Academic literature on the topic 'Timed game automata'

We introduce a generalization of tropical polyhedra able to express both strict and non-strict inequalities. Such inequalities are handled by means of a semiring of germs (encoding infinitesimal perturbations). We develop a tropical analogue of Fourier–Motzkin elimination from which we derive geometrical properties of these polyhedra. In particular, we show that they coincide with the tropically convex union of (non-necessarily closed) cells that are convex both classically and tropically. We also prove that the redundant inequalities produced when performing successive elimination steps can be dynamically deleted by reduction to mean payoff game problems. As a complement, we provide a coarser (polynomial time) deletion procedure which is enough to arrive at a simply exponential bound for the total execution time. These algorithms are illustrated by an application to real-time systems (reachability analysis of timed automata).

With the development of computer animation games, now many animation games use the automatic generation of animation game levels method to generate animation game content. Using the automatic generation levels of the animation game method can quickly generate many different levels, saving labor costs in manual production. And with the combination of other fields, more accurate results can be obtained. In this paper, the goal is to automatically generate the level of the animation game. This research proposed animation game objects and victory conditions to derive the concept of the clearance path and uses artificial intelligence genetic algorithms to obtain the clearance path that best meets the needs of the developer to recombine new levels. In addition, since the generated levels are regenerated from the clearance path, there are still too many blank areas. In order to make full use of these blank areas, this research provides a level complete system. The system has formulated its placement rules for existing animation game objects. These rules fill in these blank areas and produce a more complete level. The contributions of this search proved that the genetic algorithm can converge quickly due to the correction effect in the mutation. In the complete system, it has successfully achieved a complete and playable level. In the system running time, this research adjusted the method of selecting elites and the use of permutations and combinations to mate, so that the system’s operation can be stabilized on an average value.

Purpose Extensive efforts have been conducted on the real-time strategy (RTS) games. The purpose of this paper is the specific artificial intelligence (AI) challenges posed by RTS games; non-player character (NPC) is started out by collecting game-map resources to build up defenses and attack forces, to upgrade combat deployment. Design/methodology/approach The authors used weak AI fuzzy theory as the foundation for tunable development. With the fuzzy theory, the AI was more humanistic in its judgment process. Findings Well-developed AIs have been used brilliantly in various aspects in RTS games, especially in those developed by large production teams. For small production teams, how to develop an AI system in less time and at a lower cost is extremely important. Research limitations/implication This study aimed to develop a system using player unit threat levels for NPC deployment and arrangement so that the further strategy would be adopted for NPCs in response to player actions. Originality/value The RTS games would become more challenging for players to play.