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Intelligent Systems Lab
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A lab developing robust and adaptive next-generation artificial intelligence.
AboutAbout the lab
Building robust and adaptive next-generation artificial intelligence
The Intelligent Systems Lab develops next-generation artificial intelligence that is robust and adaptive.
It tackles weaknesses such as an AI that learned 19x19 Go being unable to play 9x9 Go, and image recognition being fooled by a change of a single pixel.
By developing new mechanisms and paradigms of intelligence, the lab aims to improve robustness and adaptability.
The lab's website states that students can conduct research using state-of-the-art CPU and GPU servers.
Key terms
- Robustness
- The property of maintaining performance despite noise, attacks, or changes in the environment
- Reinforcement learning
- A machine learning method that learns how to choose good actions through trial and error
- Evolutionary computation
- A computational method that, modeled on biological evolution, improves candidate solutions by repeatedly reselecting them
ResearchResearch themes
This lab aims at next-generation artificial intelligence that is robust and adaptive. It studies new reinforcement learning methods, the evolution of neuron models, analysis using attacks on artificial intelligence, and new optimization methods.
*Illustrative imageClassifiers that adapt to changing conditions
The lab is developing NOTC, the first method to unify the two paradigms of reinforcement learning: the value function approach and direct policy search. It is a type of Self-Organizing Classifier whose states are updated automatically through experience, and it can adapt even when the problem changes, such as in a maze whose shape changes.
*Illustrative imageSUNA, which evolves neurons
The lab is developing SUNA, a reinforcement learning method based on evolutionary computation that unifies the functions of most proposed neurons into a single Unified Neural Model. It evolves its own structure and can also learn non-Markov problems.
*Illustrative imageAnalysis through attacks on artificial intelligence
Using attacks on learning systems as one analysis method, the lab investigates how they understand categories such as "horse" and "ship." In research covered by BBC News, it showed that changing just one pixel can change the classification.
*Illustrative imageSAN, a new optimization algorithm
SAN is a very simple multi-objective optimization algorithm that outperformed all other algorithms on the most difficult multi-objective benchmarks. The analysis attributes this to the use of independent subpopulations, which avoids competition within the population of candidate solutions.
MembersFaculty
The members of the Intelligent Systems Lab consist of faculty, research assistants, doctoral, master's, and undergraduate students, and research students.
- Associate ProfessorDanilo Vasconcelos Vargas
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Aprendizado por Reforço” Leomaurodesenv / CC0 (cropped)
- Classifiers that adapt to changing conditions: “Aggregate sorting plant ^ conveyors in Wellington quarry - geograph.org.uk - 5898557” Richard Law / CC BY-SA 2.0 (cropped)
- SUNA, which evolves neurons: “Artificial Neural Network with Chip” mikemacmarketing / original posted on flickr Liam Huang / clipped and posted on flickr / CC BY 2.0 (cropped)
- Analysis through attacks on artificial intelligence: “Outdoor Security Patrol Robot” Rlistmedia / CC BY 4.0 (cropped)
- SAN, a new optimization algorithm: “Meta-Optimization Concept” Pedersen, M.E.H., Tuning & Simplifying Heuristical Optimization, PhD Thesis, 2010, University of Southampton, School of Engineering Sciences, Computational Engineering and Design Group. / Public domain (cropped)
- Related lab (Mathematical Engineering and Information Circuits Lab): “Communication theory” JuanOF9 / CC BY-SA 4.0 (cropped)
- Related lab (Stringology Lab): “A diagram of the Aho-Corasick string search algorithm extracted” User:Algorithmist / CC0 (cropped)
- Related lab (Information Security & Multimedia Security Lab): “Homomorphic Encryption Setup” Aaadir / CC0 (cropped)
- Related lab (Algorithm Theory Lab): “Jungheinrich Autonomous Robot arculee M” Marc Auledas Noguera (Auledas) / CC BY 4.0 (cropped)
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