Search papers, labs, and topics across Lattice.
Affiliation:
3
0
3
This paper proposes SUccessor-to-Novelty (SUN), an indicator derived from successor value functions to identify goals that are both novel and reachable and presents an adaptive goal-selection strategy that leverages these properties, and an accurate yet lightweight pseudocount to avoid the overhead of classic methods.
Ditch the Lipschitz constants: this new approach to safe learning-based control handles discontinuities and restrictive assumptions by directly sampling function realizations.
By enforcing physical laws, Lagrangian Neural Networks can significantly improve the accuracy and generalization of dynamics models within Model-Based Reinforcement Learning.
