Improving the Believability of Non-Player Characters in Simulations

Autor:	Jere Miles, Rahman Tashakkori
Rok vydání:	2009
Předmět:	Finite-state machine Java Rapid expansion business.industry Computer science Process (engineering) Rank (computer programming) Machine learning computer.software_genre Genetic algorithm Artificial intelligence business Video game computer computer.programming_language
Zdroj:	Proceedings of the 2nd Conference on Artificial General Intelligence (2009).
DOI:	10.2991/agi.2009.22
Popis:	In recent years the video game industry has experienced rapid expansion developing virtual environments that accurately mimic a real-world setting. However, the industry almost entirely relies on finite state machines for deploying computer-controlled characters within these environments. This has resulted in simulated inhabitants that lack the same degree of believability as their surroundings. As part of this research a simulation was developed using Java in which an agent was placed. In a survey students were asked to rank the believability of different artificial intelligence techniques employed by the simulation. The genetic algorithm developed for this simulation provided for an agent whose decisions were more believable than the decisions generated by a finite state machine or random selection process.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7d206fbcce95f117c3c94eb3659087c9 https://doi.org/10.2991/agi.2009.22 Zobrazit plný text záznamu