Alessandro Sestini | DeepAI

DeepAI AI Chat

Featured Co-authors

Andrew D. Bagdanov
26 publications
Alexander Kuhnle
15 publications
Linus Gisslén
9 publications
Joakim Bergdahl
7 publications
Konrad Tollmar
7 publications
Enrico Civitelli
3 publications
Tommaso Aldinucci
3 publications
Leonardo Di Gangi
2 publications
Rodrigue de Schaetzen
2 publications
Jonas Gillberg
1 publication
Andrew Eakins
1 publication

∙ 08/15/2023

Generating Personas for Games with Multimodal Adversarial Imitation Learning

Reinforcement learning has been widely successful in producing agents ca...

0 William Ahlberg, et al. ∙

∙ 07/19/2023

Technical Challenges of Deploying Reinforcement Learning Agents for Game Testing in AAA Games

Going from research to production, especially for large and complex soft...

0 Jonas Gillberg, et al. ∙

∙ 07/07/2023

Efficient Ground Vehicle Path Following in Game AI

This short paper presents an efficient path following solution for groun...

0 Rodrigue de Schaetzen, et al. ∙

∙ 08/15/2022

Towards Informed Design and Validation Assistance in Computer Games Using Imitation Learning

In games, as in and many other domains, design validation and testing is...

14 Alessandro Sestini, et al. ∙

∙ 07/13/2022

Contextual Decision Trees

Focusing on Random Forests, we propose a multi-armed contextual bandit r...

14 Tommaso Aldinucci, et al. ∙

∙ 02/21/2022

CCPT: Automatic Gameplay Testing and Validation with Curiosity-Conditioned Proximal Trajectories

This paper proposes a novel deep reinforcement learning algorithm to per...

2 Alessandro Sestini, et al. ∙

∙ 04/21/2021

Policy Fusion for Adaptive and Customizable Reinforcement Learning Agents

In this article we study the problem of training intelligent agents usin...

0 Alessandro Sestini, et al. ∙

∙ 12/07/2020

Deep Policy Networks for NPC Behaviors that Adapt to Changing Design Parameters in Roguelike Games

Recent advances in Deep Reinforcement Learning (DRL) have largely focuse...

0 Alessandro Sestini, et al. ∙

∙ 12/04/2020

Demonstration-efficient Inverse Reinforcement Learning in Procedurally Generated Environments

Deep Reinforcement Learning achieves very good results in domains where ...

0 Alessandro Sestini, et al. ∙

∙ 12/03/2020

DeepCrawl: Deep Reinforcement Learning for Turn-based Strategy Games

In this paper we introduce DeepCrawl, a fully-playable Roguelike prototy...

0 Alessandro Sestini, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world