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← Authors

Mirco Mutti

20 papers · 2018–2025 · 6 conferences · across top CS/AI conferences

Achievements

Jump to papers ↓
+11 more ↓ 🌍 Conference Polyglot (6) 🏃 Academic Marathon (7) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (8)
🧭 Keyword Pioneer 🐝 Cross-Pollinator (8) 🤝 Dynamic Duo (13) 👑 Triple Crown 🏆 Grand Slam 🏆 Keyword Champion (2) 💎 Century Club (20) ⚡ Prolific Year (6) ❓ The Questioner 🗃️ Keyword Collector (67) 🔥 Unstoppable (6)

Conferences

ICML (8) AAAI (4) NIPS (3) AISTATS (2) ICLR (2) JMLR (1)

Top co-authors

Marcello Restelli (13) Riccardo De Santi (6) Alberto Maria Metelli (4) Aviv Tamar (2) Filippo Lazzati (2) Riccardo Zamboni (2) Piersilvio De Bartolomeis (2) Aldo Pacchiano (1) Mattia Mancassola (1) Alberto Marchesi (1)

Keywords

reinforcement learning (5) markov decision process (4) policy gradient (3) policy optimization (2) model-based reinforcement learning (2) game theory (2) non-markovian policy (2) state distribution (2) finite trial (2) inverse reinforcement learning (2) exploration strategy (2) state entropy (2) convex reinforcement learning (2) sample efficiency (2) entropy maximization (1) reward function (1) intrinsic motivation (1) policy learning (1) offline reinforcement learning (1) exploration policy (1)

Papers

A Classification View on Meta Learning Bandits ICML 2025 A Theoretical Framework for Partially-Observed Reward States in RLHF ICLR 2025 Enhancing Diversity In Parallel Agents: A Maximum State Entropy Exploration Story ICML 2025 Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction ICML 2024 Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning ICLR 2024 How to Explore with Belief: State Entropy Maximization in POMDPs ICML 2024 How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach NIPS 2024 Test-Time Regret Minimization in Meta Reinforcement Learning ICML 2024 Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms ICML 2024 Convex Reinforcement Learning in Finite Trials JMLR 2023 Persuading Farsighted Receivers in MDPs: the Power of Honesty NIPS 2023 Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization AAAI 2023 A Tale of Sampling and Estimation in Discounted Reinforcement Learning AISTATS 2023 Unsupervised Reinforcement Learning in Multiple Environments AAAI 2022 Reward-Free Policy Space Compression for Reinforcement Learning AISTATS 2022 The Importance of Non-Markovianity in Maximum State Entropy Exploration ICML 2022 Challenging Common Assumptions in Convex Reinforcement Learning NIPS 2022 Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate AAAI 2021 An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies AAAI 2020 Configurable Markov Decision Processes ICML 2018