Sustainable Planning Across Space and Time
Monday, November 25, 2013 - 4:00pm - 4:50pm
KEC 1001
Mark Crowley
Postdoctoral Scholar
School of EECS
Oregon State University
Abstract:
There are many impediments to bringing about a more environmentally sustainable
society but one that is often overlooked are the significant and interesting
computational challenges that need to be solved in sustainability domains. The
field of Computational Sustainability attempts to connect research in the
computational sciences to hard sustainability problems such as invasive species
management, wildlife reserve design and sustainable forest management. I will
give an overview of some of these domains with a focus on spatial decision
making problems where actions must be chosen across a large physical landscape.
These problems can be modelled as using Markov decision processes but the
scale, complex dynamics and spatial correlations make these problems hard to
solve using traditional algorithms. I will describe research I have been
involved with obtaining approximate solutions to spatially factored MDPs using
policy gradients and sample based planning on invasive speci!
es, forest harvest and wildfire prevention problems. I'll also outline future
challenges in spatial planning which provide opportunities for AI and Machine
Learning research to make an impact on making sustainable world more
computationally feasible.
Speaker Biography:
Mark Crowley is a postdoctoral scholar at Oregon State University and received his PhD in Computer Science from the University of British Columbia in 2012. His primary research project explores optimization algorithms appropriate for problems with spatial structure, particularly in sustainability domains. His research interests span decision making under uncertainty, machine learning, causal modelling, visualization of spatial data, inference in probabilistic graphical models and game theory.
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