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This paper presents the ideal approach to how to minimize the time taken by reinforcement learning to train the model. Similar to Computer vision the progress in reinforcement learning is not influenced by new ideas but mostly by the computation, large data, infrastructure and efficiency of algorithm. These 4 things only influenced the reinforcement learning RL model. How much time it will take to...
Despite the vast progress made in artificial intelligence (AI) over the years and the recent renewed interest in it because of some major breakthroughs in methodologies seemingly signifying its general viability, there are still important gaps that have to be filled to enable the construction of truly general and adaptive intelligent machines. This paper points out that a useful general learning machine...
Interactive training is a technique that allows humans to guide a learning algorithm. This technique is well suited to training first person shooter bots as it allows game designers to iterate a range of behaviors in real-time. This paper investigates an initial attempt at allowing users to interact with the learning process of a reinforcement learning algorithm to create first person shooter bot...
In this paper, we present an approach for detecting MTV video shot using Hidden Markov Models (HMMs), in which the color, shape and motion features are utilized. First, the temporal characteristics of different shot transitions are exploited and an HMM is constructed for shot transitions, including cut and gradual transitions. Secondly, a trained HMM are used to recognize the shot transition automatically,...
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