Distance-Based Construction Behaviors for Dynamic Grid-Based Worlds

This paper proposes a method for the development of AI for autonomous agents in game worlds modeled by fixed regular grids.  This approach uses context behaviors driven by distance maps to support multiple agents in a dynamic environment.  This paper introduces the notion of hierarchical distance maps which allow for higher-level goals to be easily specified by designers.  We also discuss potential applications of our approach in the design and development of agents and behaviors in the block world genre.