RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
Many real-world problems are characterized by complex relational structure, which can be succinctly represented in firstorder logic. However, many relational inference algorithms ...
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
We define a partial order on colored compositions with many properties analogous to Young’s lattice. We show that saturated chains correspond to colored permutations, and that ...
Abstract. Many safety related and critical systems warn of potentially dangerous events; for example the Short Term Conflict Alert (STCA) system warns of airspace infractions betw...