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Luis da Cunha Lamb


Luis da Cunha Lamb

Universidade Federal do Rio Grande do Sul
Departamento de Informática Teórica

Steering committe





Information extracted from Lattes platform


Last update: 2021/03/31


Degrees

Ph.D. PhD in Computing Science na Imperial College London University Of London em 2000
M.Sc. Computação na Universidade Federal do Rio Grande do Sul em 1995
B.Sc. Ciências de Computação, Ênfase Softw. de Aplicação na Universidade Federal do Rio Grande do Sul em 1992
B.Sc. Eng Elétrica Incompleto na Universidade Federal do Rio Grande do Sul em 1988
B.Sc. Ciências de Computação, Ênfase Software Básico na Universidade Federal do Rio Grande do Sul em 1992


Current projects

2010 a AtualLógicas Não-Clássicas em Ciência da Computação e Inteligência Artificial: Fundamentos e Aplicações
O objetivo maior deste projeto é: estudar, desenvolver e aplicar técnicas e modelos lógicos não-clássicos à ciência da computação e inteligência artificial, visando o desenvolvimento de sistemas computacionais que contemplem habilidades cognitivas, tendo em vista os desafios de integrar a Ciência da Computação às ciências naturais, biológicas e sociais. Trata-se de objetivo de longo prazo, tendo em vista o histórico de resultados do pesquisador, que tem trabalhado em lógica aplicada à computação, inteligência artificial e cognição por aproximadamente dez anos, apresentando produção científica crescente e a necessidade de pesquisa interdisciplinar. Para isto, é necessário estudar a modelagem de raciocínio cognitivo através de sistemas lógicos, incluindo: raciocínio temporal, modal, epistêmico e sob incerteza, utilizando técnicas desenvolvidas em lógica, de forma integrada a modelos de inteligência artificial e cognição, sejam eles baseados em modelos conexionistas (neurais), simbólicos ou integrados (neuro-simbólicos) [dGlG2009, Hinton 2005; PNL 2008; Sun 2009; Valiant 2009].
Integrantes: Luís da Cunha Lamb (coordenador), Ricardo Matsumura de Araújo, Daniel S. Farenzena, d'Avila Garcez, Artur S., Marcio Dorn, Diego Vrague Noble, Felipe Grando, Marcelo de Oliveira Rosa Prates.

Current applied research projects

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Recent publications

Articles in journals

A ground truth contest between modularity maximization and modularity density maximization
2020. ARTIFICIAL INTELLIGENCE REVIEW.
A Reactive-Darwinian Model for the ultimatum game: On the dominance of moderation in high diffusion
2020. Communications in Nonlinear Science and Numerical Simulation.
Assessing gender bias in machine translation: a case study with Google Translate
2019. NEURAL COMPUTING & APPLICATIONS.
Neural-symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning
2019. THE IFCOLOG JOURNAL OF LOGICS AND THEIR APPLICATIONS.
Machine Learning in Network Centrality Measures
2018. ACM COMPUTING SURVEYS.
Human-Like Neural-Symbolic Computing
2017. DAGSTUHL REPORTS.
Exact Computational Solution of Modularity Density Maximization by Effective Column Generation
2017. COMPUTERS & OPERATIONS RESEARCH.
Efficient Modularity Density Heuristics for Large Graphs
2017. European Journal of Operational Research.
Randomness and arbitrary coordination in the reactive ultimatum game
2016. Communications in Nonlinear Science & Numerical Simulation.
The cost of search and evaluation in online problem-solving social networks with financial and non-financial incentives
2016. First Monday (Online).
Universality, correlations, and rankings in the Brazilian universities national admission examinations
2016. Physica. A (Print).
Connectionist Modal Logic: Representing Modalities in Neural Networks
2007. Theoretical Computer Science.
A Connectionist Computational Model for Epistemic and Temporal Reasoning
2006. Neural Computation.
Connectionist Computations of Intuitionistic Reasoning
2006. Theoretical Computer Science.

