MS & PhD program in AI, robotics, evolutionary comp, etc.

[Maja Mataric]

In May 1994 Brandeis University announced the opening of the new Volen
National Center for Complex Systems with the goal of promoting
interdisciplinary research and collaboration between faculty from
Computer Science, Linguistics, Neuroscience, Psychology, Biology and
Physics.  The Center, whose main mission is to study cognitive
science, brain theory, and advanced computation, has already earned
accolades from scientists world wide, and continues to expand.

Brandeis is located in Waltham, a suburb 10 miles west of Boston, with
easy rail access to both Cambridge and downtown. Founded in 1948,
it is recognized as one of the finest private liberal arts and science
universities in the United States. Brandeis combines the breadth and range of
academic programs usually found at much larger universities, with
the friendliness of a smaller and more focused research community.

The Computer Science Department is located in the Volen Center and is
the home of four Artificial Intelligence faculty actively involved in
the Center activities and collaborations: Rick Alterman, Maja Mataric,
Jordan Pollack, and James Pustejovsky. In addition to SGI
and HP workstations, the Dept owns a 4096 processor Maspar MP2 and a
16 processor SGI challenge supercomputer, and has new electronics and
metalworking facilities to support innovative research.

Rich Alterman's research interests are in the general areas of
artificial intelligence and cognitive science and include such topics
as: planning and activity, discourse and text processing, memory and
case based reasoning, and human-computer interaction.  A recent focus
has been on theories of pragmatics and usage as they apply to the
problems of man-machine interaction.  One project resulted in the
construction of a detailed cognitive model of an individual learning
how to use a device; significant features of this model included,
techniques for skill acquisition and learning, a method for organizing
procedural knowledge in memory, and "reading techniques" for actively
seeking out and interpreting instructions that are relevant to a given
"break down" situation.  A second project develops a method of system
adaptation where the system automatically evolves to the specifics of
its task environment, after is deployed, based on the history of usage
of the system for a given task.  A third project develops techniques
that support the evolution and maintenance of a collective memory for
a community of distributed heterogeneous agents who plan and work
cooperatively.  Professor Alterman is especially looking for students
(and postdocs) with backgrounds in planning and activity, memory and
case based reasoning, text and information retrieval, and
human-computer interaction.

Maja Mataric's research focuses on understanding systems that
integrate perception, representation, learning, and action.  Her work
is applied to problems of synthesis and analysis of complex behavior
in situated agents and multi--agent systems.  Mataric's Interaction
Lab (http://www.cs.brandeis.edu/~agents) covers three main project
areas: 1) multi-robot projects (dynamic task division, specialization,
learning behaviors and behavior selection, learning social rules,
distributed spatial representations, synthesis and analysis of
multi-robot controllers; using 24 mobile robots and a dynamical robot
simulator.); 2) multi-agent projects (cooperation vs. competition,
dominance hierarchies, modeling markets, economies, and ecologies with
non-rational agents, synthesizing and analyzing complex group
behavior; using various multi-agent simulations); and 3) multi-modal
representation projects (modeling learning by imitation involving
perception, representation, and motor control, sensory-motor mappings,
learning new motor behaviors, adapting internal motor programs,
attention, and analysis of moving images; using a fully dynamic human
torso simulation). Prof. Mataric encourages students with interests
and/or backgrounds in AI, robotics, autonomous agents, machine
learning, cognitive science, and cognitive neuroscience to apply.  For
more information see http://www.cs.brandeis.edu/~maja.

Jordan Pollack's research interests lie at the boundary between neural
and symbolic computation: How could simple neural mechanisms organized
naturally into multi-cellular structures by evolution provide the
capacity necessary for cognition, language, and general intelligence?
This view has lead to successful work on how variable tree-structures
could be represented in neural activity patterns, how dynamical
systems could act as language generators and recognizers, and how
fractal limit behavior of recurrent networks could represent mental
imagery. One major current focus is on co-evolutionary learning, in
which the learning task is dynamically constructed as a carrot,
dangling in front of the machine learning horse. In the Dynamical and
Evolutionary Machine Organization (DEMO), we are working on
co-evolution in strategic game playing agents, cognitive tasks, and
teams of agents who cooperate and communicate on complex tasks. As
substrate we use recurrent neural networks and genetic programs, and
use the 4096 processor Maspar machine. Professor Pollack is especially
looking for students (and postdocs) with backgrounds in NN's & GA's, 
IFS's, robot building, and evolutionary agents. For more information
see http://www.cs.brandeis.edu/~pollack or http://www.demo.cs.brandeis.edu

James Pustejovsky conducts research in the areas of computational
linguistics, lexical semantics, and information retrieval and
extraction.  The main focus of his current research is on the
computational and cognitive modeling of natural language meaning.
More specifically, the investigation is in how words and their
meanings combine to meaningful texts.  This research has focused on
developing a theory of lexical semantics based on a methodology making
use of formal and computational semantics.  There are several projects
applying the results of this theory to Natural Language Processing,
which in effect, empirically test this view of semantics. These
include: an NSF grant with Apple to automatically construct index
libraries and help systems for applications; a DEC grant to
automatically convert a trouble-shooting text-corpus into a case
library. He recently compleated a joint project with aphasiologist
Dr. Susan Kohn on word-finding difficulties and sentence generation in
aphasics.  For more information see
http://www.cs.brandeis.edu/~jamesp/

The four AI faculty work together and with other members of the Volen
Center, creating new interdisciplinary research opportunities in areas
including cognitive science (http://fechner.ccs.brandeis.edu/cogsci.html)
computational neuroscience, and complex systems at Brandeis University.

To get more information about the Volen Center for Complex Systems,
about the Computer Science Department, and about other faculty, see:
http://www.cs.brandeis.edu/dept

The URL for the graduate admission information is 
http://www.cs.brandeis.edu/dept/grad-info/application.html

Graduate applications will begin to be reviewed on March 18th.