Plan recognition, activity recognition, and intent recognition together combine and unify
techniques from user modeling, machine vision, intelligent user interfaces, human/computer …

The more intelligent systems based on sub-symbolic techniques pervade our everyday lives,
the less human can understand them. This is why symbolic approaches are getting more …

Automation and computer intelligence to support complex human decisions becomes
essential to manage large and distributed systems in the Cloud and IoT era. Understanding …

Plan recognition is a form of abductive reasoning that involves inferring plans that best
explain sets of observed actions. Most existing approaches to plan recognition and other …

Goal recognition is the task of inferring users' goals from sequences of observed actions. By
enabling player-adaptive digital games to dynamically adjust their behavior in concert with …

Abstract In Probabilistic Abductive Logic Programming we are given a probabilistic logic
program, a set of abducible facts, and a set of constraints. Inference in probabilistic …

Evolving cybersecurity threats are a persistent challenge for systemadministrators and
security experts as new malwares are continu-ally released. Attackers may look for …

Attacks on computer systems are rapidly becoming more numerous and more sophisticated,
and current preventive techniques do not seem able to keep pace. Many successful attacks …

In this paper, we introduce Bayesian Abductive Logic Programs (BALPs), a new formalism
that integrates Bayesian Logic Programs (BLPs) and Abductive Logic Programming (ALP) …

Abstract Information systems play a crucial role in most of today's business operations. High
availability and reliability of services and hardware, and, in the case of outages, short …