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EVOW
2003
Springer
14 years 26 days ago
Exploring the T-Maze: Evolving Learning-Like Robot Behaviors Using CTRNNs
Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...
Jesper Blynel, Dario Floreano
ROBOCUP
2009
Springer
134views Robotics» more  ROBOCUP 2009»
14 years 2 months ago
Learning Complementary Multiagent Behaviors: A Case Study
As the reach of multiagent reinforcement learning extends to more and more complex tasks, it is likely that the diverse challenges posed by some of these tasks can only be address...
Shivaram Kalyanakrishnan, Peter Stone
RAS
2002
131views more  RAS 2002»
13 years 7 months ago
Behavior generation for a mobile robot based on the adaptive fitness function
We have to prepare the evaluation (fitness) function to evaluate the performance of the robot when we apply the machine learning techniques to the robot application. In many cases,...
Eiji Uchibe, Masakazu Yanase, Minoru Asada
AIIDE
2008
13 years 10 months ago
Constructing Complex NPC Behavior via Multi-Objective Neuroevolution
It is difficult to discover effective behavior for NPCs automatically. For instance, evolutionary methods can learn sophisticated behaviors based on a single objective, but realis...
Jacob Schrum, Risto Miikkulainen
DAGSTUHL
2003
13 years 9 months ago
Evolution of Embodied Intelligence
Abstract. We provide an overview of the evolutionary approach to the emergence of artificial intelligence in embodied behavioral agents. This approach, also known as Evolutionary R...
Dario Floreano, Francesco Mondada, Andrés P...