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Alessandro Abate

33 papers · 2020–2026 · 7 conferences · across top CS/AI conferences

Achievements

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+8 more ↓ 🌈 Renaissance Researcher (8) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (5) πŸ—ΊοΈ Taxonomy Completionist (49)
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Conferences

AAAI (13) L4DC (7) ICLR (3) NIPS (3) UAI (3) ICML (2) IJCAI (2)

Top co-authors

Joar Max Viktor Skalse (5) Daniel Kroening (3) Joar Skalse (3) Lewis Hammond (3) Thom Badings (3) Licio Romao (3) Tom Melham (2) David Parker (2) Sadegh Soudjani (2) Nils Jansen (2)

Keywords

reward function (4) markov decision process (4) policy synthesis (3) reinforcement learning (3) dynamical system (3) robust control (3) lexicographic optimization (2) epistemic uncertainty (2) interval markov decision process (2) sparse reward (2) safety verification (2) multi-objective reinforcement learning (2) robust optimization (2) risk bound (2) formal verification (2) safety constraint (2) inverse reinforcement learning (2) partial identifiability (2) game theory (2) control policy synthesis (2)

Papers

Best-Effort Policies for Robust Markov Decision Processes AAAI 2026 Symbolic Task Inference in Deep Reinforcement Learning (Abstract Reprint) AAAI 2026 Efficient Solution and Learning of Robust Factored MDPs AAAI 2026 Incremental Data-Driven Policy Synthesis via Game Abstractions AAAI 2026 The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret ICML 2025 Partial Identifiability in Inverse Reinforcement Learning for Agents with Non-Exponential Discounting AAAI 2025 DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL ICLR 2025 SPoRt - Safe Policy Ratio: Certified Training and Deployment of Task Policies in Model-Free RL IJCAI 2025 Temporal Logic Control for Nonlinear Stochastic Systems Under Unknown Disturbances L4DC 2025 Data-Driven Yet Formal Policy Synthesis for Stochastic Nonlinear Dynamical Systems L4DC 2025 Safeguarded Progress in Reinforcement Learning: Safe Bayesian Exploration for Control Policy Synthesis AAAI 2024 Walking the Values in Bayesian Inverse Reinforcement Learning UAI 2024 STARC: A General Framework For Quantifying Differences Between Reward Functions ICLR 2024 Quantifying the Sensitivity of Inverse Reinforcement Learning to Misspecification ICLR 2024 Learning-based rigid tube model predictive control L4DC 2024 Learning robust policies for uncertain parametric Markov decision processes L4DC 2024 Bounded robustness in reinforcement learning via lexicographic objectives L4DC 2024 Deep Bayesian Active Learning for Preference Modeling in Large Language Models NIPS 2024 Stability Analysis of Switched Linear Systems with Neural Lyapunov Functions AAAI 2024 Reasoning about Causality in Games (Abstract Reprint) AAAI 2024 Policy Evaluation in Distributional LQR L4DC 2023 On the limitations of Markovian rewards to express multi-objective, risk-sensitive, and modal tasks UAI 2023 Low Emission Building Control with Zero-Shot Reinforcement Learning AAAI 2023 Probabilities Are Not Enough: Formal Controller Synthesis for Stochastic Dynamical Models with Epistemic Uncertainty AAAI 2023 Misspecification in Inverse Reinforcement Learning AAAI 2023 Invariance in Policy Optimisation and Partial Identifiability in Reward Learning ICML 2023 Data-driven memory-dependent abstractions of dynamical systems L4DC 2023 Sampling-Based Robust Control of Autonomous Systems with Non-Gaussian Noise AAAI 2022 Lexicographic Multi-Objective Reinforcement Learning IJCAI 2022 Neural Abstractions NIPS 2022 DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning AAAI 2021 Certification of iterative predictions in Bayesian neural networks UAI 2021 A Randomized Algorithm to Reduce the Support of Discrete Measures NIPS 2020