Games AI

This paper is a preliminary attemps to serve as a reference of the state of the art of the techniques and tools related to 'Game Design' (GD). We analyze the relationship existing between Game Design and the main subareas related to Artificial and Computational Intelligence in Games. Here, we focus particularly in Techniques and Tools that help in any way to designers involved in game development.

Multi-thread architectures are the current trends for both PCs (multi-core CPUs and GPUs) and game consoles such as the Microsoft Xbox 360 and Sony Playstation 3. GPUs (Graphics Processing Units) have evolved into extremely powerful and flexible processors, allowing its use for processing different data. This advantage can be used in game development to optimize the game loop. As reported in the literature, GPGPUs have been used in processing some steps of the game loop, while most of the game logic is still processed by the CPU. This proposal differs by presenting an architecture designed to process practically the entire game loop using the GPU. Two test cases, a crowd simulation and a 2D game shooter prototype called GpuWars, are presented to illustrate the proposed architecture.

A new domain-independent pruning method is described that guarantees returning a correct game value. Even though alpha-beta-based chess programs are already searching close to the minimal tree, there is still scope for improvement. Our idea hinges on the recognition that the game tree has two types of node, those where cuto s occur and those that must be fully explored. In the latter case one of the moves is best and yields the subtree value, thus for the remaining alternatives one is simply proving their inferiority. This o ers an opportunity for pruning, while introducing some potential for uncertainty in the search process. There are two cases of interest. One considers the immediate alternaitves to the Principal Variation itself, and here a safe uncertainty cut-o is presented, the second is a proposal for an unsafe generalization, one which o ers substatnial search reduction but with the potential for control of the error probability. Experiments with the new pruning method show some potential for savings in the search.

In this paper we take a general look at forward pruning in tree search. By identifying what we think are desirable characteristics of pruning heuristics, and what attributes are important for them to consider, we hope to understand better the shortcomings of existing techniques, and to provide some additional insight into how they can be improved. We view this work as a first step towards the goal of improving existing forward-pruning methods.

This is a thesis that deals with the norms and rules of players playing online games together. It is also a thesis about believability, the current capabilities of non-player characters (NPCs) and the attitudes amongst game developers towards dynamic and systemic games AI.

This chapter provides a brief historical overview of how variabledepth-search methods have evolved in the last half a century of computer chess work. We focus mainly on techniques that have not only withstood the test of time but also embody ideas that are still relevant in contemporary game-playing programs. Pseudo code is provided for a special formulation of the PVS/ZWS alpha-beta search algorithm, as well for an implementation of the method of singular extensions. We provide some data from recent experiments with Abyss’99, an updated Chinese Chess program. We also pinpoint the current research in forward pruning, since this is where the greatest performance improvements are possible. The work closes with a short summary of the impact of computer chess work on Chinese Chess, Shogi and Go.

In this paper we take a general look at forward pruning in tree search. By identifying what we think are desirable characteristics of pruning heuristics, and what attributes are important for them to consider, we hope to understand better the shortcomings of existing techniques, and to provide some additional insight into how they can be improved. We view this work as a first step towards the goal of improving existing forward-pruning methods.

— Battle of Etam Earth is one of the games developed by Bibir Design Studio for PC platform, tablets and arcade machines. A modern rock paper scissors game that was packed in a duel robot, where there were two players will depend on experience, strategy and luck to be a winner. The AI technology required for this game to be played by one player only. The second players are replaced by game agent. Game agent is constructed by transferring the knowledge of the game master of this game to become the model of a Finite State Machine (FSM). Research about game agent has become the attention of researchers in the field of Artificial Intelligence (AI). Every action-reaction of game that probably would happen, transform into states that will be the behavior of the agent. In this research will show us about the strategy model of the Battle of Etam Earth, which to design the behavioral of the Agent that was used Finite State Machine. Where the game agent is developed into three levels: easy, normal, and hard to make player can improve the experience. Finally, test results through simulation battle, was concluded that FSM could be properly functioned as a pattern of behavior as an intelligence game agent.