Inverse reinforcement learning via stochastic mirror descent

Inverse Reinforcement Learning (IRL) and Apprenticeship Learning (AL) are foundational problems in decision-making under uncertainty, where the goal is to infer cost functions and policies from observed behavior. In this thesis, we establish the equivalence between the inverse optimization framework...

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Autores:
Leiva Montoya, Esteban
Tipo de recurso:
Trabajo de grado de pregrado
Fecha de publicación:
2025
Institución:
Universidad de los Andes
Repositorio:
Séneca: repositorio Uniandes
Idioma:
eng
OAI Identifier:
oai:repositorio.uniandes.edu.co:1992/75575
Acceso en línea:
https://hdl.handle.net/1992/75575
Palabra clave:
Inverse optimization
Inverse reinforcement learning
Stochastic mirror descent
Markov decision processes
Matemáticas
Rights
openAccess
License
Attribution 4.0 International