23 citations · 29 across the 9 of their papers we have counts for
4 papers · 1 filter
MEMENTO: Memory-Guided Memetic Code-as-Policy Evolution
Alkis Sygkounas, Victor Aregbede, Amy Loutfi +1
Long-horizon embodied tasks require policies that execute many dependent actions before task success can be observed. Representing policies as executable control pro- grams (code-a…
Evolutionary Discovery of Reinforcement Learning Algorithms via Large Language Models
Alkis Sygkounas, Amy Loutfi, Andreas Persson
Reinforcement learning algorithms are defined by their learning update rules, which are typically hand-designed and fixed. We present an evolutionary framework for discovering rein…
COvolve: Adversarial Co-Evolution of Large-Language-Model-Generated Policies and Environments via Two-Player Zero-Sum Game
Alkis Sygkounas, Rishi Hazra, Andreas Persson +2
A central challenge in building continually improving agents is that training environments are typically static or manually constructed. This restricts continual learning and gener…
LAP: A Language-Aware Planning Model For Procedure Planning In Instructional Videos
Lei Shi, Victor Aregbede, Andreas Persson +3
Procedure planning requires a model to predict a sequence of actions that transform a start visual observation into a goal in instructional videos. While most existing methods rely…