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The video games industry is one of the fastest growing branches of industry, reaching revenues comparable to (or even surpassing, depending on the source) the 70 year older film industry. The growth was not free from turmoil, as the industry faced many disruptive changes, market crashes, fusions and takeovers. High development costs and fierce competition make video games a high-risk business. While it seems obvious that companies in such unstable environment should strive to achieve the highest quality of their products, the uniqueness, variety, complexity, and constant evolution of video games makes common definitions and models of quality difficult to apply. This article provides an overview of problems concerning the application of the term "quality", it's frameworks and measurement methods to video games.
EN
This paper concerns the manner and results of Jumping-Jack video game implementation performed with the use of programmable logic device. The implementation corresponds to a non-memory approach involving only the logical resources of mentioned device. What is more, it is referred to the creation of the game from scratch. Selected aspects of the implementation are presented, as well as the information about the hardware and software used for the process. Furthermore, the usability of the achieved solution is considered and the possible ways of the solution development are listed. The organization of the paper is as follows: in chapter 1 the description and screen of the game are shown. In chapters 2 to 4 the graphics details of the implemented game are provided. In chapters 5 to 7 the implementation process, its results and the final conclusions are described.
EN
Searching for the shortest-path in an unknown or changeable environment is a common problem in robotics and video games, in which agents need to update maps and to perform re-planning in order to complete their missions. D* Lite is a popular incremental heuristic search algorithm (i.e., it utilizes knowledge from previous searches). Its efficiency lies in the fact that it re-expands only those parts of the search-space that are relevant to registered changes and the current state of the agent. In this paper, we propose a new D* Extra Lite algorithm that is close to a regular A*, with reinitialization of the affected search-space achieved by search-tree branch cutting. The provided worst-case complexity analysis strongly suggests that D* Extra Lite’s method of reinitialization is faster than the focused approach to reinitialization used in D* Lite. In comprehensive tests on a large number of typical two-dimensional path-planning problems, D* Extra Lite was 1.08 to 1.94 times faster than the optimized version of D* Lite. Moreover, while demonstrating that it can be particularly suitable for difficult, dynamic problems, as the problem-complexity increased, D* Extra Lite’s performance further surpassed that of D*Lite. The source code of the algorithm is available on the open-source basis.
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