration of planning algorithms and agent reasoning},
journal = {The Knowledge Engineering Review},
volume = {30},
issue = {01},
month = {1},
year = {2015},
issn = {1469-8005},
pages = {1--44},
numpages = {44},
doi = {10.1017/S0269888913000337},
URL = {http://journals.cambridge.org/article_S0269888913000337},
abstract = { ABSTRACT Agent programming languages have often avoided the use of automated (first principles or hierarchical) planners in favour of predefined plan/recipe libraries for computational efficiency reasons. This allows for very efficient agent reasoning cycles, but limits the autonomy and flexibility of the resulting agents, oftentimes with deleterious effects on the agent's performance. Planning agents can, for instance, synthesise a new plan to achieve a goal for which no predefined recipe worked, or plan to make viable the precondition of a recipe belonging to a goal being pursued. Recent work on integrating automated planning with belief-desire-intention (BDI)-style agent architectures has yielded a number of systems and programming languages that exploit the efficiency of standard BDI reasoning, as well as the flexibility of generating new recipes at runtime. In this paper, we survey these efforts and point out directions for future work. }
}
@article{Modgil2015,
year={2015},
issn={0924-8463},
journal={Artificial Intelligence and Law},
doi={10.1007/s10506-015-9167-9},
title={Monitoring compliance with E-contracts and norms},
url={http://dx.doi.org/10.1007/s10506-015-9167-9},
publisher={Springer Netherlands},
keywords={E-contracts; Norms; Monitoring; Multiagent systems},
author={Modgil, Sanjay and Oren, Nir and Faci, Noura and Meneguzzi, Felipe and Miles, Simon and Luck, Michael},
pages={1-36},
language={English}
}
@INPROCEEDINGS{Cranefield2016,
author = {Stephen Cranefield and Felipe Meneguzzi and Nir Oren and Bastin T. R. Savarimuthu},
title = {A Bayesian approach to norm identification},
booktitle = {Proceedings of the Twenty Second European Conference on Artificial Intelligence},
year = {2016},
doi = {10.3233/978-1-61499-672-9-622},
pages = {622 -- 629},
}
@INPROCEEDINGS{Pereira2016,
author = {Ramon Fraga Pereira and Felipe Meneguzzi},
title = {Landmark-based Plan Recognition},
booktitle = {Proceedings of the Twenty Second European Conference on Artificial Intelligence},
year = {2016},
doi = {10.3233/978-1-61499-672-9-1706},
pages = {1706 - 1707},
}
@inproceedings{Magnaguagno2016,
author = {Mauricio Magnaguagno and Ramon Pereira and Felipe Meneguzzi},
title = {DOVETAIL — An Abstraction for Classical Planning Using a Visual Metaphor},
booktitle = {Florida Artificial Intelligence Research Society Conference},
year = {2016},
keywords = {Planning; Visualization; Metaphor},
abstract = {While domain descriptions are often shared and manipulated through diagrams, most complex domains are still described using text-based languages. Code becomes an intermediary between the real-world and an abstract idea, and the programmer is merely a converter of diagrams into code. For automated planning this is no different. The state transition function is described in terms of a textual representation of actions and, although simple actions require little effort to define by the user, the learning process is often slow. New users have no metaphor to help them to visualize the domain description that they are working on and little information about why a planner fails due to formalization errors. In this paper, we propose a visual abstraction for both the planning domain actions and the planning process itself, to facilitate the design of classical planning domains. Using this abstraction, we expect to improve the learning curve for defining and subsequently diagnosing problems with new planning domains.},
url = {http://www.aaai.org/ocs/index.php/FLAIRS/FLAIRS16/paper/view/12966}
}
@INPROCEEDINGS{Meneguzzi2015,
author = {Felipe Meneguzzi and Pankaj Telang and Neil Yorke-Smith},
title = {Towards Planning Uncertain Commitment Protocols},
booktitle = {Proceedings of the Thirteenth International Conference on Autonomous
Agents and Multiagent Systems},
year = {2015},
pages = {1681--1682},
abstract = {In the context of a business process modeled by commitments, agents enact a protocol by carrying out goals that service their part of commitments.
