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cs.AI2026
Towards Zero-Shot Task Transfer with Neurosymbolic World Models
Isidoro Tamassia, Lennert De Smet, Giuseppe Marra
State-of-the-art model-based reinforcement learning methods learn neural world models that allow policy improvement by planning in a latent space, without assumptions on the struct…
cs.AI2025
Improving Robustness of AlphaZero Algorithms to Test-Time Environment Changes
Isidoro Tamassia, Wendelin Böhmer
The AlphaZero framework provides a standard way of combining Monte Carlo planning with prior knowledge provided by a previously trained policy-value neural network. AlphaZero usual…