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Interdisciplinary Lab for Intelligent and Adaptive Systems (ILIAS)

 

The "Intelligent and Adaptive Systems" research area is concerned with - 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.
    • Normative Multi-Agent Systems, Cognitive Agents/Robots, Decision Systems, Computational Social Choice and Agreement Technologies.
  • Computational Intelligence:
    Adaptive systems exploiting learning, flexible probabilistic, or nature-inspired computing models to deal with opaque, dynamic contexts, and big data.
    • Bio-inspired Computing, Data Science, Text/Data Mining, Knowledge Discovery, Information Theory.
  • Computational/Applied Logic:
    Logic-based methods for analyzing/specifying computational systems, providing advanced knowledge representation and reasoning techniques for intelligent agents.
    • Agent logics, Normative Reasoning, Knowledge Representation, Uncertain Inference, Foundations of Reasoning.

The "Intelligent and Adaptive Systems" research area is concerned with - 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.
    • Normative Multi-Agent Systems, Cognitive Agents/Robots, Decision Systems, Computational Social Choice and Agreement Technologies.
  • Computational Intelligence:
    Adaptive systems exploiting learning, flexible probabilistic, or nature-inspired computing models to deal with opaque, dynamic contexts, and big data.
    • Bio-inspired Computing, Data Science, Text/Data Mining, Knowledge Discovery, Information Theory.
  • Computational/Applied Logic:
    Logic-based methods for analyzing/specifying computational systems, providing advanced knowledge representation and reasoning techniques for intelligent agents.
    • Agent logics, Normative Reasoning, Knowledge Representation, Uncertain Inference, Foundations of Reasoning.
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