Alessandro Sestini

36 papers B 1C 11Journal 24

Year	Rank	Type	Title / Venue / Authors
2025	C	`conf`	A Call for Deeper Collaboration Between Robotics and Game Development. CoG Iolanda Leite, William Ahlberg, André Pereira, Alessandro Sestini, Linus Gisslén, Konrad Tollmar
2025	J	`jnl`	Human-Like Goalkeeping in a Realistic Football Simulation: a Sample-Efficient Reinforcement Learning Approach. CoRR Alessandro Sestini, Joakim Bergdahl, Jean-Philippe Barrette-LaPierre, Florian Fuchs, Brady Chen, Michael Jones, Linus Gisslén
2025	C	`conf`	Real-Time Diffusion Policies for Games: Enhancing Consistency Policies with Q-Ensembles. CoG Ruoqi Zhang, Ziwei Luo, Jens Sjölund, Per Mattsson, Linus Gisslén, Alessandro Sestini
2025	J	`jnl`	Real-Time Diffusion Policies for Games: Enhancing Consistency Policies with Q-Ensembles. CoRR Ruoqi Zhang, Ziwei Luo, Jens Sjölund, Per Mattsson, Linus Gisslén, Alessandro Sestini
2025	J	`jnl`	SPEQ: Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning. CoRR Carlo Romeo, Girolamo Macaluso, Alessandro Sestini, Andrew D. Bagdanov
2025	J	`jnl`	Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games. CoRR António Afonso, Iolanda Leite, Alessandro Sestini, Florian Fuchs, Konrad Tollmar, Linus Gisslén
2025	J	`jnl`	TROFI: Trajectory-Ranked Offline Inverse Reinforcement Learning. CoRR Alessandro Sestini, Joakim Bergdahl, Konrad Tollmar, Andrew D. Bagdanov, Linus Gisslén
2025	J	`jnl`	Towards Better Sample Efficiency in Multi-Agent Reinforcement Learning via Exploration. CoRR Amir Baghi, Jens Sjölund, Joakim Bergdahl, Linus Gisslén, Alessandro Sestini
2024	C	`conf`	A Benchmark Environment for Offline Reinforcement Learning in Racing Games. CoG Girolamo Macaluso, Alessandro Sestini, Andrew D. Bagdanov
2024	J	`jnl`	A Benchmark Environment for Offline Reinforcement Learning in Racing Games. CoRR Girolamo Macaluso, Alessandro Sestini, Andrew D. Bagdanov
2024	J	`jnl`	Automated Gameplay Testing and Validation With Curiosity-Conditioned Proximal Trajectories. IEEE Trans. Games Alessandro Sestini, Linus Gisslén, Joakim Bergdahl, Konrad Tollmar, Andrew D. Bagdanov
2024	J	`jnl`	Improving Conditional Level Generation Using Automated Validation in Match-3 Games. IEEE Trans. Games Monica Villanueva Aylagas, Joakim Bergdahl, Jonas Gillberg, Alessandro Sestini, Theodor Tolstoy, Linus Gisslén
2024	J	`jnl`	Improving Conditional Level Generation using Automated Validation in Match-3 Games. CoRR Monica Villanueva Aylagas, Joakim Bergdahl, Jonas Gillberg, Alessandro Sestini, Theodor Tolstoy, Linus Gisslén
2024	B	`conf`	Improving Generalization in Game Agents with Data Augmentation in Imitation Learning. CEC Derek Yadgaroff, Alessandro Sestini, Konrad Tollmar, Ayça Özçelikkale, Linus Gisslén
2024	C	`conf`	Leveraging Large Language Models for Efficient Failure Analysis in Game Development. CoG Leonardo Marini, Linus Gisslén, Alessandro Sestini
2024	J	`jnl`	Leveraging Large Language Models for Efficient Failure Analysis in Game Development. CoRR Leonardo Marini, Linus Gisslén, Alessandro Sestini
2024	C	`conf`	Reinforcement Learning for High-Level Strategic Control in Tower Defense Games. CoG Joakim Bergdahl, Alessandro Sestini, Linus Gisslén
2024	J	`jnl`	Reinforcement Learning for High-Level Strategic Control in Tower Defense Games. CoRR Joakim Bergdahl, Alessandro Sestini, Linus Gisslén
2023	C	`conf`	Efficient Ground Vehicle Path Following in Game AI. CoG Rodrigue de Schaetzen, Alessandro Sestini
2023	J	`jnl`	Efficient Ground Vehicle Path Following in Game AI. CoRR Rodrigue de Schaetzen, Alessandro Sestini
2023	C	`conf`	Generating Personas for Games with Multimodal Adversarial Imitation Learning. CoG William Ahlberg, Alessandro Sestini, Konrad Tollmar, Linus Gisslén
2023	J	`jnl`	Generating Personas for Games with Multimodal Adversarial Imitation Learning. CoRR William Ahlberg, Alessandro Sestini, Konrad Tollmar, Linus Gisslén
2023	J	`jnl`	Improving Generalization in Game Agents with Data Augmentation in Imitation Learning. CoRR Derek Yadgaroff, Alessandro Sestini, Konrad Tollmar, Linus Gisslén
2023	J	`jnl`	Small Dataset, Big Gains: Enhancing Reinforcement Learning by Offline Pre-Training with Model Based Augmentation. CoRR Girolamo Macaluso, Alessandro Sestini, Andrew D. Bagdanov
2023	C	`conf`	Technical Challenges of Deploying Reinforcement Learning Agents for Game Testing in AAA Games. CoG Jonas Gillberg, Joakim Bergdahl, Alessandro Sestini, Andrew Eakins, Linus Gisslén
2023	J	`jnl`	Technical Challenges of Deploying Reinforcement Learning Agents for Game Testing in AAA Games. CoRR Jonas Gillberg, Joakim Bergdahl, Alessandro Sestini, Andrew Eakins, Linus Gisslén
2023	C	`conf`	Towards Informed Design and Validation Assistance in Computer Games Using Imitation Learning. CoG Alessandro Sestini, Joakim Bergdahl, Konrad Tollmar, Andrew D. Bagdanov, Linus Gisslén
2022	J	`jnl`	CCPT: Automatic Gameplay Testing and Validation with Curiosity-Conditioned Proximal Trajectories. CoRR Alessandro Sestini, Linus Gisslén, Joakim Bergdahl, Konrad Tollmar, Andrew D. Bagdanov
2022	J	`jnl`	Contextual Decision Trees. CoRR Tommaso Aldinucci, Enrico Civitelli, Leonardo Di Gangi, Alessandro Sestini
2022	J	`jnl`	Towards Informed Design and Validation Assistance in Computer Games Using Imitation Learning. CoRR Alessandro Sestini, Joakim Bergdahl, Konrad Tollmar, Andrew D. Bagdanov, Linus Gisslén
2021	C	`conf`	Demonstration-Efficient Inverse Reinforcement Learning in Procedurally Generated Environments. CoG Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
2021	C	`conf`	Policy Fusion for Adaptive and Customizable Reinforcement Learning Agents. CoG Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
2021	J	`jnl`	Policy Fusion for Adaptive and Customizable Reinforcement Learning Agents. CoRR Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
2020	J	`jnl`	Deep Policy Networks for NPC Behaviors that Adapt to Changing Design Parameters in Roguelike Games. CoRR Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
2020	J	`jnl`	DeepCrawl: Deep Reinforcement Learning for Turn-based Strategy Games. CoRR Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
2020	J	`jnl`	Demonstration-efficient Inverse Reinforcement Learning in Procedurally Generated Environments. CoRR Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov