Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
Unifying first-order logic and probability is a long-standing goal of AI, and in recent years many representations combining aspects of the two have been proposed. However, infere...
Most traditional approaches to probabilistic planning in relationally specified MDPs rely on grounding the problem w.r.t. specific domain instantiations, thereby incurring a com...
Intelligent systems need to store their experience so that it can be reused. A memory for such systems needs to efficiently organize and search previous experience and to retriev...
Firewalls have an important role in network security. However, managing firewall policies is an extremely complex task because the large number of interacting rules in single or d...