Updating BC's README with the new losses.
This folder contains an implementation for supervised learning of a policy from
a dataset of observations and target actions.
-This is an approach known as Behavioral Cloning, introduced by
-[Pomerleau, 1989].
-There is an example which generates data for bsuite environment `Deep Sea`
-using an optimal policy.
+This is an approach of Imitation Learning known as Behavioral Cloning,
+introduced by [Pomerleau, 1989].
+
+Several losses are implemented:
+
+ * Mean squared error (mse)
+ * Cross entropy (logp)
+ * Peer Behavioral Cloning (peerbc), a regularization scheme from [Wang et al., 2021]
+ * Reward-regularized Classification for Apprenticeship Learning (rcal), another
+regularization scheme from [Piot et al., 2014], defined for discrete action
+environments (or discretized action-spaces in case of continuous control).
+
[Pomerleau, 1989]: https://papers.nips.cc/paper/95-alvinn-an-autonomous-land-vehicle-in-a-neural-network.pdf
+[Wang et al., 2021]: https://arxiv.org/pdf/2010.01748.pdf
+[Piot et al., 2014]: https://www.cristal.univ-lille.fr/~pietquin/pdf/AAMAS_2014_BPMGOP.pdf
