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.