EasyCog: Affordable and Easy to Develop Cognitive Models

Applications that incorporate human behavior models (HBMs) have the potential to improve the training, decision-making, and even the operational effectiveness of US forces. This software can mimic human decision-making, reasoning, learning, social and cultural biases, as well as perceptual, cognitive, and motor limitations in support of many applications, including analysis, simulation-based acquisition, training, and mission rehearsal. Unfortunately, the development of such complex software systems is currently costly, time consuming, and error-prone due to a lack of appropriate high-level languages and corresponding development tools. To improve the affordability, efficiency and robustness of the HBM-development process, we propose to design and demonstrate the feasibility of EasyCog, a high-level cognitive language, development environment, and compiler that is designed to improve the HBM-development process across multiple cognitive architectures. EasyCog combines cognitive, behavioral, social, affect and cultural models with high-level programming language features to improve the breadth and scalability of HBMs. Visual editors and debuggers work at the level of the high-level language to improve the efficiency of model development. Finally, EasyCog can generate configurable source code for a variety of existing cognitive architectures, meaning runtime users can reuse models in a variety of domains based on a single high-level model.