Sciweavers

51 search results - page 4 / 11
» Transferring experience in reinforcement learning through ta...
Sort
View
AAAI
2010
14 years 10 months ago
Bayesian Policy Search for Multi-Agent Role Discovery
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
Aaron Wilson, Alan Fern, Prasad Tadepalli
ICCBR
2009
Springer
15 years 4 months ago
Case-Based Reasoning in Transfer Learning
Positive transfer learning (TL) occurs when, after gaining experience from learning how to solve a (source) task, the same learner can exploit this experience to improve performanc...
David W. Aha, Matthew Molineaux, Gita Sukthankar
89
Voted
IJCAI
2007
14 years 11 months ago
Transfer Learning in Real-Time Strategy Games Using Hybrid CBR/RL
The goal of transfer learning is to use the knowledge acquired in a set of source tasks to improve performance in a related but previously unseen target task. In this paper, we pr...
Manu Sharma, Michael P. Holmes, Juan Carlos Santam...
101
Voted
PPSN
2004
Springer
15 years 3 months ago
A Neuroevolutionary Approach to Emergent Task Decomposition
A scalable architecture to facilitate emergent (self-organized) task decomposition using neural networks and evolutionary algorithms is presented. Various control system architectu...
Jekanthan Thangavelautham, Gabriele M. T. D'Eleute...
ICML
1994
IEEE
15 years 1 months ago
A Modular Q-Learning Architecture for Manipulator Task Decomposition
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
Chen K. Tham, Richard W. Prager