Our research on Interactive Drama aims at conciliating interaction and story at the deepest level, the level of action. From a given story representation formalism, a set of eleme...
We propose a general method for reranker construction which targets choosing the candidate with the least expected loss, rather than the most probable candidate. Different approac...
Explaining policies of Markov Decision Processes (MDPs) is complicated due to their probabilistic and sequential nature. We present a technique to explain policies for factored MD...
Abstract. We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian Decision Problems. As opposed to previous theoretical wo...
Abstract - This paper describes an efficient graphbased method to optimize data-flow expressions for best hardware implementation. The method is based on factorization, common su...
Daniel Gomez-Prado, Q. Ren, Maciej J. Ciesielski, ...