Search Results for author: Matthew J. Sargent

Found 2 papers, 0 papers with code

Temporally Extended Successor Representations

no code implementations25 Sep 2022 Matthew J. Sargent, Peter J. Bentley, Caswell Barry, William de Cothi

We show that in environments with dynamic reward structure, t-SR is able to leverage both the flexibility of the successor representation and the abstraction afforded by temporally extended actions.

A Simple Approach for State-Action Abstraction using a Learned MDP Homomorphism

no code implementations14 Sep 2022 Augustine N. Mavor-Parker, Matthew J. Sargent, Andrea Banino, Lewis D. Griffin, Caswell Barry

Consequently, impressive improvements in sample efficiency have been achieved when a suitable MDP homomorphism can be constructed a priori -- usually by exploiting a practioner's knowledge of environment symmetries.

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