Research area Intelligent and Adaptive Systems

Computational reasoning given uncertain information

UniLu ResearchArea DCS IntelligentAndAdaptiveSystems

We work at the crossroads between theoretical foundations and algorithmic realization of computational intelligence and user modelling.

About

The Intelligent and Adaptive Systems research investigates the theoretical foundations and the algorithmic realization of information processing and reasoning in complex and dynamic environments given limited resources and incomplete or uncertain information. It encompasses three overlapping subthemes and their corresponding topics:
• Intelligent agents:
Computational techniques for autonomous problem solving and decision making in complex environments populated by humans and/or artificial agents.
• Computational Intelligence:
Adaptive systems exploiting learning, flexible probabilistic, or nature-inspired computing models to deal with opaque, dynamic contexts, big data, and machine learning.
• Computational/Applied Logic:
Logic-based methods for analysing/specifying computational systems, providing advanced knowledge representation, and reasoning techniques for intelligent agents.

The following professors and their teams contribute to this research area:
• Pascal BOUVRY:
o Computer Networks
o Cloud Computing
o Parallel and evolutionary computing
• Luis LEIVA:
o Human-Computer Interaction
o Information Retrieval and Learning
o Machine Learning
o Natural Language Processing
• Christoph SCHOMMER:
o Natural Language Processing
o Artificial Companions
o Data Mining and Knowledge Discovery
o Data Science
o Information Retrieval and Learning
o Machine Learning
o Natural Language Processing
o Data Science
• Leon VAN DER TORRE:
o Agreement Technologies and Cognitive Dynamics
o Foundations of Reasoning and AI
o Knowledge Representation and Natural Language Semantics
o Logics for Intelligent Agents/Robots
o Normative Multi-Agent Systems and Deontic Reasoning
o Uncertain and Nonmonotonic Inference
• Decebal MOCANU
o Machine learning
o Sparse neural networks.

Research groups