45 citations · 145 across the 15 of their papers we have counts for
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cs.AI2018
Autonomous Extraction of a Hierarchical Structure of Tasks in Reinforcement Learning, A Sequential Associate Rule Mining Approach
Behzad Ghazanfari, Fatemeh Afghah, Matthew E. Taylor
Reinforcement learning (RL) techniques, while often powerful, can suffer from slow learning speeds, particularly in high dimensional spaces. Decomposition of tasks into a hierarchi…
cs.AI2018
Interactive Reinforcement Learning with Dynamic Reuse of Prior Knowledge from Human/Agent's Demonstration
Zhaodong Wang, Matthew E. Taylor
Reinforcement learning has enjoyed multiple successes in recent years. However, these successes typically require very large amounts of data before an agent achieves acceptable per…