In a competitive or even in a cooperative setting, an agent does not know for sure that its partners will successfully act on their part of the commitments.
We introduce uncertainty into a successful recent approach of planning first-order commitment protocols.
Probabilities reflect a semantics of the belief of an agent about the successful completion of tasks by other agents within the protocol, capturing notions of trust.
We take a deterministic Hierarchical Task Network (HTN) planner, introduce probabilities into the task networks, and derive a protocol enactment which maximizes expected utility from the point of view of one agent. We illustrate our approach on a business scenario in e-commerce.},
file = {:http\://www.meneguzzi.eu/felipe/pubs/aamas-commitments-probabilities-2015.pdf:PDF},
url = {http://www.meneguzzi.eu/felipe/pubs/aamas-commitments-probabilities-2015.pdf},
owner = {meneguzzi},
timestamp = {2015.05.29}
}
@INPROCEEDINGS{Cranefield2015,
author = {Stephen Cranefield and Felipe Meneguzzi and Nir Oren and Tony Savarimuthu},
title = {A Bayesian Approach to Norm Identification},
booktitle = {Proceedings of the Thirteenth International Conference on Autonomous
Agents and Multiagent Systems},
year = {2015},
pages = {1743--1744},
abstract = {When entering a system, an agent should be aware of the obligations and prohibitions (collectively norms) that will affect it. Several solutions to this norm identification problem have been proposed, which make use of observations of either other's norm compliant, or norm violating, behaviour. These solutions fail in situations where norms are typically violated, or complied with, respectively. In this paper we propose a Bayesian approach to norm identification which operates by learning from both norm compliant and norm violating behaviour. By utilising both types of behaviour, our work not only overcomes a major limitation of existing approaches, but also yields improved performance over the state-of-the-art. We evaluate its effectiveness empirically, showing, under certain conditions, high accuracy scores.},
file = {:http\://www.meneguzzi.eu/felipe/pubs/aamas-norm-recognition-2015.pdf:PDF},
url = {http://www.meneguzzi.eu/felipe/pubs/aamas-norm-recognition-2015.pdf},
owner = {meneguzzi},
timestamp = {2015.05.29}
}
@INPROCEEDINGS{Chang2015,
author = {Stephan Chang and Felipe Meneguzzi},
title = {Simulating Normative Behaviour in Multi-Agent Environments using Monitoring Artefacts},
booktitle = {17th International Workshop on Coordination, Organizations, Institutions, and Norms},
year = {2015},
pages = {1-16},
abstract = {While there are tools for programming Multi-Agent Systems, few provide an explicit mechanism for simulating norm-based behaviour using a variety of normative representations.
In this paper, we develop an artefact-based mechanism for norm processing, monitoring and enforcement and show its implementation as a framework built with CARTAGO.
Our framework is then empirically demonstrated using a variety of enforcement settings.},
file = {:http\://www.meneguzzi.eu/felipe/pubs/coin-simulating-norms-2015.pdf:PDF},
owner = {meneguzzi},
timestamp = {2015.07.28},
url = {http://www.meneguzzi.eu/felipe/pubs/coin-simulating-norms-2015.pdf}
}
@INPROCEEDINGS{Li2015,
author = {de Silva, Lavindra and Felipe Meneguzzi},
title = {On the Design of Symbolic-Geometric Online Planning Systems},
booktitle = {2015 Workshop on Hybrid Reasoning (HR 2015)},
year = {2015},
pages = {1-8},
abstract = {We describe an abstract multilayered architecture for the organisation of robotic systems that takes
into account some of the key functionalities of existing robotic hardware and software in the literature. We demonstrate a concrete instance of the architecture by combining the popular AgentSpeak agent/robot programming language with standard motion planning algorithms. Our work offers some first insights into developing a more formal agent architecture for programming autonomous robots.},
file = {:http\://www.meneguzzi.eu/felipe/pubs/hr-symbolic-geometric-2015.pdf:PDF},
owner = {meneguzzi},
timestamp = {2015.07.28},
url = {http://www.meneguzzi.eu/felipe/pubs/hr-symbolic-geometric-2015.pdf}
}
@INPROCEEDINGS{Aires2015,
author = {João Paulo Aires and Vera Lúcia Strube de Lima and Felipe Meneguzzi},
title = {Identifying Potential Conflicts between Norms in Contracts},
booktitle = {18th International Workshop on Coordination, Organizations, Institutions, and Norms},
year = {2015},
pages = {1-6},
abstract = {Contracts formally represent agreements between parties and often involve the exchange of goods or services.
In contracts, clauses define the behavior expected from parties in terms of deontic statements such as obligation, permission and prohibition.
These normative clauses may contain conflicting deontic statements referring to the same party in the same context, producing inconsistencies in the normative structure of the contract.
Our main contribution is an approach to detect potential conflicts between norms within contracts written in natural language.
We use a rule-based approach and natural language processing, which result in promising empirical results.
This constitutes a first step into automated processing of contracts in natural language.},
file = {:http\://www.meneguzzi.eu/felipe/pubs/coin-nlp-norm-conflicts-2015.pdf:PDF},
owner = {meneguzzi},
timestamp = {2015.07.28},
url = {http://www.meneguzzi.eu/felipe/pubs/coin-nlp-norm-conflicts-2015.pdf}
}
@INPROCEEDINGS{Li2015,
author = {Jiaqi Li and Felipe Meneguzzi and Moser Silva Fagundes and Brian Logan},
title = {Reinforcement Learning of Normative Monitoring Intensities},
booktitle = {18th International Workshop on Coordination, Organizations, Institutions, and Norms},
year = {2015},
pages = {1-15},
abstract = {Choosing actions within norm-regulated environments involves balancing achieving one's goals and coping with any penalties for non-compliant behaviour. This choice becomes more complicated in environments where there is uncertainty. In this paper, we address the question of choosing actions in environments where there is uncertainty regarding both the outcomes of agent actions and the intensity of monitoring for norm violations. Our technique assumes no prior knowledge of probabilities over action outcomes or the likelihood of norm violations being detected by employing reinforcement learning to discover both the dynamics of the environment and the effectiveness of the enforcer. Results indicate agents become aware of greater rewards for violations when enforcement is lax, which gradually become less attractive as the enforcement is increased.},
file = {:http\://www.meneguzzi.eu/felipe/pubs/coin-nmdp-asym-2015.pdf:PDF},
owner = {meneguzzi},
timestamp = {2015.07.28},
url = {http://www.meneguzzi.eu/felipe/pubs/coin-nmdp-asym-2015.pdf}
}
@InProceedings{Morais2015,
Title = {Distributed Fault Diagnostic for Multiple Mobile Robots Using an Agent Programming Language},
Author = {Marcio G. Morais and Felipe R. Meneguzzi and Rafael H. Bordini and Alexandre M. Amory},
Booktitle = {Proceedings of the 17th International Conference on Advanced Robotics},
Year = {2015},
pages = {395-400},
Abstract = {Programming autonomous multi-robot systems can be extremely complex without the use of appropriate software development techniques to abstract the hardware heterogeneity from the complexity of distributed software to coordinate autonomous behavior. Moreover, real environments are dynamic, which can generate unpredictable events that can lead the robots to failure. This paper presents a highly abstract cooperative fault diagnostic method for a team of mobile robots described on a programming environment based on ROS (Robot Operating System) and the Jason multi-agent framework. When a robot detects a failure, it can perform two types of diagnostic methods: a local method executed on the faulty robot itself and a cooperative method where another robot helps the faulty robot to determine the source of failure. A case study demonstrates the success of the approach on two turtlebots.},
file = {:http\://www.meneguzzi.eu/felipe/pubs/icar-ros-jason-2015.pdf:PDF},
owner = {meneguzzi},
timestamp = {2015.09.04},
url = {http://www.meneguzzi.eu/felipe/pubs/icar-ros-jason-2015.pdf}
}
@incollection{Oh2014,
year={2014},
isbn={978-0123985323},
booktitle={Plan, Activity, and Intent Recognition: Theory and Practice},
editor={Gita Sukthankar and Robert P. Goldman and Christopher Geib and David V. Pynadath and Hung Hai Bui},
title={Probabilistic Plan Recognition for Proactive Assistant Agents},
url={http://store.elsevier.com/Plan-Activity-and-Intent-Recognition/isbn-9780123985323/},
publisher={Elsevier},
author={Jean Oh, Felipe Meneguzzi and Katia Sycara},
pages={275-288},
language={English}
}
@INPROCEEDINGS{Meneguzzi2014,
