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Found 3 papers, 1 papers with code
Learning Reusable Options for Multi-Task Reinforcement Learning
Reinforcement learning (RL) has become an increasingly active area of research in recent years.
A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning
In this paper we consider the problem of how a reinforcement learning agent that is tasked with solving a sequence of reinforcement learning problems (a sequence of Markov decision processes) can use knowledge acquired early in its lifetime to improve its ability to solve new problems.
A Compression-Inspired Framework for Macro Discovery
In this paper we consider the problem of how a reinforcement learning agent tasked with solving a set of related Markov decision processes can use knowledge acquired early in its lifetime to improve its ability to more rapidly solve novel, but related, tasks.
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