Inverse reinforcement learning from failure
<em>Inverse reinforcement learning</em> (IRL) allows autonomous agents to learn to solve complex tasks from successful demonstrations. However, in many settings, e.g., when a human learns the task by trial and error, <em>failed</em> demonstrations are also readily available....
Κύριοι συγγραφείς: | Shiarlis, K, Messias, J, Whiteson, S |
---|---|
Μορφή: | Conference item |
Έκδοση: |
International Foundation for Autonomous Agents and Multiagent Systems
2016
|
Παρόμοια τεκμήρια
Παρόμοια τεκμήρια
-
Rapidly exploring learning trees
ανά: Shiarlis, K, κ.ά.
Έκδοση: (2017) -
Learning from demonstration in the wild
ανά: Behbahani, F, κ.ά.
Έκδοση: (2019) -
Identifiability in inverse reinforcement learning
ανά: Cao, H, κ.ά.
Έκδοση: (2021) -
Bayesian Nonparametric Inverse Reinforcement Learning
ανά: How, Jonathan P., κ.ά.
Έκδοση: (2013) -
TACO: Learning task decomposition via temporal alignment for control
ανά: Shiarlis, K, κ.ά.
Έκδοση: (2018)