5 papers · 1 filter
Probabilistic Recurrent Intention Switching Model
Wenyuan Sheng, Hao Zhu, Joschka Boedecker
Inverse reinforcement learning (IRL) recovers reward functions from observed behavior, yet traditional methods assume a single stationary reward that cannot capture goal switching…
Spectral Alignment in Forward-Backward Representations via Temporal Abstraction
Seyed Mahdi B. Azad, Jasper Hoffmann, Iman Nematollahi +3
Forward-backward (FB) representations provide a powerful framework for learning the successor representation (SR) in continuous spaces by enforcing a low-rank factorization. Howeve…
Inverse Reinforcement Learning via Convex Optimization
Hao Zhu, Yuan Zhang, Joschka Boedecker
We consider the inverse reinforcement learning (IRL) problem, where an unknown reward function of some Markov decision process is estimated based on observed expert demonstrations.…
Constrained Reinforcement Learning with Smoothed Log Barrier Function
Baohe Zhang, Yuan Zhang, Lilli Frison +2
Reinforcement Learning (RL) has been widely applied to many control tasks and substantially improved the performances compared to conventional control methods in many domains where…
Multi-intention Inverse Q-learning for Interpretable Behavior Representation
Hao Zhu, Brice De La Crompe, Gabriel Kalweit +4
In advancing the understanding of natural decision-making processes, inverse reinforcement learning (IRL) methods have proven instrumental in reconstructing animal's intentions und…