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cs.AI2026
Neurosymbolic Action Model Learning under Partial Observability
Adem Kikaj, Lennert De Smet, Giuseppe Marra +1
AI planning studies how an agent can reach a goal by executing a sequence of actions. To plan correctly, the agent needs an action model describing when each action can be executed…
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…