3 papers
cs.LO2026
Quantitative Verification with Neural Networks
Alessandro Abate, Alec Edwards, Mirco Giacobbe +2
We present a data-driven approach to the quantitative verification of probabilistic programs and stochastic dynamical models. Our approach leverages neural networks to compute tigh…
cs.MA2025
Networked Communication for Decentralised Agents in Mean-Field Games
Patrick Benjamin, Alessandro Abate
Methods like multi-agent reinforcement learning struggle to scale with growing population size. Mean-field games (MFGs) are a game-theoretic approach that can circumvent this by fi…
cs.AI2025
Goal Kernel Planning: Linearly-Solvable Non-Markovian Policies for Logical Tasks with Goal-Conditioned Options
Thomas J. Ringstrom, Mohammadhosein Hasanbeig, Alessandro Abate
In the domain of hierarchical planning, compositionality, abstraction, and task transfer are crucial for designing algorithms that can efficiently solve a variety of problems with…