Logical Markov Decision Programs
Kristian Kersting, Luc De Raedt · 2003
Motivated by the interest in relational reinforcement learning, we introduce a novel representation formalism, called logical Markov decision programs (LOMDPs), that integrates Markov Decision Processes with Logic Programs. Using LOMDPs one can compactly and declaratively represent complex relational Markov decision processes. Within this framework we then develop a theory of reinforcement learning in which abstraction (of states and actions) plays a major role.