For modeling the interpretation process of NL sentences we use the mechanisms implying semantic networks that assure syntactic – semantic text interpretation (SSI), including an...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Abstract. In this paper, we consider the problem of filtering in relational hidden Markov models. We present a compact representation for such models and an associated logical par...
Luke S. Zettlemoyer, Hanna M. Pasula, Leslie Pack ...
Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
The study of transportability aims to identify conditions under which causal information learned from experiments can be reused in a different environment where only passive obser...