SBIR-STTR Award

Military training systems require better computer-based modeling and simulation than is currently available. Key to such enhanced training is the use of computer-generated non-player characters (NPCs), or "avatars," exhibiting believable and culturally relevant behaviors in real-time training scenarios. Non-technical personnel must be able to generate such NPCs easily, either as individuals or groups, to fit training goals. Online Alchemy proposes to design and produce a working technology prototype for creating believable NPCs. This proposal focuses on creating NPCs with distinct personalities, goals, relationships, and in particular emergent nuanced emotions. Our technology is based on the "Five Factor" model of personality combined with a motivational and emotional model built on Maslovian and CogAff models and BDI architectural principles. This results in configurable NPCs that exhibit believable behaviors and emotions across a wide range of interactions. This proposal does not include natural language or advanced rendering technologies, but is compatible with work being done in these areas. During Phase I we will also specify methods for assessing the believability of the NPCs within a training context. The assessment itself will be part of Phase II, and will include Institutional Review Board (IRB) compliance for experimentation using human subjects

Online Alchemy proposes to extend prior SBIR research with this two-part SBIR Phase II project. Part one, to be funded via this technical proposal, includes three objectives: 1) further development of the patent-pending “Dynemotion™” people engine to incorporate temporal associations, emergent plans, refined motivations and emotions, group-related goals, and performance enhancements, 2) develop parametric crowd generation tools for heterogeneous NPCs possessing distinct personalities, goals, relationships, and exhibiting believable behaviors and nuanced emotions, and 3) integrate Dynemotion support for Micro Forté’s “Big World” architecture, necessary for commercial development and SCALE-UP participation. The result of part one of this Phase II project will be an enhanced Dynemotion engine, supporting the Big World architecture, for creating individuals and groups of NPCs. Part one above will provide the basis for part two of this project, to be funded separately, with objectives: 1) further Dynemotion enhancements including advanced tools for crowd specification, tracking and analysis (psychological telemetry), 2) support of National Training Center “geneogram” data, and 3) definition and integration of Dynemotion into the SCALE-UP AI test bed. The culmination of both parts will be a refined people engine and support tools, suitable for creating and evaluating individuals and/or crowds in commercial and MS&T applications.

Keywords:
SOFTWARE, SIMULATION, TRAINING, CROWD GENERATION, NON-PLAYER CHARACTERS, INTELLIGENT AGENTS