D. Hunter Hale

Influence points for tactical information in navigation meshes

Good artificial intelligence for strategy and first person shooter games requires tactical information. Tactical information assists agents in choosing appropriate places to place vulnerable resources, safe paths for moving through the world, and the most effective places to attack the enemy. Unfortunately, providing this information can be very expensive, as it typically requires keeping one or more full map arrays around. In this paper, we present influence points, a technique for providing tactical information by annotating navigation meshes. This greatly improves the memory cost of storing the information, and reduces the cost of updates as the world changes.

Embedding Information into Game Worlds to Improve Interactive Intelligence

Current game worlds are visually rich but information poor – particularly poor from the artificial intelligence (AI) point of view. Where the player sees a rich visual representation of 3D objects, internally these are just very sparsely described collections of points in space. Tools for advanced world creation, character modeling, animation, and advancements in computer graphics have brought us into the age of near photo-realistic interaction; however, these interactions are still very limited in comparison to the real world, and the information is presented overwhelmingly for the player, packaged for the Graphics Processing Unit (GPU) with little reflection or structure suitable for use by AI systems. This problem of a lack of rich information suitable for consumption by the game AI often limits the true potential for deeper levels of interaction that are becoming more in-demand by game players. This chapter presents a number of tools and techniques, which are being used to improve the embedded information contained in immersive game worlds. Symbolic annotation of the environmental elements, advanced spatial decomposition, calculating the information value of the surfaces in an interactive environment, and visual analysis form the core tools and information generators of our Common Games Understanding and Learning (CGUL) Toolkit. Using these tools to incorporate information into the game design and development process can help create information-rich interactive worlds. AI developers can work with these environmental information elements to improve non-player character (NPC) interactions both with the player and the environment, enhancing interaction, and leading to new possibilities such as meaningful in-game learning and character portability. Case studies from two different projects using these techniques provide some additional insight and reference as to how these techniques have been incorporated into current game AI and research.

Using navigation meshes for collision detection

Traditionally, tree-based spatial data structures such as k-d trees or hash-based structures such as spatial hashing are used to accelerate collision detection, and navigation meshes are used for agent path planning. In this paper, we present a series of algorithms to replace the traditional tree-based spatial data structures with the graph-based navigation-mesh. The advantages of using a single data structure for both agent navigation and collision detection acceleration are two-fold. First, the costs of constructing and maintaining two unique data structures are cut in half if a single data structure provides both spatial groupings for rapid collision detection and search space reduction for path planning. Second, using one spatial structure, development time can be shorter and, at runtime, there is generally less memory overhead. We present the results of an experiment that compares a navigation mesh as a collision detection accelerator to two popular and commonly used forms of spatial data structures, the k-d tree and the spatial hash map. We also compare its performance to a world without any spatial data structures to provide a baseline of performance. Our results show a fifty percent decrease in collision detection time between dynamic objects in comparison to k-d trees. In addition, until the number of objects present in the world exceeds three thousand the navigation mesh accelerated collision detection outperforms spatial hashing accelerated collision detection across all tests.