Search Results for author:
Found 7 papers, 1 papers with code
AMaze: An intuitive benchmark generator for fast prototyping of generalizable agents
Agents were trained under three different regimes (one-shot, scaffolding, interactive), and the results showed that the latter two cases outperform direct training in terms of generalization capabilities.
Interactive embodied evolution for socially adept Artificial General Creatures
We introduce here the concept of Artificial General Creatures (AGC) which encompasses "robotic or virtual agents with a wide enough range of capabilities to ensure their continued survival".
Lamarckian Inheritance Improves Robot Evolution in Dynamic Environments
This study explores the integration of Lamarckian system into evolutionary robotics (ER), comparing it with the traditional Darwinian model across various environments.
A comparison of controller architectures and learning mechanisms for arbitrary robot morphologies
The main question this paper addresses is: What combination of a robot controller and a learning method should be used, if the morphology of the learning robot is not known in advance?
Lamarck's Revenge: Inheritance of Learned Traits Can Make Robot Evolution Better
We research this issue through simulations with an evolutionary robot framework where morphologies (bodies) and controllers (brains) of robots are evolvable and robots also can improve their controllers through learning during their lifetime.
Open-endedness induced through a predator-prey scenario using modular robots
This work investigates how a predator-prey scenario can induce the emergence of Open-Ended Evolution (OEE).
EvoMan: Game-playing Competition
For this particular competition, the main goal is to beat all of the eight bosses using a generalist strategy.
