AIM: Designing a language for AI models
Ionuţ Cristian Pistol, Andrei Arusoaie · Procedia Computer Science · 2019
Describing an unambiguous model for an Artificial Intelligence (AI) problem has been a significant topic in AI for almost 70 years, with the main goal of formalizing a natural language description to allow the computer to solve it. Nowadays, an AI problem is usually modelled as a transitional system, by following four steps: identify a representation for a problem state, describe the initial and final states in that representation, describe valid transitions together with a search strategy that looks for a path between an initial and a final state using the available transitions. This paper proposes a new language for describing AI models with the goal to generate executable code. The proposed language is capable of representing all common types of problems, and models implemented can be adapted easily to any search strategy with specific requirements (such as score functions). The language is fully described in this paper together with several non-trivial examples, while the code generation feature is work-in-progress.