2 citations · 5 across the 5 of their papers we have counts for
5 papers
On Centralized Critics in Multi-Agent Reinforcement Learning
Xueguang Lyu, Andrea Baisero, Yuchen Xiao +2
Centralized Training for Decentralized Execution where agents are trained offline in a centralized fashion and execute online in a decentralized manner, has become a popular approa…
Equivariant Reinforcement Learning under Partial Observability
Hai Nguyen, Andrea Baisero, David Klee +3
Incorporating inductive biases is a promising approach for tackling challenging robot learning domains with sample-efficient solutions. This paper identifies partially observable d…
A Deeper Understanding of State-Based Critics in Multi-Agent Reinforcement Learning
Xueguang Lyu, Andrea Baisero, Yuchen Xiao +1
Centralized Training for Decentralized Execution, where training is done in a centralized offline fashion, has become a popular solution paradigm in Multi-Agent Reinforcement Learn…
Identification of Unmodeled Objects from Symbolic Descriptions
Andrea Baisero, Stefan Otte, Peter Englert +1
Successful human-robot cooperation hinges on each agent's ability to process and exchange information about the shared environment and the task at hand. Human communication is prim…
On a Family of Decomposable Kernels on Sequences
Andrea Baisero, Florian T. Pokorny, Carl Henrik Ek
In many applications data is naturally presented in terms of orderings of some basic elements or symbols. Reasoning about such data requires a notion of similarity capable of handl…