Behaviour oriented design for real-time-strategy games

Design is an essential part of all games and narratives, yet designing and implementing believable game strategies can be time consuming and error-prone. This motivates the development and application of systems AI methodologies. Here we demonstrate for the first time the iterative development of agent behaviour for a real-time strategy game (here StarCraft) utilising Behaviour Oriented Design (BOD). BOD provides focus on the robust creation and easy adjustment of modular and hierarchical cognitive agents. We demonstrate BOD’s usage in creating an AI capable of playing the StarCraft character the Zerg hive mind, and document its performance against a variety of opponent AI systems. In describing our tool-driven development process, we also describe the new Abode IDE, provide a brief literature review situating BOD in the AI game literature, and propose possible future work.

[1]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[2]  Joanna J. Bryson,et al.  Intelligence by design: principles of modularity and coordination for engineering complex adaptive agents , 2001 .

[3]  Rainer Knauf,et al.  In Search for the Human Factor in Rule Based Game AI: The GrinTu Evaluation and Refinement Approach , 2009, FLAIRS Conference.

[4]  Regina Barzilay,et al.  Non-Linear Monte-Carlo Search in Civilization II , 2011, IJCAI.

[5]  Kurt Konolige,et al.  The saphira architecture for autonomous mobile robots , 1998 .

[6]  Peter I. Cowling,et al.  Monte Carlo search applied to card selection in Magic: The Gathering , 2009, 2009 IEEE Symposium on Computational Intelligence and Games.

[7]  Joanna Bryson,et al.  The Behavior Oriented Design of an Unreal Tournament Character , 2005, IVA.

[8]  Simon M. Lucas,et al.  A Survey of Monte Carlo Tree Search Methods , 2012, IEEE Transactions on Computational Intelligence and AI in Games.

[9]  Arnav Jhala,et al.  Applying Goal-Driven Autonomy to StarCraft , 2010, AIIDE.

[10]  Aleksandar Micic,et al.  Developing game AI for the real‐time strategy game StarCraft , 2011 .

[11]  Steve Jacobs Raising the Stakes: E-Sports and the Professionalization of Computer Gaming , 2014 .

[12]  John E. Laird,et al.  Human-Level AI's Killer Application: Interactive Computer Games , 2000, AI Mag..

[13]  Rudolf Kadlec,et al.  Pogamut 3 Can Assist Developers in Building AI (Not Only) for Their Videogame Agents , 2009, AGS.

[14]  Joanna Bryson,et al.  How to Compare Usability of Techniques for the Specification of Virtual Agents' Behavior? An Experimental Pilot Study with Human Subjects , 2011, AEGS.

[15]  Dave Cliff,et al.  Creatures: artificial life autonomous software agents for home entertainment , 1997, AGENTS '97.

[16]  Ian Millington,et al.  Artificial Intelligence for Games , 2006, The Morgan Kaufmann series in interactive 3D technology.

[17]  Alex J. Champandard AI Game Development , 2003 .

[18]  David M. Bourg,et al.  AI for Game Developers , 2004 .

[19]  Joanna Bryson,et al.  The Behavior-Oriented Design of Modular Agent Intelligence , 2002, Agent Technologies, Infrastructures, Tools, and Applications for E-Services.

[20]  Joanna J. Bryson,et al.  POSH Tools for Game Agent Development by Students and Non-Programmers , 2006 .

[21]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[22]  Arnav Jhala,et al.  Reactive planning idioms for multi-scale game AI , 2010, Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games.

[23]  Joanna Bryson,et al.  Modularity and Design in Reactive Intelligence , 2001, IJCAI.

[24]  Joanna J. Bryson,et al.  Procedural quests: A focus for agent interaction in role-playing-games , 2011 .