no code implementations • 23 Feb 2024 • Zihan Zhou, Jonathan Booher, Khashayar Rohanimanesh, Wei Liu, Aleksandr Petiushko, Animesh Garg
Safe reinforcement learning tasks with multiple constraints are a challenging domain despite being very common in the real world.
no code implementations • 15 Feb 2023 • Khashayar Rohanimanesh, Jake Metzger, William Richards, Aviv Tamar
However, we find that an approximate solution based on sparse tree search yields near optimal performance at a fraction of the time.
no code implementations • 26 Aug 2020 • Coline Devin, Payam Rowghanian, Chris Vigorito, Will Richards, Khashayar Rohanimanesh
Robots have the capability to collect large amounts of data autonomously by interacting with objects in the world.
Robotics
no code implementations • ICLR 2018 • Aviv Tamar, Khashayar Rohanimanesh, Yin-Lam Chow, Chris Vigorito, Ben Goodrich, Michael Kahane, Derik Pridmore
In this paper we present an LfD approach for learning multiple modes of behavior from visual data.
no code implementations • NeurIPS 2009 • Khashayar Rohanimanesh, Sameer Singh, Andrew McCallum, Michael J. Black
Large, relational factor graphs with structure defined by first-order logic or other languages give rise to notoriously difficult inference problems.