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- W2521096197 abstract "Action learning is an important aspect of self-improving. This paper explores a new approach for the learning of two types of actions, namely precondition-free actions and conditional actions. The corresponding two learning algorithms are designed and implemented using modern logic reasoners. Finally, a simple system of action learning agents is implemented to explore cooperative self-improving multi-agent systems." @default.
- W2521096197 created "2016-09-30" @default.
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- W2521096197 date "2016-07-01" @default.
- W2521096197 modified "2023-09-25" @default.
- W2521096197 title "Towards Dynamic Epistemic Learning of Actions for Self-Improving Agents and Multi-agent Systems" @default.
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- W2521096197 doi "https://doi.org/10.1109/icac.2016.40" @default.
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