Professor Felipe Meneguzzi

Chair in Computing Science

Accepting PhDs

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School/Department: School of Natural and Computing Sciences

Biography

I am a researcher on automated planning, goal and plan recognition, multiagent systems, BDI agents, and machine learning. I currently hold a Chair of Computing Science at the 黑料网. I am a and of . I was a Professor of AI at the Pontifical Catholic University of Rio Grande do Sul in Brazil, where I remain as a Bridges Professor. Before my current position, I worked as a Project Scientist in Multiagent Systems at the of after completing a Postdoctoral Fellowship at the same university. I obtained my PhD degree at , with a thesis on under the supervision of Professor and co-supervised by Professor . Prior to my full-time academic career, I worked in the industry as a contractor for , and worked on a variety of projects with some very interesting .

For further information, visit my .

Qualifications

PhD Artificial Intelligence
2009 - King's College London

External Memberships

Executive Council of the AAAI
Special Committee on AI for the Brazilian Computer Society
Bridges Professor at the Pontifical Catholic University of Rio Grande do Sul

Prizes and Awards

in 2024;
;
;
1st place at the () in 2020;
Distinguished Visiting Fellow award from the
Best Student paper at IJCNN 2017:
Visionary workshop paper at AAMAS 2017: ;
as well as
1st place at the
2nd place at the ; and
Runner up to the Microsoft Research Faculty Fellowship in 2013.

Research

Research Overview

My overall research area is Artificial Intelligence and my research spans the areas of Automated Planning, Autonomous Agents and Applications of Machine Learning. The main goal of my research is to develop practical reasoning mechanisms as a means to both refine the capabilities of autonomous agents and to understand reasoning in general. To accomplish this objective, I work on integrating data-driven and symbolic techniques for reasoning and decision-making while maintaining a low complexity for the description formalisms, helping to achieve explainability for human users.

Research Areas

Accepting PhDs

I am currently accepting PhDs in Computing Science.

Please get in touch if you would like to discuss your research ideas further.

Computing Science

Supervising
Accepting PhDs

View Research Area

Research Specialisms

Artificial Intelligence
Machine Learning

Our research specialisms are based on the Higher Education Classification of Subjects (HECoS) which is , published under the licence.

Teaching

Programmes

BSc Computing Science
Undergraduate, 4 year, September start
MSc Artificial Intelligence
Postgraduate, 3 stage, January start
MSc Artificial Intelligence
Postgraduate, 3 semester, September start
MEng Computing Science (5 years)
Undergraduate, 5 year, September start
MEng Computing Science (Artificial Intelligence)
Undergraduate, 5 year, September start
BSc Computing Science and Mathematics
Undergraduate, 4 year, September start
BSc Computing Science and Physics
Undergraduate, 4 year, September start

Courses

Publications

Update

黑料网

Biography

Qualifications

External Memberships

Prizes and Awards

Research Overview

Research Areas

Accepting PhDs

Computing Science

Research Specialisms

Programmes

Courses

Identifying Potential Conflicts between Norms in Contracts

Integrating Ontologies with Multi-Agent Systems through CArtAgO Artifacts

On the Design of Symbolic-Geometric Online Planning Systems

Simulating Normative Behaviour in Multi-Agent Environments using Monitoring Artefacts

Towards Practical Argumentation-Based Dialogues in Multi-Agent Systems

Utilizing Permission Norms in BDI Practical Normative Reasoning

Imperfect norm enforcement in stochastic environments:: an analysis of efficiency and cost tradeoffs

A smart home model using JaCaMo framework

Dealing with Ambiguity in Plan Recognition under Time Constraints

Norm Monitoring with Asymmetric Information: Monitoring Strategies with Asymmetric Information in Stochastic Environments

Analyzing the tradeoff between efficiency and cost of norm enforcement in stochastic environments

Analyzing the tradeoff between efficiency and cost of norm enforcement in stochastic environments populated with self-interested agents

An Approach for Argumentation-based Reasoning Using Defeasible Logic in Multi-Agent Programming Languages

BioPlan: An API for Classical Planning on BioCrowds

Classifying Brain States for Cognitive Tasks: a Functional MRI Study in Children with Reading Impairments

Formal Semantics of Speech Acts for Argumentative Dialogues

Integrating Multi-Agent Systems in JaCaMo using a Semantic Representations

Planning Interactions for Agents in Argumentation-Based Negotiation

Probabilistic Plan Recognition for Proactive Assistant Agents

Semantic representations of agent plans and planning problem domains

Using ontologies as semantic representations of hierarchical task network planning domains

Declarative planning in procedural agent architectures

A first-order formalization of commitments and goals for planning

Hierarchical planning about goals and commitments

Norm identification through plan recognition

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Books and Reports

Chapters in Books, Reports and Conference Proceedings

Contributions to Conferences

Contributions to Journals

Contributions to Specialist Publications

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Other Contributions