We present a first attempt at the compilation of the Game Description Language (GDL) using a bottom-up strategy. GDL is transformed into a normal form in which rules contain at most two predicates. The rules are then inverted to allow forward chaining and each predicate will turn into a function in the target language. Adding a fact to the knowledge base corresponds to triggering a function cal...

In the single-agent case general game playing and action planning are two related topics, so that one might hope to use the established planners to improve the handling of general single-player games. However, both come with their own description language, GDL and PDDL, respectively. In this paper we propose a way to translate single-player games described in GDL to PDDL planning tasks and prov...

The Game Description Language GDL is the standard input language for general game-playing systems. While players can gain a lot of traction by an efficient inference algorithm for GDL, state-of-the-art reasoners suffer from a variant of a classical KR problem, the inferential frame problem. We present a method by which general game players can transform any given game description into a represe...

We describe a multilevel algorithm compiling a general game description in GDL into an optimized reasoner in a low level language. The aim of the reasoner is to efficiently compute game states and perform simulations of the game. This is essential for many General Game Playing systems, especially if they use simulation-based approaches. Our compiler produces a faster reasoner than similar appro...

PROBLEM California's graduated driver licensing (GDL) program was implemented to reduce the high crash risk of teenage drivers. The program enhancements made in 1998 were evaluated in this study using methods that rule out the noticeable downward trend in California teen's fatal/injury crash rates as a possible explanation for any observed crash reductions that could otherwise be mistaken for p...

In general game playing [5], game rules are communicated at runtime, and the players must be able to read and understand the descriptions they are given in order to play legally and effectively. Unlike specialized game players, such as Deep Blue, general game players cannot rely on algorithms designed in advance for specific games. General game playing expertise depends on intelligence on the p...

Geometric deep learning (GDL) is based on neural network architectures that incorporate and process symmetry information. GDL bears promise for molecular modelling applications rely representations with different properties levels of abstraction. This Review provides a structured harmonized overview GDL, highlighting its in drug discovery, chemical synthesis prediction quantum chemistry. It con...

Liquid water transport and removal from the gas diffusion layer GDL and gas channel of a polymer electrolyte fuel cell PEFC are studied experimentally and theoretically. In situ observations of the liquid water distribution on the GDL surface and inside the gas channel were made in an operating transparent PEFC. Liquid droplet formation and emergence from the GDL surface are characterized and t...

The influence of the different properties gas diffusion layer (GDL) on operation a liquid-cooled, proton-exchange polymer electrolyte fuel cell (PEMFC) has been studied in this work. Three-dimensional numerical simulations (CFD) have conducted to compare several commercial GDLs with properties, analyzing their performance. Specifically, four (AvCarb P-75, SIGRACET 34BC, 34BA and Toray TGP-H-090...