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Готові списки джерел за темами / Timed game automata

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Добірка наукової літератури з теми "Timed game automata"

Автор: Grafiati

Опубліковано: 11 березня 2023

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Статті в журналах з теми "Timed game automata"

1

Cimatti, Alessandro, Luke Hunsberger, Andrea Micheli, Roberto Posenato, and Marco Roveri. "Dynamic controllability via Timed Game Automata." Acta Informatica 53, no. 6-8 (2016): 681–722. http://dx.doi.org/10.1007/s00236-016-0257-2.

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2

Bertrand, Nathalie, Amélie Stainer, Thierry Jéron, and Moez Krichen. "A game approach to determinize timed automata." Formal Methods in System Design 46, no. 1 (2014): 42–80. http://dx.doi.org/10.1007/s10703-014-0220-1.

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3

Bouyer, Patricia, Nicolas Markey, and Ocan Sankur. "Robust reachability in timed automata and games: A game-based approach." Theoretical Computer Science 563 (January 2015): 43–74. http://dx.doi.org/10.1016/j.tcs.2014.08.014.

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4

Jovanović, Aleksandra, and Marta Kwiatkowska. "Parameter synthesis for probabilistic timed automata using stochastic game abstractions." Theoretical Computer Science 735 (July 2018): 64–81. http://dx.doi.org/10.1016/j.tcs.2017.05.005.

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5

Guha, Shibashis, Shankara Narayanan Krishna, Chinmay Narayan, and S. Arun-Kumar. "A Unifying Approach to Decide Relations for Timed Automata and their Game Characterization." Electronic Proceedings in Theoretical Computer Science 120 (July 26, 2013): 47–62. http://dx.doi.org/10.4204/eptcs.120.5.

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6

Largouët, Christine, Omar Krichen, and Yulong Zhao. "Extended Automata for Temporal Planning of Interacting Agents." International Journal of Monitoring and Surveillance Technologies Research 5, no. 1 (2017): 30–48. http://dx.doi.org/10.4018/ijmstr.2017010102.

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Анотація:

In this paper, the authors consider the planning problem for a system represented as a set of interacting agents evolving along time according to explicit timing constraints. Given a goal, the planning problem is to find the sequence of actions such that the system reaches the goal state in a limited time and in an optimal manner, assuming actions have a cost. In their approach, the planning problem is based on model-checking and controller synthesis techniques while the goal is defined using temporal logic. Each agent of the system is represented using the formalism of Priced Timed Game Automata (PTGA). PTGA is an extension of Timed Automata that allows the representation of cost on actions and the definition of uncontrollable actions. The authors define a planning algorithm that computes the best strategy to achieve a goal. To experiment their approach, they extend the classical Transport Domain with timing constraints, cost on actions and uncontrollable actions. The planning algorithm is finally presented on a marine ecosystem management problem.

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7

Allamigeon, Xavier, Uli Fahrenberg, Stéphane Gaubert, Ricardo D. Katz, and Axel Legay. "Tropical Fourier–Motzkin elimination, with an application to real-time verification." International Journal of Algebra and Computation 24, no. 05 (2014): 569–607. http://dx.doi.org/10.1142/s0218196714500258.

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Анотація:

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).

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8

Larsen, Kim G. "Playing Games with Timed Automata." Electronic Proceedings in Theoretical Computer Science 166 (October 26, 2014): 2–3. http://dx.doi.org/10.4204/eptcs.166.2.

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9

Zhang, Rong. "Automatic Generation of Real-Time Animation Game Learning Levels Based on Artificial Intelligence Assistant." Scientific Programming 2022 (October 13, 2022): 1–19. http://dx.doi.org/10.1155/2022/1557302.

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Анотація:

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.

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10

Yang, Cheng-Ta, Her-Tyan Yeh, Bing-Chang Chen, and Guo-Xiang Jian. "Automatic tunable deployment for real-time strategy games." Engineering Computations 34, no. 2 (2017): 239–50. http://dx.doi.org/10.1108/ec-08-2015-0251.

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Анотація:

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.

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