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Game players of different skills expect different challenge levels in game to be filled with enjoyment and fulfillment. Thus intelligent game opponent can be made adaptive to match different player strategies and different player skills. Traditional difficulty adjustment setting the status of the opponent often fills players with a feeling of being cheated, which cannot perfectly satisfy the player...
Recent advancements in the neuroscience and engineering of brain-machine interfaces are providing a blueprint for how new co-adaptive designs based on reinforcement learning change the nature of a user's ability to accomplish tasks that were not possible using static methodologies. By designing adaptive controls and artificial intelligence into the neural interface, computers can become active assistants...
A primary delay is the deviation from a scheduled process time caused by disruption within the process. Delay is controlled by timetable and shows the characters of random occurrence. Rail transit system is a complex system which is dynamic, nonlinear, self-adaptive, random-occurrence and schedule-controllability. The multi-agent method enlarges the range of computer applying in rail system. This...
Adaptive techniques tend to converge to a single optimum. For adaptive game AI, such convergence is often undesirable, as repetitive game AI is considered to be uninteresting for players. In this paper, we propose a method for automatically learning diverse but effective macros that can be used as components of adaptive game AI scripts. Macros are learned by a cross-entropy method (CEM). This is a...
An adaptive game AI has the potential of tailoring a uniquely entertaining and meaningful game experience to a specific player. An online adaptive AI should be able to profile its opponent efficiently during the early phase of the game and adapts its own playing style to the level of the player so that the player feels entertained playing against it. This paper presents an online adaptive algorithm...
In this paper, we introduce a pricing model that ensures efficient resource allocation that provides guaranteed quality of service while maximizing profit in multiservice networks. Specifically, a dynamic allocation policy is examined that relies on online measurements while each service class operates under a probabilistic bound delay constraint. We present a rigorous analysis of the properties of...
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