Related papers: Diverse Behavior Is What Game AI Needs: Generating…
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AI-controlled characters in fighting games are expected to possess reasonably high skills and behave in a believable, human-like manner, exhibiting a diversity of play styles and strategies. Thus, the development of fighting game AI…
This paper has been withdrawn
This paper has been withdrawn by the author, since the relation mentioned in the paper between nonstandard analysis and games is probably useless.
This paper has been withdrawn by the author.
The paper was done as an assigned Princeton university project. It is being withdrawn since it needs to be changed and updated substantially.
In the last decade, deep learning has achieved great success in machine learning tasks where the input data is represented with different levels of abstractions. Driven by the recent research in reinforcement learning using deep neural…
This paper has been withdrawn by the author due to some errors
Recent times have witnessed sharp improvements in reinforcement learning tasks using deep reinforcement learning techniques like Deep Q Networks, Policy Gradients, Actor Critic methods which are based on deep learning based models and…
The paper has been withdrawn
This paper has been withdrawn by the author due to similarity to the author's other paper
This paper has been withdrawn by the authors.
Recently, there have been several high-profile achievements of agents learning to play games against humans and beat them. In this paper, we study the problem of training intelligent agents in service of game development. Unlike the agents…
This paper has been withdrawn by the author.
This paper has been withdrawn because of serious errors.
This paper has been withdrawn.
This paper has been withdrawn.
In order perform a large variety of tasks and to achieve human-level performance in complex real-world environments, Artificial Intelligence (AI) Agents must be able to learn from their past experiences and gain both knowledge and an…