4 papers
Visualizing Movement Control Optimization Landscapes
Perttu Hämäläinen, Juuso Toikka, Amin Babadi +1
A large body of animation research focuses on optimization of movement control, either as action sequences or policy parameters. However, as closed-form expressions of the objectiv…
Self-Imitation Learning of Locomotion Movements through Termination Curriculum
Amin Babadi, Kourosh Naderi, Perttu Hämäläinen
Animation and machine learning research have shown great advancements in the past decade, leading to robust and powerful methods for learning complex physically-based animations. H…
PPO-CMA: Proximal Policy Optimization with Covariance Matrix Adaptation
Perttu Hämäläinen, Amin Babadi, Xiaoxiao Ma +1
Proximal Policy Optimization (PPO) is a highly popular model-free reinforcement learning (RL) approach. However, we observe that in a continuous action space, PPO can prematurely s…
Intelligent Middle-Level Game Control
Amin Babadi, Kourosh Naderi, Perttu Hämäläinen
We propose the concept of intelligent middle-level game control, which lies on a continuum of control abstraction levels between the following two dual opposites: 1) high-level con…