Abstract--Model checkers for concurrent probabilistic systems have become very popular within the last decade. The study of long-run average behavior has however received only scan...
ate Abstractions of Discrete-Time Controlled Stochastic Hybrid Systems Alessandro D’Innocenzo, Alessandro Abate, and Maria D. Di Benedetto — This work proposes a procedure to c...
Alessandro D'Innocenzo, Alessandro Abate, Maria Do...
Abstract— We provide a method for planning under uncertainty for robotic manipulation by partitioning the configuration space into a set of regions that are closed under complia...
In this paper, we propose a model named Logical Markov Decision Processes with Negation for Relational Reinforcement Learning for applying Reinforcement Learning algorithms on the ...
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...