Brown Computer Science
 Home Search  
 About Us
 Graduate Study
 Undergraduate Study
*  AI
   Comp Finance
 Software Catalog
 Rooms & Labs
 Computing Systems
 Industrial Relations

Artificial Intelligence

Artificial Intelligence at Brown University is concerned with theoretical and empirical studies involving problems ranging from natural language interpretation and machine perception to mobile robotics and disembodied agents, such as those employed in searching the World Wide Web. The research emphasizes algorithmic issues as they arise in using sophisticated models (many of them probabilistic models) to represent and solve such problems. The applications include auctions and other economic transactions on the World Wide Web, data mining, extraction of semantic content from text, face and gesture recognition, and planning and control for mobile robots. The basic techniques borrow from information and game theory, statistics, probability theory, operations research, Bayesian decision theory, and the design and analysis of algorithms. Faculty and students (both graduate and undergraduate) are involved in multi-disciplinary research projects collaborating with such departments as Applied Mathematics, Brain Science, Cognitive and Linguistic Sciences, Engineering, and the School of Medicine.




Major Grants

Research Groups

BLLIP (Brown Laboratory for Linguistic Information Processing)
BLLIP is research group for the stufy of computational linguistics (or, if you prefer, Natural Language Processing). It is comprised of members from both the Computer Science and the Cognitive and Linguistic Science departments.


Every week
  • BLLIP group meeting, for discussion of current work in the Natural Language Processing (i.e. computational linguistics) group. Every Friday at 11am in the Cog Sci conference room (Metcalf 229?).
  • AI Lunch, for presentations of current and in-progress AI papers, practice talks, etc. Often on Wednesdays at noon in the conference room (CIT 506).

Information on particular areas

Partially observable Markov decision processes (POMDPs)
Uncertainty in AI
Bayesian networks, belief networks, influence diagrams
Planning and scheduling
Page Owner: Don Blaheta Last Modified: Tue Jun 4 13:46:47 2002