We present a general framework for Game Artificial Intelligence Planning (AIP) Analytics. The objective is to provide analytic tools to study and improve AIP components and their use in video-games. Extraction and formatting of AI data is first described and discussed. Then AIP metrics are listed with examples and illustrations from three popular First-Person Shooters: F.E.A.R. (2005), Zone 3 (...

Opponent behavior in today's computer games is often the result of a static set of Artificial Intelligence (AI) behaviors or a fixed AI script. While this ensures that the behavior is reasonably intelligent, it also results in very predictable behavior. This can have an impact on the replayability of entertainment-based games and the educational value of training-based games. This paper propose...

The purpose of this document is to develop an understanding of the components of a lesson learned process and how they fit together from the perspective of the Joint Center for Lessons Learned (JCLL). We also discuss the status of the JCLL, its lessons learned products, and provide a roadmap for what activities JCLL should support, including nearand long-term goals. Throughout we stress the pot...

Automated planning has become an increasingly influential area of research in the realm of artificial intelligence. Task based planning algorithms provide a number of advantages including the ease of human readability when creating mission length plans. However, task based planning algorithms are rarely implement on real world robotic systems because they require additional domain specific know...

Artificial intelligence (AI) techniques have been applied to video games to make the overall experience more enjoyable. In games with interactive storytelling (IS), player actions can substantially affect plot events and plot characters. Therefore, AI planning techniques have been used to shape the plot in response to player actions that conflict with authorial goals. While such methods are poi...

We propose an artificial intelligence problem called ‘User Intention Market for Multi-Agent Navigation’ which is a real problem in engineering context and also should be analyzed in economic context. The purpose of multi-agent navigation is to improve the performance of whole multiuser system without forcing them to make effort for the goal of the whole system. Although some negotiation and adj...

Igor is a knowledge-based system for exploratory statistical analysis of complex data. Igor has two related goals: to help automate the search for interesting patterns in data sets, and to help develop models that capture significant relationships in the data. Igor relies on a planning representation to manage the complexities of data analysis. We outline the relationship between planning and E...

Present-day technical infrastructures and appliances provide aplenty of opportunities for simplifying and supporting the everyday life. However, many of the systems available today such as typical feature loaded multimedia or infotainment systems are not always efficiently usable for the average person. This paper presents a planning-based approach to helping the user to control such complex in...

Project management is a business process for successfully delivering one-of-a kind products and services under real-world time and resource constraints. Developing a project plan, a crucial element of project management, is a difficult task that requires significant experience and expertise. Interestingly, artificial intelligence researchers have developed both mixed-initiative and automated hi...

This dedicated volume of the AIPS "96 proceedings is devoted to a progress report on the ARPA / Rome Laboratory Knowledge-based Planning and Scheduling Initiative (or ARPI for short). The ARPI has been co-sponsored by the Advanced Research Projects Agency (ARPA) and the United States Air Force Rome Laboratory (RL) since 1989. The ARPI’s main purpose is the development of the next generation of ...