To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilist...
Hanna Pasula, Luke S. Zettlemoyer, Leslie Pack Kae...
We introduce Petruchio, a tool for computing Petri net translations of dynamic networks. To cater for unbounded architectures beyond the capabilities of existing implementations, t...
Deictic representation is a representational paradigm, based on selective attention and pointers, that allows an agent to learn and reason about rich complex environments. In this...
Balaraman Ravindran, Andrew G. Barto, Vimal Mathew
Abstract -- We experimentally examine the performance of preconditioners based on entries of the symmetric positive definite part and small subspace solvers for linear system of eq...
In the book on Advanced Topics in Types and Programming Languages, Crary illustrates the reasoning technique of logical relations in a case study about equivalence checking. He pr...