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Evolutionary games on networks traditionally involve the same game at each interaction. Here we depart from this assumption by considering mixed games, where the game played at each interaction is drawn uniformly at random from a set of two…
This paper has been withdrawn by the author due to a crucial error in the submission action.
This paper has been withdrawn
This paper has been withdrawn by the author.
This article has been withdrawn.
This paper has been withdrawn by the author due to serious flaws in certain proofs. For instance, the method used to construct certain automorphic representations is flawed.
This paper has been withdrawn
This paper has been withdrawn by the author.
This paper has been withdrawn
This paper has been withdrawn by the authors
This paper has been withdrawn by the author(s), due the final version in math.QA/0604564
This paper has been withdrawn by the authors due to an incorrect analysis.
In 2015, Google's DeepMind announced an advancement in creating an autonomous agent based on deep reinforcement learning (DRL) that could beat a professional player in a series of 49 Atari games. However, the current manifestation of DRL is…
This paper has been withdrawn by the authors. Significantly revised versions of the results of this paper are now available in arXiv:0707.0487v2 and arXiv:0808.3169v1.
This paper has been withdrawn by the author, due to errors in the figures.
This paper has been withdrawn. (Reason) Its contents have been entirely superseded by the contents of the articles arXiv:0809.3444 and arXiv:0705.3070. There is no profitable reason to keep it alive. No material on it is however wrong.
This paper is withdrawn because the results in the paper are included in a paper to be published in Mathematical and Computer Modelling.
This paper has been withdrawn.
This paper has been withdrawn by the author due to a crucial error in the definition of homomorphism.
Rapid progress in deep reinforcement learning has made it increasingly feasible to train controllers for high-dimensional humanoid bodies. However, methods that use pure reinforcement learning with simple reward functions tend to produce…