[TZI]  [Computer Science Department]  [University of Bremen] 

Events in Algorithmic Intelligence

International Workshop on Algorithmic Intelligence

BMI User Behaviour Modeling

Workshop on Movement Pattern Analysis

German Conference on Artificial Intelligence

International Conference on Automated Planning and Scheduling

International Workshop on Intelligent Security

International Workshop on Graph Inspection and Traversal Engineering

Teaching Algorithmic Intelligence (SS 2011)

Lecture on Digital Communication and Media

Lecture on Algorithm Theory

Lecture on Wearable Computing

Lecture on Machine Learning

Lecture on Video Processing

Lecture on Computer Vision

Lecture on Plan Recognition

Lecture on Artificial Intelligence

Lecture on Logistics

Projects in Algorithmic Intelligence













SFB Autonomous Cooperating Logistic Prozesses

Model Checking on SSD and GPU

Planning Algorithms for General Game Playing

Algorithmic Intelligence at

IT University of Copenhagen

Research Group

Algorithmic Intelligence is a collective and pragmatic term for the range of algorithmic methods that have been identified as key revenue drivers in companies including Google, Netflix, UPS, and Walmart. The topic contrasts the term Artificial Intelligence that carries the meaning that there is intelligence, but nothing is real. With Algorithmic Intelligence we stress the focus on the impact that well-founded AI algorithms have for the success in practice.


One obstacle for cross-fertilization between the algorithmic and AI community has been the perceived emphasis of the term "intelligence". It is, therefore, essential to have the term "algorithmic" attached to it to interface with people in theory, at least to those that aim to change something in the real-world. Of course, an algorithm as a sequence of instructions cannot be intelligent on its own, but by seing it performing well, it might be attributed of being smart.

In his book Artificial Intelligence, A Modern Myth John Kelly states:

    The nature of human intelligence is elusive and does not admit of a tractable formalism or effective characterization. There is a wide divergence between the nature of machine and human as currently understood and as revealed by conceptual analysis. Computers are misleadingly characterized as symbol processors. In themselves they are merely repositories and manipulators of uninterpreted physical shapes, merely formal functional media. Computer systems, whether traditional hardware or software [...], are best understood as texts. Computer have no ability to act in any deep sense of the word. They do not do anything. The dependence of computers on human articulation points to fundamental limits to their potential, because of the fact that human experience, even language-mediated experience, is ultimately rooted in ineffability. Unfortunately the deployment of explicit language conditions and encloses what can be thought. Misconceptions about computer potential and misrepresentation of computer power emerge from excessive anthropomorphisation of machines; the lure of an existential fallacy of the fallacy of misplaced concreteness; the list fallacy, i.e. the reliance on a mere list to provide a necessary unity; excessive respect for the power of science; belief in the ad rem adequacy of rationality; and belief in the adequacy of language.
Besides these philosophical insights there is real need for software systems capable of taking action in real-time situations with algorithms that adapt, generalize, assist and improve over time. Algorithmic Intelligence has a core that is methodical. The field has grown beyond philosophical problems of artificial intelligence with methods applied in mainstream products. With Algorithmic Intelligence we give this trend a name. Effectively, the term relates closer the second meaning of intelligence, as in business intelligence. The related term Comptuational Intelligence is bound rather to evolutionary, neural networks and fuzzy logic aspects.


There is real need for software systems capable of taking action in real-time situations involving sensor inputs, state variables, situation assessments and environmental conditions. Algorithmic Intelligence thus tributes to the fact that computer action for real-life applications refers to an algorithmic and constructive process. The machine is an information constructor, assisted by humans to create machine representations of objective reality. New information is then linked to prior knowledge. The focus also includes tackling optimization problems where there is no learning as such, but AI come in as a way of dealing with computational hardness. Our mission is promote cross-fertilization among researchers working on related topics from different perspectives.


  • Stefan Edelkamp (Principal Investigator, Search & Planning Algorithms)
  • Björn Gottfried (Principal Investigator, Assitive Algorithms)
  • Otthein Herzog (Principal Investigator, Real-Time AI)
  • Gerrit Kalkbrenner (Principal Investigator, Mobile Media & Communication)
  • Hagen Langer (Principal Investigator, Language Processing Algorithms)
  • Michael Lawo (Principal Investigator, Human-Computer Interaction)
  • Hartmut Messerschmidt (Principal Investigator, Analytical Intelligence)
  • Arne Schuldt (Principal Investigator, Multi-Agent Systems)
  • Martin Stommel (Principal Investigator, Algorithmic Vision)
  • Thomas Wagner (Principal Investigator, Machine Learning & Plan Recognition)

  • Hannes Bauman (PhD Student, Mobile Solutions)
  • Jan-Ole Bernd (PhD Student, Graduate College)
  • Carsten Elfers (PhD Student, Imprecise Pattern Matching with CRF)
  • Mirko Horstmann (PhD Student, Assisted Ontology Generation)
  • Hendrik Iben (PhD Student, Wearable Computing)
  • Andreas Kemnade (PhD Student, Wearable Solutions)
  • Peter Kissmann (PhD Student, Generalized Intelligence with BDDs)
  • Rüdiger Leibrandt (PhD Student, Wearable Solutions)
  • Andree Lüdtke (PhD Student, Multimedia Retrieval)
  • Markus Modzelewski (PhD Student, Assisted Living)
  • Florian Pantke (PhD Student, Dynamic Planning with Guide Numbers)
  • Markus Schröder (PhD Student, Model Checking and Security)
  • Damian Stoppe (PhD Student, Computer Vision)
  • Damian Sulewski (PhD Student, Model Checking on SSD and GPU)
  • Tobias Warden (PhD Student, Logistics)
  • Till von Wenzlawowicz (PhD Student, Computer Vision)
  • Xin Xing (PhD Student, Ubiquitious Computing)
  • etc.


Algorithmic Intelligence Group
Center for Computing and Communication Technologies
University of Bremen

Am Fallturm 1, D-28357 Bremen

Phone: +49-(0)421-218-4676
Fax: +49-(0)421-218-7196

EMail: ai@tzi.de

Algorithmic Intelligence

Algorithmic Intelligence (ai@tzi.de)