Abstract
The main goal of this paper is to develop software agent which is autonomous with reactive behavior and learning abilities. One of the applications of such agents are in gaming. Gaming characters are expected to work in unpredictable environment with decision making capabilities like weapon selection for different targets, wall following. This can be achieved artificial intelligence (AI) techniques and methods. In this paper, agent is designed to exhibit capabilities like - Moving Abilities, Steering behavior and obstacle avoidance, Synthesis of movement enhancing movement, weapon selection, adapting defense strategies, strategic Decision making.
Highlights
There is a significant change and development in the gaming industry over years
There is a need for game characters with cognitive behaviors like how they interact with the game terrain, other characters in a game, how they take decision in various situations of game for example in shooter game, whether to face the enemy or choose weapon and attack
Overall an effort is made to design non-player characters (NPC) in game to behave like a human and get adopted to different gaming terrain
Summary
There is a significant change and development in the gaming industry over years This has demanded for the character appearing in the gaming world is intelligent and close to human in the real world. In the games like first person shooter, player should learn from the environment and experience based on which gaming decisions should be taken. Though FPS is older generation game, but there exists few challenges in weapon choices, flexibility in the size of player base. This allows accessing control settings of environment through command-line. Quake 3, one can experiment on different maps in a game [16]
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