Sciweavers

163 search results - page 19 / 33
» Policy Gradient Methods for Robotics
Sort
View
GECCO
2011
Springer
256views Optimization» more  GECCO 2011»
14 years 5 months ago
Evolving complete robots with CPPN-NEAT: the utility of recurrent connections
This paper extends prior work using Compositional Pattern Producing Networks (CPPNs) as a generative encoding for the purpose of simultaneously evolving robot morphology and contr...
Joshua E. Auerbach, Josh C. Bongard
115
Voted
PKDD
2009
Springer
181views Data Mining» more  PKDD 2009»
15 years 8 months ago
Active Learning for Reward Estimation in Inverse Reinforcement Learning
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
Manuel Lopes, Francisco S. Melo, Luis Montesano
ICML
1995
IEEE
16 years 3 months ago
Learning Policies for Partially Observable Environments: Scaling Up
Partially observable Markov decision processes (pomdp's) model decision problems in which an agent tries to maximize its reward in the face of limited and/or noisy sensor fee...
Michael L. Littman, Anthony R. Cassandra, Leslie P...
ICRA
2009
IEEE
106views Robotics» more  ICRA 2009»
15 years 9 months ago
Stochastic strategies for a swarm robotic assembly system
— We present a decentralized, scalable approach to assembling a group of heterogeneous parts into different products using a swarm of robots. While the assembly plans are predete...
Loic Matthey, Spring Berman, Vijay Kumar
104
Voted
ICRA
2007
IEEE
155views Robotics» more  ICRA 2007»
15 years 8 months ago
Dogged Learning for Robots
— Ubiquitous robots need the ability to adapt their behaviour to the changing situations and demands they will encounter during their lifetimes. In particular, non-technical user...
Daniel H. Grollman, Odest Chadwicke Jenkins