Author name cluster

Ingrid Nunes

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

8 papers

2 author rows

AAMAS Conference 2017 Conference Paper

ABStractme: Modularized Environment Modeling in Agent-based Simulations

Deividi Moreira
Fernando Santos
Matheus Barbieri
Ingrid Nunes
Ana L. C. Bazzan

This paper presents ABStractme, a tool for modeling the simulated environment in agent-based simulations. Differently from existing alternatives, ABStractme allows specification of the environment in terms of concerns, which improve modularization. Moreover, it supports the modeling of setup aspects of the simulation, in addition to entities and the spatial abstraction. The tool generates ready-touse code for the NetLogo simulation platform. A user study provided evidence that ABStractme is useful, enjoyable, and easy to use and learn. Demonstration video: https: //youtu. be/Z4DeVDwdjVw

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AAMAS Conference 2017 Conference Paper

Model-Driven Engineering in Agent-based Modeling and Simulation: a Case Study in the Traffic Signal Control Domain

Fernando Santos
Ingrid Nunes
Ana L. C. Bazzan

Model-driven engineering (MDE) is an approach for improving productivity in software development. This approach was exploited in the context of agent-based modeling and simulation (ABMS) only to a certain extent. Previous work has not shown real evidence of the benefits that MDE promotes in ABMS. This paper thus explores the use of MDE in ABMS with a case study in the traffic domain. We propose a domain analysis method to identify domain concepts and a modeling language that provides building blocks for them. Our evaluation gives evidence that our MDE approach reduces the effort to develop agent-based simulations.

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AAMAS Conference 2017 Conference Paper

Modelling and Reasoning about Remediation Actions in BDI Agents

Joã o Faccin
Ingrid Nunes

Remediation actions are performed in scenarios in which consequences of a problem should be promptly mitigated when its cause takes too long to be addressed or is unknown. Existing approaches that address these scenarios are application-specific. Nevertheless, the reasoning about remediation actions as well as cause identification and resolution, in order to address problems permanently, can be abstracted in such a way that they can be incorporated to agents. In this paper, we present a domain-independent approach that extends the belief-desire-intention (BDI) architecture, providing means of modelling and reasoning over causal relationships and remediation actions.

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KER Journal 2015 Journal Article

An introduction to reasoning over qualitative multi-attribute preferences

Ingrid Nunes
Simon Miles
Michael Luck
Carlos J. P. Lucena

Abstract Research on preferences has significantly increased in recent years, as it involves not only many subproblems to be investigated, such as elicitation, representation, and reasoning, but has also been the target of different research areas, for example, artificial intelligence and databases. In particular, much work has focused on qualitative preferences, because these are closer to the way people express their preferences in comparison with quantitative preferences. Against this background, a large number of approaches have been proposed, associated with heterogeneous areas, so that these approaches are usually just compared with those of the same area. In response, we present in this paper a survey of approaches to qualitative multi-attribute preference reasoning, covering different research areas. We introduce selected approaches that propose different techniques and algorithms, which take as input qualitative multi-attribute preference statements following a particular structure specified by the approach. We analyse each approach in a systematic way and discuss their commonalities and limitations.

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EAAI Journal 2015 Journal Article

Decision making with natural language based preferences and psychology-inspired heuristics

Ingrid Nunes
Simon Miles
Michael Luck
Simone Barbosa
Carlos Lucena

Decision making is required by many tasks, such as shopping, nowadays assisted by software systems, and providing support to the decision making process is a feature that would significantly improve such systems. Many decision support systems and related approaches have been proposed to that purpose, but they often involve tedious elicitation processes or previously collected data. In this paper, we propose an automated decision making technique, which chooses an option from the set of those available based on preferences and priorities expressed in a high-level preference language, exploiting natural-language terms, such as expressive speech acts. Moreover, in order to make a decision, our technique goes beyond the provided preferences with psychology-inspired heuristics, which concern how humans make decisions, as provided preferences are typically not enough to resolve trade-offs among available options. Two studies were performed to evaluate our approach, and results indicate that our technique is effective both by comparing its recommendations with those made by a human expert, and by considering evaluation scores provided by users that experienced our technique.

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ECAI Conference 2014 Conference Paper

Pattern-based Explanation for Automated Decisions

Ingrid Nunes
Simon Miles
Michael Luck
Simone Diniz Junqueira Barbosa
Carlos Lucena

Explanations play an essential role in decision support and recommender systems as they are directly associated with the acceptance of those systems and the choices they make. Although approaches have been proposed to explain automated decisions based on multi-attribute decision models, there is a lack of evidence that they produce the explanations users need. In response, in this paper we propose an explanation generation technique, which follows user-derived explanation patterns. It receives as input a multi-attribute decision model, which is used together with user-centric principles to make a decision to which an explanation is generated. The technique includes algorithms that select relevant attributes and produce an explanation that justifies an automated choice. An evaluation with a user study demonstrates the effectiveness of our approach.

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AAMAS Conference 2012 Conference Paper

User-Centric Preference-Based Decision Making

Ingrid Nunes
Simon Miles
Michael Luck
Carlos de Lucena

The automation of user tasks by agents may involve decision making that must take into account user preferences. This paper introduces a decision making technique that reasons about preferences and priorities expressed in a high-level language in order to choose an option from the set of those available. Our technique includes principles from psychology, concerning the way in which humans make decisions. Our preference language is informed by a user study on preference expression, which is also used to evaluate our approach by comparing our results with those provided by a human expert. The evaluation indicates that our technique makes choices on behalf of the user with as good quality as made by the expert.

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AAMAS Conference 2010 Conference Paper

Supporting Prenatal Care in the Public Healthcare System in a Newly Industrialized Country

Ingrid Nunes
Ricardo Choren
Camila Nunes
Bruno F
aacute; bri
Fernando Silva
Gustavo Carvalho
Carlos J. P. De Lucena

Most of women's deaths related to pregnancy occur in newlyindustrialized countries. In association with gynecologistsand obstetricians of the Ant\^{o}nio Pedro University Hospitalo(HUAP) in Brazil, we have identified deficiencies in the prenatal care of the Brazilian public healthcare system that canbe computer-supported. They are mainly related to protocols that must be followed in the primary healthcare institutions and the referral process that must take place when ahigh risk pregnancy is identified, besides other functionalities that can be automated by a software application. In thispaper, the Prenatal Care Unified System (SUAP) projectwill be introduced, which provides a Multi-agent System forsupporting and monitoring the prenatal care. This projectuses agent technology to manage healthcare records, to actas a clinical decision support system, and to handle the logistics of high risk pregnancy cases. We also describe the challenges encountered during the implementation of the SUAPand discuss the benefits that an agent-based solution provided to the development of our system.

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