Papers in conferences

Discrete and Continuous Deep Residual Learning over Graphs
2021. 13th International Conference on Agents and Artificial Intelligence - ICAART.
Superpixel Image Classification with Graph Attention Networks
2020. SIBGRAPI Conference on Graphics, Patterns and Images.
Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases
2020. ICANN - International Conference on Artificial Neural Networks.
Exact Signed Modularity Density Maximization Solutions and Their Real Meaning
2020. IEEE Congress on Evolutionary Computation.
Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective
2020. International Joint Conference on Artificial Intelligence IJCAI-2020.
Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP
2019. AAAI - Conference on Artificial Intelligence.
Graph Colouring Meets Deep Learning: Effective Graph Neural Network Models for Combinatorial Problems
2019. ICTAI - IEEE International Conference on Tools with Artificial Intelligence.
On the Role of Central Individuals in Influence Propagation
2019. ICAART - International Conference on Agents and Artificial Intelligence.
Multitask Learning on Graph Neural Networks: Learning Multiple Graph Centrality Measures with a Unified Network
2019. ICANN - International Conference on Artificial Neural Networks.
Problem Solving at the Edge of Chaos: Entropy, Puzzles and the Sudoku Freezing Transition
2018. ICTAI - IEEE International Conference on Tools with Artificial Intelligence.
Computing Vertex Centrality Measures in Massive Real Networks with a Neural Learning Model
2018. 2018 International Joint Conference on Neural Networks (IJCNN).
Novel Parallel Anytime A* for Graph and Network Clustering
2018. IEEE Congress on Evolutionary Computation.
On Quantifying and Understanding the Role of Ethics in AI Research: A Historical Account of Flagship Conferences and Journals
2018. GCAI2018. 4th Global Conference on Artificial Intelligence.
On the Effectiveness of the Block Two-Level Erdős-Rényi Generative Network Model
2018. ISCC - International Symposium on Computers and Communications.
Effective Ant Colony Optimization Solution for the Brazilian Family Health Team Scheduling Problem
2018. ICTAI - IEEE International Conference on Tools with Artificial Intelligence.
Neural Networks Models for Analyzing Magic: The Gathering Cards
2018. ICONIP - International Conference on Neural Information Processing.
Novel Clique enumeration heuristic for detecting overlapping clusters
2017. 2017 IEEE Congress on Evolutionary Computation (CEC).
Genetic algorithm for epidemic mitigation by removing relationships
2017. the Genetic and Evolutionary Computation Conference.
On approximating networks centrality measures via neural learning algorithms
2016. 2016 International Joint Conference on Neural Networks (IJCNN).
A New Model and Heuristic for Infection Minimization by Cutting Relationships
2016. International Conference on Neural Information Processing.
An Analysis of Centrality Measures for Complex and Social Networks
2016. GLOBECOM 2016 2016 IEEE Global Communications Conference.
On the role of degree influence in suboptimal modularity maximization
2016. 2016 IEEE Congress on Evolutionary Computation (CEC).
Memetic Networks: analyzing the effects of network properties in multi-agent performance
2008. Twenty-Third AAAI Conference on Artificial Intelligence (AAAI-08).

Extended abstracts in conferences

Efficient quantitative heuristics for graph clustering
2017. the Genetic and Evolutionary Computation Conference Companion.
Efficient Stochastic Local Search for Modularity Maximization
2016. Genetic and Evolutionary Computation Conference - GECCO 2016.
Neural-symbolic cognitive agents: architecture, theory and application
2014. 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2014).
Combining Machine Learning and Optimization Techniques to Determine 3-D Structures of Polypeptides
2011. 22nd International Joint Conference on Artificial Intelligence.
Towards Social Problem-Solving with Human Subjects
2011. 22nd International Joint Conference on Artificial Intelligence (IJCAI-11).

Abstracts in conferences

Fundamentos de interpretação abstrata
2002. XIV Salão de Iniciação Científica da UFRGS.
Labelled Natural Deduction for First-Order Conditional Logic
2002. Logic Colloquim 2001 - European Summer Meeting of the Association for Symbolic Logic.
Descrição de um Software Estatístico Orientado a Objetos
1991. III Salão de Iniciação Científica da UFRGS.
Método de Cramer através de Estrutura de Dados Híbrida
1991. Congresso Nacional de Matemática Aplicada e Computacional (CNMAC).
Um Software Interativo para Resolver Problemas de Cálculo Numérico
1990. II Salão de Iniciação Científica da UFRGS.

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Current students

MS

João Marcos Flach. Logical Foundations of AI (area). Início: 2020. Universidade Federal do Rio Grande do Sul (Orientador principal)

PhD

Marcio Nicolau. Machine Learning Applications/Agritech/Image interpretation. Início: 2020. Universidade Federal do Rio Grande do Sul (Orientador principal)
Pedro Henrique da Costa Avelar. Graph neural networks; deep learning (provisional title). Início: 2019. Universidade Federal do Rio Grande do Sul (Orientador principal)

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