Satisfiability (SAT) solvers often benefit from a preprocessing of the formula to be decided. For formulae in conjunctive normal form (CNF), subsumed clauses may be removed or par...
In this paper, we present a method that helps improve the performance of Bounded Model Checking by automatically strengthening invariants so that the termination proof may be obta...
A typical goal for transfer learning algorithms is to utilize knowledge gained in a source task to learn a target task faster. Recently introduced transfer methods in reinforcemen...
This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...
This paper introduces the RL-TOPs architecture for robot learning, a hybrid system combining teleo-reactive planning and reinforcement learning techniques. The aim of this system ...