Archive for October, 2008

23 Oct

Stochastic Plan Optimization in Real-Time Strategy Games

Posted by cognitivecomputing in Game AI. Tagged: , , , .

We present a domain independent off-line adaptation technique called Stochastic Plan Optimization for finding and improving plans in real-time strategy games. Our method is based on ideas from genetic algorithms, but we utilize a different representation for our plans and an alternate initialization procedure for our search process. The key to our technique is the use of expert plans to initialize our search in the most relevant parts of plan space. Our experiments validate this approach using our existing case based reasoning system Darmok in the real-time strategy game Wargus, a clone of Warcraft II.

Read the paper:

Stochastic Plan Optimization in Real-Time Strategy Games

by Andrew Trusty, Santi Ontañón, Ashwin Ram

4th Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE-08), Stanford, CA, October 2008
www.cc.gatech.edu/faculty/ashwin/papers/er-08-09.pdf

23 Oct

An Intelligent IDE for Behavior Authoring in Real-Time Strategy Games

Posted by cognitivecomputing in Game AI, Learning. Tagged: , , .

Behavior authoring for computer games involves writing behaviors in a programming language and then iteratively refining them by detecting issues with them. The main bottlenecks are a) the effort required to author the behaviors and b) the revision cycle as, for most games, it is practically impossible to write a behavior for the computer game AI in a single attempt. The main problem is that the current development environments (IDE) are typically mere text editors that can only help the author by pointing out syntactical errors.

In this paper we present an intelligent IDE (iIDE) that has the following capabilities: it allows the author to program initial versions of the behaviors through demonstration, presents visualizations of behavior execution for revision, lets the author define failure conditions on the existing behavior set, and select appropriate fixes for the failure conditions to correct the behaviors. We describe the underlying techniques that support these capabilities inside our implemented iIDE and the future steps that need to be carried out to improve the iIDE. We also provide details on a preliminary user study showing how the new features inside the iIDE can help authors in behavior authoring and debugging in a real-time strategy game.

Read the paper:

An Intelligent IDE for Behavior Authoring in Real-Time Strategy Games

by Manish Mehta, Suhas Virmani, Yatin Kanetkar, Santi Ontañón, Ashwin Ram

4th Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE-08), Stanford, CA, October 2008
www.cc.gatech.edu/faculty/ashwin/papers/er-08-08.pdf