Most AI systems in the games industry focus on short-term reactive memory and combat behaviors applying techniques such as behavior trees. However, there seems to be little support for long-term memory, for example remembering locations in space that mark events that occurred. In our daily lives, we internally map, model and remember our surroundings and experiences. This begs the question, how can we similarly organize and leverage longer-term memory within modern AI?

Wieso hockt meine Mutter jahrelang (!) in ein- und derselben Position vor ihrem Bett? Wieso kann ich mich buchstäblich vor der Nase von drei Wachen in den direkt daneben befindlichen Eingang schleichen? Warum spazieren nachts ebenso viele Menschen in den Städten herum wie am Tag?

Artificial intelligence methods open up new possibilities in game design, enabling the creation of believable characters with rich personalities and emotions, interactive story systems that incorporate player interaction into the construction of dynamic plots, and authoring systems that assist human designers in creating games. Games are fast becoming a major medium of the 21st century, being used for everything from education, to editorial news commentary, to expressing public policy and political opinions. Game AI research can radically expand the expressiveness of games, supporting them in becoming a mainstream medium for societal discourse. These ideas will be illustrated by looking at two projects: the interactive drama Façade (released July 2005, downloadable from www.interactivestory.net) and current work on automated game design support.

[...] is a software model developed for programming intelligent agents. Superficially characterized by the implementation of an agent’s beliefs, desires and intentions, it actually uses these concepts to solve a particular problem in agent programming. In essence, it provides a mechanism for separating the activity of selecting a plan (from a plan library) from the execution of currently active plans. Consequently, BDI agents are able to balance the time spent on deliberating about plans (choosing what to do) and executing those plans (doing it). A third activity, creating the plans in the first place (planning), is not within the scope of the model, and is left to the system designer and programmer.

Game designers currently have no formal, abstract tools or representations they can use to reason about designs in progress. This talk describes research in the Expressive Intelligence Studio at UC Santa Cruz that seeks to build systems that can reason about the consequences of and interactions between game design mechanics, as well as make heuristic game design suggestions. Michael and his team have identified four different design domains that interact during game design, the thematic, abstract mechanics, game state representation, and input mapping domains, and seek to provide semi-automated and automated support to assist with these domains. They have experimented with common-sense reasoning approaches for reasoning about game thematics, and event calculus representations of game mechanics and state representation. This talk provides an overview of the research agenda, present the demo systems they’ve created, and describes the two primary application directions they’re pursuing, namely, design support tools (‘CAD for game designers’) and computer creativity systems that discover new and interesting game mechanics.

ConceptNet aims to give computers access to common-sense knowledge, the kind of information that ordinary people know but usually leave unstated.
The data in ConceptNet is being collected from ordinary people who contributed it over the Web. ConceptNet represents this data in the form of a semantic network, and makes it available to be used in natural language processing and intelligent user interfaces.