Search Results for author: Suraj Narayanan Sasikumar

Found 2 papers, 1 papers with code

Exploration in Feature Space for Reinforcement Learning

no code implementations5 Oct 2017 Suraj Narayanan Sasikumar

Function approximation techniques enable RL agents to generalize in order to estimate the value of unvisited states, but at present few methods have achieved generalization about the agent's uncertainty regarding unvisited states.

Montezuma's Revenge reinforcement-learning

Count-Based Exploration in Feature Space for Reinforcement Learning

1 code implementation25 Jun 2017 Jarryd Martin, Suraj Narayanan Sasikumar, Tom Everitt, Marcus Hutter

We present a new method for computing a generalised state visit-count, which allows the agent to estimate the uncertainty associated with any state.

Atari Games Efficient Exploration +1

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