Andrea Baisero

Publication Activity (10 Years)

Years Active: 2013-2023
Publications (10 Years): 16

Top Topics

Markov Decision Process

Partially Observable

Symbolic Descriptions

Top Venues

Publications

Xueguang Lyu, Andrea Baisero, Yuchen Xiao, Brett Daley, Christopher Amato
On Centralized Critics in Multi-Agent Reinforcement Learning. J. Artif. Intell. Res. 77 (2023)
Hai Huu Nguyen, Andrea Baisero, David Klee, Dian Wang, Robert Platt, Christopher Amato
Equivariant Reinforcement Learning under Partial Observability. CoRL (2023)
Hai Nguyen, Andrea Baisero, Dian Wang, Christopher Amato, Robert Platt
Leveraging Fully Observable Policies for Learning under Partial Observability. CoRL (2022)
Andrea Baisero, Christopher Amato
Unbiased Asymmetric Reinforcement Learning under Partial Observability. AAMAS (2022)
Andrea Baisero, Brett Daley, Christopher Amato
Asymmetric DQN for partially observable reinforcement learning. UAI (2022)
Hai Nguyen, Zhihan Yang, Andrea Baisero, Xiao Ma, Robert Platt, Christopher Amato
Hierarchical Reinforcement Learning under Mixed Observability. CoRR (2022)
Hai Nguyen, Zhihan Yang, Andrea Baisero, Xiao Ma, Robert Platt, Christopher Amato
Hierarchical Reinforcement Learning Under Mixed Observability. WAFR (2022)
Hai Nguyen, Andrea Baisero, Dian Wang, Christopher Amato, Robert Platt
Leveraging Fully Observable Policies for Learning under Partial Observability. CoRR (2022)
Xueguang Lyu, Andrea Baisero, Yuchen Xiao, Christopher Amato
A Deeper Understanding of State-Based Critics in Multi-Agent Reinforcement Learning. AAAI (2022)
Xueguang Lyu, Andrea Baisero, Yuchen Xiao, Christopher Amato
A Deeper Understanding of State-Based Critics in Multi-Agent Reinforcement Learning. CoRR (2022)
Andrea Baisero, Christopher Amato
Unbiased Asymmetric Actor-Critic for Partially Observable Reinforcement Learning. CoRR (2021)
Andrea Baisero, Christopher Amato
Reconciling Rewards with Predictive State Representations. IJCAI (2021)
Andrea Baisero, Christopher Amato
Reconciling Rewards with Predictive State Representations. CoRR (2021)
Andrea Baisero, Christopher Amato
Learning Complementary Representations of the Past using Auxiliary Tasks in Partially Observable Reinforcement Learning. AAMAS (2020)
Christopher Amato, Andrea Baisero
Active Goal Recognition. CoRR (2019)
Andrea Baisero, Stefan Otte, Peter Englert, Marc Toussaint
Identification of Unmodeled Objects from Symbolic Descriptions. CoRR (2017)
Andrea Baisero, Florian T. Pokorny, Carl Henrik Ek
On a Family of Decomposable Kernels on Sequences. CoRR (2015)
Yoan Mollard, Thibaut Munzer, Andrea Baisero, Marc Toussaint, Manuel Lopes
Robot programming from demonstration, feedback and transfer. IROS (2015)
Andrea Baisero, Yoan Mollard, Manuel Lopes, Marc Toussaint, Ingo Lütkebohle
Temporal segmentation of pair-wise interaction phases in sequential manipulation demonstrations. IROS (2015)
Andrea Baisero, Florian T. Pokorny, Danica Kragic, Carl Henrik Ek
The Path Kernel. ICPRAM (2013)
Andrea Baisero, Florian T. Pokorny, Danica Kragic, Carl Henrik Ek
The Path Kernel: A Novel Kernel for Sequential Data. ICPRAM (Selected Papers) (2013)