Monday
January 31
4:00 - 5:00 PM 
Kelley 1001

Saket Joshi 
Postdoctoral Researcher
School of EECS
Oregon State University


Advances in Decision Theoretic Planning

The field of Decision Theoretic Planning (DTP) has been highly successful in 
providing solutions for problems of planning under  uncertainty. This success 
is largely due to the ability of DTP algorithms to exploit structure and 
regularities in planning domains. Markov decision process (MDP) have provided 
the conceptual framework for these algorithms. However, the combinatorial 
nature of the state spaces often makes the use of classical dynamic programming 
solutions for MDPs, infeasible. This talk will summarize some of the landmark 
developments in DTP. Particular focus will be on algorithms that exploit 
relational structure in planning domains by leveraging First Order Decision 
Diagrams (FODD), a compact knowledge representation for capturing real valued 
functions over relational structures. The talk will also briefly touch upon 
some expressive extensions of FODDs and their application to DTP.


Biography

Saket Joshi completed his Masters degree in 2003 at the Computer Science 
department at OSU under Prof. Tom Dietterich. After spending a few months at 
Microsoft he joined the Computer Science department at Tufts University as a 
graduate student. He graduated from Tufts in 2010 with a PhD under the guidance 
of Prof. Roni Khardon. Since October 2010 he has been a post doc with Prof. 
Prasad Tadepalli at OSU. Saket's primary research interest and main focus has 
been on the development of agents that can successfully act in complex and 
uncertain environments.


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