Intrinsically Motivated Hierarchical Policy Learning in Multiobjective Markov Decision Processes
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DOI: 10.1109/tcds.2019.2948025
Abstract: The multiobjective Markov decision processes (MOMDPs) are sequential decision-making problems that involve multiple conflicting reward functions that cannot be optimized simultaneously without a compromise. This type of problem cannot be solved by a single optimal… read more here.
Keywords: markov decision; intrinsically motivated; multiobjective markov; policy ... See more keywords