The paper presents an efficient goal oriented algorithm for symbolic propagation in Bayesian networks. The proposed algorithm performs symbolic propagation using numerical methods. It first takes advantage of the independence relationships among the variables and produce a reduced graph which contains only the relevant nodes and parameters required to compute the desired propagation. Then, the ...

Nowadays, the use of software systems implemented for automatically guiding and monitoring business processes is becoming a common option in modern enterprises. This kind of systems (workflow management systems) is designed to monitor tasks, documents, rules, computers etc. To do this, these software systems implement an automated representation of the enterprise processes. In most cases, these...

Recently, a Euclidean heuristic (EH) has been proposed for A* search. EH exploits manifold learning methods to construct an embedding of the state space graph, and derives an admissible heuristic distance between two states from the Euclidean distance between their respective embedded points. EH has shown good performance and memory efficiency in comparison to other existing heuristics such as ...

In this article a predictive task-dependent gaze control strategy for goal-oriented humanoid walking is presented. In the context of active vision systems we introduce an information theoretical approach for maximization of visual information. Based on two novel concepts, Information Content of a view situation and Incertitude, we present a method for selecting optimal subsequent view direction...

Recent progress has seen an explosion in dialog systems, including voice-activated bots, text-based chatbots, and email-based bots for scheduling meetings. However real life interaction with these so-called intelligent agents consistently fall short of expectations. Consequently, this project deploys neural-based bots and rule-based bots across a wide variety of tasks in order to analyze where ...

Interactions between agents are traditionally specified as interaction protocols using notations such as Petri nets, AUML, or finite state machines. These protocols are a poor fit with autonomous proactive agents since protocols are message-centric and do not support goals. Additionally, interaction protocols prescribe how interactions are carried out by agents, thus limiting the flexibility of...

p0220 Many users are familiar with the interesting but limited functionality of data detector interfaces like Microsoft’s Smart Tags and Google’s AutoLink. In this chapter we significantly expand the breadth and functionality of this type of user interface through the use of large-scale knowledge bases of semantic information. The result is a Web browser that is able to generate personalized se...

W ith the heal thcare reform debate intensifying, public discourse on the issue has begun to focus more on the mechanics of various proposals and less on the broad goals and principles that inform different plans. But as Rev. Kevin D. O'Rourke, O P , JCD, reminded the audience at a March conference sponsored by the Saint Louis University School of Medicine, those goals and principles must remai...

i* is a widespread framework in the software engineering field that supports goal-oriented modeling of socio-technical systems and organizations. At its heart lies a language offering concepts such as actor, dependency, goal and decomposition. i* models resemble a network of interconnected, autonomous, collaborative and dependable strategic actors. Around this language, several analysis techniq...

A dialogue algorithm is described that executes Prolog-style rules in an attempt to achieve a goal. The algorithm selects paths in the proof in an attempt to achieve success and proves subgoals on the basis of internally available information where possible. Where \missing axioms" are discovered, the algorithm interacts with the user to solve subgoals, and it uses the received information from ...