MIT: Independent Activities Period: IAP

IAP 2014 Activities by Sponsor - Institute of Electrical and Electronic Engineers

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Concurrent Learning-Based Adaptive Dynamic Programming for Autonomous Agents

Warren Dixon, Professor of Mechanical and Aero Engineering, U. of Florida

Jan/15 Wed 11:00AM-12:00PM 4-149

Enrollment: Unlimited: No advance sign-up
Prereq: none

Analytical solutions to the infinite horizon optimal control
problem for continuous time nonlinear systems are generally not possible
because they involve solving a nonlinear partial differential equation.
Another challenge is that the optimal controller includes exact knowledge
of the system dynamics. Motivated by these issues, researchers have
recently used reinforcement learning methods that involve an actor and a
critic to yield a forward-in-time approximate optimal control design. This
presentation describes a forward-in-time dynamic programming approach that
exploits the use of concurrent learning tools where the adaptive update
laws are driven by current state information and recorded state information
to yield approximate optimal control solutions without the need for ad hoc
probing. Applications are presented for autonomous systems including robot
manipulators, underwater vehicles, and fin controlled cruise missiles.
Solutions are also developed for networks of systems where the problem is
cast as a differential game where a Nash equilibrium is sought.

Description of speaker: Warren Dixon is a Professor at the University of
Florida in the Mechanical and Aerospace Engineering Department and has published 3 books,
an edited collection, 9 chapters, and over 250 refereed journal and
conference papers and has received numerous awards for his work.

Sponsor(s): Electrical Engineering and Computer Science, Institute of Electrical and Electronic Engineers
Contact: Quanquan Liu, quanquan@mit.edu


Professional Portfolio Selection Techniques: From Markowitz to Innovative Engineering

Antonella Sabatini

Jan/06 Mon 12:00PM-02:00PM 32-124

Enrollment: Unlimited: No advance sign-up
Prereq: none

A brief review of the most important and widely used state-of-the-art Portfolio Selection Techniques will be presented. Such techniques could be used by capital firm wealth management institutions as well as for a personal financial portfolio.  An introduction to some innovative methodologies, including the proprietary novel model as a tactical asset allocation technique, will be illustrated and some working examples will be presented as time allows.  Gentle introduction to the subject, specifically targeted at undergraduates in Economics, EECS and other fields with interest in quantitative finance, economics and management; emphasis on innovation and research.

Sponsor(s): Electrical Engineering and Computer Science, Institute of Electrical and Electronic Engineers
Contact: Antonella Sabatini, as@alum.mit.edu