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
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
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
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
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)
Algorithmic Intelligence Group
Center for Computing and Communication Technologies
University of Bremen
Am Fallturm 1, D-28357 Bremen