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A unified strategy for implementing curiosity and empowerment driven reinforcement learning
[article]
2018
arXiv
pre-print
Although there are many approaches to implement intrinsically motivated artificial agents, the combined usage of multiple intrinsic drives remains still a relatively unexplored research area. Specifically, we hypothesize that a mechanism capable of quantifying and controlling the evolution of the information flow between the agent and the environment could be the fundamental component for implementing a higher degree of autonomy into artificial intelligent agents. This paper propose a unified
arXiv:1806.06505v1
fatcat:ky5xgsyyhjgjfnck7bvmexdd5y