We describe how, by modelling plot generation as a Continual Multiagent Planning process, dynamic stories can be generated in which characters not only inteleave perception, action and interaction, but in which also beliefs and motivations may change repeatedly, thus driving the plot forward.

Generating an article automatically with computer program is a challenging task in artificial intelligence and natural language processing. In this paper, we target at essay generation, which takes as input a topic word in mind and generates an organized article under the theme of the topic. We follow the idea of text planning (Reiter and Dale, 1997) and develop an essay generation framework. T...

The main objective of this thesis is to propose automatic planning tools for the planning problem of Long Term Evolution (LTE) networks based on realistic traffic. More precisely, a set of equations is first proposed to generate realistic traffic profile while considering as many practical aspects as possible. Then, a mathematical model is created to solve the planning problem of the evolved pa...

Natural language generation (NLG) is a major subfield of computational linguistics with a long tradition as an application area of automated planning systems. While things were relatively quiet with the planning approach to NLG for a while, several recent publications have sparked a renewed interest in this area. In this paper, we investigate the extent to which these new NLG approaches profit ...

Andrew Marks' recent editorial eloquently reiterated a concern that many of us have voiced before, that the current policies and practices of the NIH are not serving the public well.

Although the benefit of using business games is generally approved it is questionable if the present games serve the learning process as effectively as possible. The present state of computer environments and programming languages offers tools with which the games could be developed to serve as even more effective tools of teaching the rules of businesses. While the world around businesses is c...

In this paper, we translate sentence generation from TAG grammars with semantic and pragmatic information into a planning problem by encoding the contribution of each word declaratively and explicitly. This allows us to tap into the recent performance improvements in off-the-shelf planners. It also opens up new perspectives on referring expression generation and the relationship between languag...

We introduce a novel algorithm for temporal planning in Golog using shared resources, and describe the Bulk Freight Rail Scheduling Problem, a motivating example of such a temporal domain. We use the framework of column generation to tackle complex resource constrained temporal planning problems that are beyond the scope of current planning technology by combining: the global view of a linear p...

While Artiicial Intelligence techniques have been applied to a variety of software engineering applications, the area of automated software testing remains largely unexplored. Yet, test cases for certain types of systems (e.g., those with command language interfaces and transaction based systems) are similar to plans. We have exploited this similarity by constructing an automated test case gene...

We present PCRISP, a sentence generation system for probabilistic TAG grammars which performs sentence planning and surface realization in an integrated fashion, in the style of the SPUD system. PCRISP operates by converting the generation problem into a metric planning problem and solving it using an offthe-shelf planner. We evaluate PCRISP on the WSJ corpus and identify trade-offs between cov...