Publications
- S. Elfwing, E. Uchibe, K. Doya, and H. I. Christensen.
Evolutionary Development of Hierarchical Learning Structures.
IEEE Transactions on Evolutionary Computations, Vol. 11, Issue 2,
pages 249--264, 2007.
[IEEE
Xplore]
[download]
- T. Sato, E. Uchibe, and K. Doya. Learning how, what, and whether
to communicate: emergence of protocommunication in reinforcement
learning agents. Journal of Artificial Life and Robotics, vol. 12,
2007.
- E. Uchibe and M. Asada.
Incremental coevolution with competitive and cooperative tasks
in a multi-robot environment.
Proceedings of the IEEE, Vol. 94, Issue 7, pages 1412--1424, 2006.
[IEEE
Xplore]
- K. Doya and E. Uchibe. The Cyber Rodent Project: Exploration of
Adaptive Mechanisms for Self-Preservation and Self-Reproduction.
Adaptive Behavior, vol. 13, no. 2, pages 149--160, 2005.
[download]
- G. Capi and K. Doya. Evolution of neural architecture fitting
environmental dynamics. Adaptive Behavior, vol. 13, no. 1,
pages 53--66, 2005.
[download]
- T. Morimura, E. Uchibe, and K. Doya. Natural Actor-Critic with Baseline
Adjustment for Variance Reduction.
In Proc. of the 13th International Symposium on Artificial Life
and Robotics (AROB2007), 2008.
[download]
- E. Uchibe and K. Doya. Finding Exploratory Rewards by Embodied Evolution
and Constrained Reinforcement Learning in the Cyber Rodents.
In Proc. of the 14th International Conference on Neural Information
Processing, 2007 (oral presentation).
One of the Five Best Paper Awards.
[download (provisional proceeding
version)]
- E. Uchibe and K. Doya. Constrained reinforcement learning from intrinsic
and extrinsic rewards.
In Proc. of the IEEE International Conference on Development and
Learning, 2007 (oral presentation).
[download]
- T. Sato, E. Uchibe, and K. Doya. Learning how, what, and whether
to communicate: emergence of protocommunication in reinforcement
learning agents. In Proc. of the 12th International Symposium
on Artificial Life and Robotics (AROB2007), 2007.
- E. Brunskill, E. Uchibe, and K. Doya. Learning Adaptive Sensory
Observation-Action Policies for Mobile Robot Control.
In Proc. of the IEEE International Conference on Robotics and
Automation, Poster presentation, 2006.
[download]
- T. Morimura, E. Uchibe, and K. Doya. Utilizing the natural gradient
in temporal difference reinforcement learning with eligibility traces.
In Proc. of the 2nd International Symposium on Information Geometry
and its Application, pages 256--263, 2005.
[download]
- S. Elfwing, E. Uchibe, K. Doya, and H. I. Christensen. Biologically
Inspired Embodied Evolution of Survival.
In Proc. of the IEEE Congress on Evolutionary Computation,
2005.
[download]
- E. Uchibe and K. Doya. Reinforcement learning with multiple heterogeneous
modules: A framework for developmental robot learning.
In Proc. of the 4th International Conference on Development
and Learning, 2005.
[download]
- S. Elfwing, E. Uchibe, K. Doya, and H. I. Christensen. Multi-Agent
Reinforcement Learning: Using Macro Actions to Learn a Mating Task,
In Proc. of the IEEE/RSJ International Conference on Intelligent
Robots and Systems, 2004.
[download]
- E. Uchibe, and K. Doya.
Competitive-Cooperative-Concurrent Reinforcement Learning with
Importance Sampling,
In Proc. of International Conference on Simulation of Adaptive
Behavior: From Animals and Animats, pages 287--296, 2004.
Best Philosophical Paper Award (Sponsored by Applied AI
Systems).
[download]
- G. Capi, and K. Doya. Evolving recurrent neural controllers for sequential
tasks - a parallel implementation.
In Proc. of Congress on Evolutionary Computation, 1, 514-519,
2003.
- A. Eriksson, G. Capi, and K. Doya.
Evolution of Meta-parameters in Reinforcement Learning Algorithm.
In Proc. of IEEE/RSJ International Conference on Intelligent
Robots and Systems, 2003.
[download]
- S. Elfwing, E. Uchibe, and K. Doya.
An Evolutionary Approach to Automatic Construction of the Structure
in Hierarchical Reinforcement Learning.
In Proc. of the Genetic and Evolutionary Computaion
Conference, 2003.
[download]
- G. Capi, E. Uchibe, and K. Doya.
Selection of Neural Architecture and the Environment Complexity.
In Proc. of the 3rd International Symposium on Human and
Artificial Intelligent Systems. 2002.
[download]
- T. Morimura, E. Uchibe, J. Yoshimoto, and K. Doya. Policy Gradient
Reinforcement Learning with Log Stationary Distribution Gradients.
NAIST Technical Report, NAIST-IS-TR-2007013, 2007.
[download
from NAIST]
- Anders Eriksson.
Evolution of Meta-parameters in Reinforcement Learning. Master's
Thesis in Computer Science at the School of Computer Science and
Engineering, Royal Institute of Technology, 2003.
[download]
- Stefan Elfwing.
An Evolutionary Approach to Automatic Construction of the
Structure in Hierarchical Reinforcement Learning. Master's
Thesis in Computer Science at the School of Computer Science and
Engineering, Royal Institute of Technology, 2003.
[download]