author = {Felipe Meneguzzi and Brian Logan and Moser Fagundes},
title = {Norm Monitoring with Asymmetric Information},
booktitle = {Proceedings of the Thirteenth International Conference on Autonomous
Agents and Multiagent Systems},
year = {2014},
pages = {1523--1524},
abstract = {In this paper we consider the implications of imperfect monitoring in a stochastic environment for both the agents and the normative organisation in a normative MAS. We introduce a notion of information asymmetry to characterise the agents’ knowledge of the monitoring strategy, and show that there are potential benefits of information asymmetry for the normative organisation in reducing its cost of enforcement.},
file = {:http\://www.meneguzzi.eu/felipe/pubs/aamas-nmdp-asym-2014.pdf:PDF},
url = {http://www.meneguzzi.eu/felipe/pubs/aamas-nmdp-asym-2014.pdf},
owner = {meneguzzi},
timestamp = {2014.05.30}
}
@INPROCEEDINGS{Fagundes2014,
author = {Moser Fagundes and Felipe Meneguzzi and Rafael H. Bordini and Renata Vieira},
title = {Dealing with Ambiguity in Plan Recognition under Time Constraints},
booktitle = {Proceedings of the Thirteenth International Conference on Autonomous
Agents and Multiagent Systems},
year = {2014},
pages = {389--396},
abstract = {Plan recognition has been widely used in agents that need to infer which plans are being executed or which activities are being performed by others. In many applications reasoning and acting in response to plan recognition requires time. In such systems, plan recognition is expected to be made not only with precision, but also in a timely fashion. When recognition cannot be made in time, the plan recognition agent can interact with the observed agents to disambiguate multiple hypotheses, however, such an intrusive behavior is either not possible, very costly, or undesirable. In this paper, we focus on the problem of deciding when to interact with the observed agents in order to determine their plans under execution. To tackle this problem, we develop a plan recognizer that, on the one hand is the least intrusive possible, and on the other hand, attempts to recognize the plans of the observed agents with precision as soon as possible and no later than it is viable to respond to the recognized plan.},
file = {:http\://www.meneguzzi.eu/felipe/pubs/aamas-intention-rec-2014.pdf:PDF},
url = {http://www.meneguzzi.eu/felipe/pubs/aamas-intention-rec-2014.pdf},
owner = {meneguzzi},
timestamp = {2014.05.31}
}
@INPROCEEDINGS{Fagundes2014,
author = {Moser Silva Fagundes and Sascha Ossowski and Felipe Meneguzzi},
title = {Analyzing the tradeoff between efficiency and cost of norm enforcement in stochastic environments populated with self-interested agents},
booktitle = {Proceedings of the Twenty First European Conference on Artificial Intelligence},
year = {2014},
pages = {1003-1004},
}
@INPROCEEDINGS{Alrawagfeh2014,
author = {Wagdi Alrawagfeh and Felipe Meneguzzi},
title = {Utilizing Permission Norms in BDI Practical Normative Reasoning},
booktitle = {16th International Workshop on Coordination, Organizations, Institutions, and Norms},
year = {2014},
abstract = {Norms have been used in multiagent systems as a standard description of agents’ behaviors. A lot of effort has been put in formalizing norms and utilizing them in agents’ decision making. Most of this work focuses on two types of norms: prohibitions and obligations. Agents may have incomplete knowledge about norms in a system for several reasons, such as, deficient norms identification techniques or because norms are not fixed and they may change and emerge, etc. In this work we argue that, by assuming that agents do not have complete knowledge of the norms within a system permission norms are fundamental for modeling unknown normative states. Using Event Calculus, we propose a formal representation of permission norm and we show how to use it in agent normative practical reasoning. A simple mineral mining scenario has been used to demonstrate our work, which was implemented in a popular agent programming language.},
file = {:http\://www.meneguzzi.eu/felipe/pubs/coin-permissions-2014.pdf:PDF},
owner = {meneguzzi},
timestamp = {2014.05.31},
