Artificial Intelligence

Our artificial intelligence research addresses the central challenges of machine cognition, both from a theoretical perspective and from an empirical, implementation-oriented perspective.

Topics:

  • Automatic Programming
    • Generic Programs, Partial Evaluation, Design Representation, Inference, Programming Interfaces.
  • Automated Reasoning and Interactive Theorem Proving
    • Simplification; Induction; Concept-formation; Lemma discovery; User interfaces; Hardware and software modeling and verification.
  • Autonomous Agents
    • Learning agents; Bidding agents; Robots; Game AI.
  • Computer Vision
    • Object and activity recognition; Content-based retrieval; Learning and vision; Robot vision; Biologically inspired vision.
  • Data Mining
    • Database search and mining; Large-scale data analysis; Social network analysis; Network estimation.
  • Knowledge Representation and Reasoning
    • Knowledge representation languages: Description logic, frames, graphical representations; Knowledge content areas: Temporal, Spatial, Causal knowledge; Ontology; Semantic matching; Constraint satisfaction; Expert systems; Semantic web; Cognitive modeling: memory models; Belief revision and truth maintenance.
  • Learning Theory
    • Computational and statistical analysis of learning algorithms; Online learning; Active learning; Probabilistic inference.
  • Logic-based AI
    • Commonsense knowledge; Reasoning about actions; Nonmonotonic reasoning; Answer set programming.
  • Machine Learning
    • Supervised learning; Reinforcement learning; Transfer learning; Active learning; Online learning; Statistical relational learning; Optimization; Graphical models; Nonparametric models; Probabilistic inference.
  • Multiagent Systems
    • Multiagent learning; Multirobot systems; Game theory.
  • Natural Computation
    • Neural networks; Evolutionary computation; Computational neuroscience; Cognitive science.
  • Natual Language Processing
    • Syntactic parsing; Semantic analysis; Information extraction; Machine translation; Machine reading; Connectionist models of lexical, sentence, and story processing.
  • Robotics
    • Robot learning; Developmental robotics; Multirobot systems; Multilegged walking; Embodied Cognition.
  • AI Applications
    • Autonomous driving; Robot soccer; Question answering; Math and Physics Problem Solving; Nonlinear control; Game playing; Fraud detection.

Courses: 

  • CS 343 Artificial Intelligence
  • CS 344M Autonomous Multiagent Systems
  • CS 371R Information Retrieval and Web Search
  • CS 376 Computer Vision
  • CS 342 Neural Networks
  • CS 378 Autonomous Vehicles Driving in Traffic
  • CS 378 Computational Brain
  • CS 378 Computational Intelligence in Game Design
  • CS 378 Introduction to Data Mining
  • CS 378 Knowledge Based Systems
  • CS 388 Natural Language Processing
  • CS 388L Introduction to Mathematical Logic
  • CS 391D Data Mining: A Mathematical Perspective
  • CS 391L Machine Learning
  • CS 393R Autonomous Robots
  • CS 394F Knowledge Representation and Reasoning
  • CS 394N Neural Networks
  • CS 394P Automatic Programming
  • CS 394R Reinforcement Learning: Theory and Practice
  • CS 395T Logic-Based Artificial Intelligence
  • CS 395T Object Recognition
  • CS 395T Introduction to Cognitive Science
  • CS 395T Learning Theory
  • UGS 301 Mirrors on Ourselves: Attempts to Build Artificial People

Research Groups: