Anthony Kobanda — accepted AI-conference papers

2026

Adaptive Quasimetric Mapping : Principled Topological Abstraction for Robust Offline Goal-Conditioned Navigation

Anthony Kobanda, Waris Radji, Odalric-Ambrym Maillard, Rémy Portelas

ICML 2026poster

Goal-Conditioned Reinforcement Learning aims to design agents that can reach specified goals, notably from previously collected trajectories in the offline setting. In this context, graph-based approaches have been proposed to mitigate compounding value-estimation errors in long-horizon navigation t…

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2025

Efficient Active Imitation Learning with Random Network Distillation

Emilien Biré, Anthony Kobanda, Ludovic Denoyer, Rémy Portelas

ICLR 2025poster

Developing agents for complex and underspecified tasks, where no clear objective exists, remains challenging but offers many opportunities. This is especially true in video games, where simulated players (bots) need to play realistically, and there is no clear reward to evaluate them. While imitatio…

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