url = {http://www.meneguzzi.eu/felipe/pubs/coin-permissions-2014.pdf}
}
@inproceedings{fagundes2014imperfect,
title={Imperfect norm enforcement in stochastic environments: an analysis of efficiency and cost tradeoffs},
author={Fagundes, Moser Silva and Ossowski, Sascha and Meneguzzi, Felipe},
booktitle={Ibero-American Conference on Artificial Intelligence},
pages={523--535},
year={2014},
organization={Springer}
}
@inproceedings{DBLP:conf/aaai/MeneguzziTS13,
author = {Felipe Meneguzzi and
Pankaj R. Telang and
Munindar P. Singh},
title = {A First-Order Formalization of Commitments and Goals for
Planning},
booktitle = {AAAI},
pages = {697--703},
year = {2013},
ee = {http://www.aaai.org/ocs/index.php/AAAI/AAAI13/paper/view/6371},
crossref = {DBLP:conf/aaai/2013},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
@INPROCEEDINGS{Telang2013,
author = {Pankaj Telang and Felipe Meneguzzi and Munindar Singh},
title = {Hierarchical Planning about Goals and Commitments},
booktitle = {Proceedings of the Twelfth International Conference on Autonomous
Agents and Multiagent Systems},
year = {2013},
pages = {877--884},
abstract = {We consider the problem of relating an agent's internal state (its beliefs and goals) and its social state (its commitments to and from other agents) as a way to develop a comprehensive account of decision making by agents in a multiagent system. We model this problem in terms of hierarchical task networks (HTNs) and show how HTN planning provides a natural representation and reasoning framework for goals and commitments. Our approach combines a domain-independent theory capturing the lifecycles of goals and commitments, generic patterns of reasoning, and domain models. Specifically, our approach shows how each agent may take into account its capabilities, costs, and preferences as it plans its interactions (captured as operations on commitments) with other agents to attempt to achieve its goals.},
file = {:http\://www.meneguzzi.eu/felipe/pubs/aamas-commitments-2013.pdf:PDF},
url = {http://www.meneguzzi.eu/felipe/pubs/aamas-commitments-2013.pdf},
owner = {meneguzzi},
timestamp = {2013.06.02}
}
@INPROCEEDINGS{Oren2013:norm-detect,
author = {Nir Oren and Felipe Meneguzzi},
title = {Norm Identification through Plan Recognition},
booktitle = {15th International Workshop on Coordination, Organizations, Institutions, and Norms},
year = {2013},
pages = {161-175},
abstract = {Societal rules, as exemplified by norms, aim to provide a degree of behavioural stability to multi-agent societies. Norms regulate a society using the deontic concepts of permissions, obligations and prohibitions to specify what can, must and must not occur in a society. Many implementations of normative systems assume various combinations of the following assumptions: that the set of norms is static and defined at design time; that agents joining a society are instantly informed of the complete set of norms; that the set of agents within a society does not change; and that all agents are aware of the existing norms. When any one of these assumptions is dropped, agents need a mechanism to identify the set of norms currently present within a society, or risk unwittingly violating the norms. In this paper, we develop a norm identification mechanism that uses a combination of parsing-based plan recognition and Hierarchical Task Network (HTN) planning mechanisms, which operates by analysing the actions performed by other agents. While our basic mechanism cannot learn in situations where norm violations take place, we describe an extension which is able to operate in the presence of violations.},
file = {:http\://www.meneguzzi.eu/felipe/pubs/coin-norm-detect-2013.pdf:PDF},
owner = {meneguzzi},
timestamp = {2013.05.06},
url = {http://www.meneguzzi.eu/felipe/pubs/coin-norm-detect-2013.pdf}
}
@incollection{Luck2013,
year={2013},
isbn={978-94-007-5582-6},
booktitle={Agreement Technologies},
volume={8},
series={Law, Governance and Technology Series},
editor={Ossowski, Sascha},
doi={10.1007/978-94-007-5583-3_14},
title={Normative Agents},
url={http://dx.doi.org/10.1007/978-94-007-5583-3_14},
publisher={Springer Netherlands},
