1 citations · 1 across the 3 of their papers we have counts for
Showing cs.AIShow all
2 papers · 1 filter
cs.AI2025
Learning Representations in Video Game Agents with Supervised Contrastive Imitation Learning
Carlos Celemin, Joseph Brennan, Pierluigi Vito Amadori +1
This paper introduces a novel application of Supervised Contrastive Learning (SupCon) to Imitation Learning (IL), with a focus on learning more effective state representations for…
cs.AI2025★ 1 cited
Bayesian Optimization-based Search for Agent Control in Automated Game Testing
Carlos Celemin
This work introduces an automated testing approach that employs agents controlling game characters to detect potential bugs within a game level. Harnessing the power of Bayesian Op…