no code implementations • ICLR 2019 • Vikas Dhiman, Shurjo Banerjee, Jeffrey M. Siskind, Jason J. Corso
Multi-goal reinforcement learning (MGRL) addresses tasks where the desired goal state can change for every trial.
no code implementations • 25 Sep 2018 • Vikas Dhiman, Shurjo Banerjee, Jeffrey M. Siskind, Jason J. Corso
We do this by adapting the Floyd-Warshall algorithm for RL and call the adaptation Floyd-Warshall RL (FWRL).
1 code implementation • 7 Feb 2018 • Vikas Dhiman, Shurjo Banerjee, Brent Griffin, Jeffrey M. Siskind, Jason J. Corso
However, when trained and tested on different sets of maps, the algorithm fails to transfer the ability to gather and exploit map-information to unseen maps.
no code implementations • NeurIPS 2011 • David Wingate, Noah Goodman, Andreas Stuhlmueller, Jeffrey M. Siskind
Probabilistic programming languages allow modelers to specify a stochastic process using syntax that resembles modern programming languages.