author={Luck, Michael and Mahmoud, Samhar and Meneguzzi, Felipe and Kollingbaum, Martin and Norman, Timothy J. and Criado, Natalia and Fagundes, Moser Silva},
pages={209-220},
language={English}
}
@article{Oh2013,
title = {Prognostic normative reasoning},
journal = {Engineering Applications of Artificial Intelligence},
volume = {26},
number = {2},
pages = {863 -- 872},
year = {2013},
issn = {0952-1976},
doi = {10.1016/j.engappai.2012.12.006},
url = {http://www.sciencedirect.com/science/article/pii/S0952197612003144},
author = {Jean Oh and Felipe Meneguzzi and Katia Sycara and Timothy J. Norman},
keywords = {Proactive agents},
keywords = {Normative reasoning},
keywords = {Agent architecture},
abstract = {Human users planning for multiple objectives in complex environments are subjected to high levels of cognitive workload, which can severely impair the quality of the plans created. This paper describes a software agent that can proactively assist cognitively overloaded users by providing normative reasoning about prohibitions and obligations so that the user can focus on her primary objectives. In order to provide proactive assistance, we develop the notion of prognostic normative reasoning (PNR) that consists of the following steps: (1) recognizing the user's planned activities, (2) reasoning about norms to evaluate those predicted activities, and (3) providing necessary assistance so that the user's activities are consistent with norms. The idea of PNR integrates various AI techniques, namely, user intention recognition, normative reasoning over a user's intention, and planning, execution and replanning for assistive actions. In this paper, we describe an agent architecture for PNR and discuss practical applications.}
}
@article{Meneguzzi2012,
title = {Applying electronic contracting to the aerospace aftercare domain},
journal = {Engineering Applications of Artificial Intelligence},
volume = {25},
number = {7},
year = {2012},
pages = {1471-1487},
issn = {0952-1976},
doi = {10.1016/j.engappai.2012.06.004},
url = {http://www.sciencedirect.com/science/article/pii/S0952197612001479},
author = {Felipe Meneguzzi and Sanjay Modgil and Nir Oren and Simon Miles and Michael Luck and Noura Faci},
keywords = {CONTRACT},
keywords = {Norms},
keywords = {Monitoring},
keywords = {BDI},
keywords = {ATN},
abstract = {The contract project was a European Commission project whose aim was to develop frameworks, components and tools to model, build, verify and monitor distributed electronic business systems based on electronic contracts. In this context, an electronic contract provides a specification of the expected behaviours of individual services, with the assumption that these services are often enacted by autonomous agents. Using the theoretical tools created by the project, in this paper we describe the complete life cycle of instantiating an electronic contracting system using the contract framework within the aerospace aftercare domain. Thus, we use a natural language description of parts of the types of contracts used in this domain to generate individual norms amenable to a computational representation, and how these norms are used to generate a concrete contract monitor. Moreover, we describe a concrete implementation of contract agents in the AgentSpeak(L) language and how these agents interact within a concrete instantiation of contract.}
}
@article{DBLP:journals/aim/AzevedoBBCFHHHKKLLMMOPRSSD11,
author = {Roger Azevedo and
Gautam Biswas and
Dan Bohus and
Ted Carmichael and
Mark A. Finlayson and
Mirsad Hadzikadic and
Catherine Havasi and
Eric Horvitz and
Takayuki Kanda and
Oluwasanmi Koyejo and
William F. Lawless and
Douglas B. Lenat and
Felipe Meneguzzi and
Bilge Mutlu and
Jean Oh and
Roberto Pirrone and
Antoine Raux and
Donald A. Sofge and
Gita Sukthankar and
Benjamin Van Durme},
title = {Reports of the {AAAI} 2010 Fall Symposia},
journal = {{AI} Magazine},
volume = {32},
number = {1},
pages = {93--100},
year = {2011},
url = {http://www.aaai.org/ojs/index.php/aimagazine/article/view/2338},
timestamp = {Thu, 07 Jul 2011 21:51:18 +0200},
biburl = {http://dblp.uni-trier.de/rec/bib/journals/aim/AzevedoBBCFHHHKKLLMMOPRSSD11},
bibsource = {dblp computer science bibliography, http://dblp.org}
}