Modeling and simulation framework of real urban and board games to train players

Abstract

This tutorial will include: (1) a modeling approach for generating an urban terrain model from a Compact Terrain DataBase (CTDB) for computer-simulation of an urban search and rescue operation (US&RO), (2) a modeling approach for implementing the game RISK and generating autonomous players (3) a generalized implementation strategy for integrating both models into an autonomous dynamic planning and execution (ADP&E) framework for gaming simulations, and (4) an evolutionary strategy for using autonomous simulation results to improve player's abilities. The game RISK a multi-player non-cooperative stochastic game problem, and the US&RO simulation is a single-player multi-agent cooperative game problem. Accumulated results from both applications have given insight into a more general framework to ADP&E for Very Large Partially Observable and Uncertain Environments. The generalization of this approach will be described in terms of its hierarchy, modular components, and dynamic processes.