Research Output per year
Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
Gradient methods
Engineering & Materials Science
Reinforcement learning
Engineering & Materials Science
Mobile robots
Engineering & Materials Science
Motion planning
Engineering & Materials Science
magnons
Physics & Astronomy
Decomposition
Engineering & Materials Science
internal energy
Physics & Astronomy
thermodynamics
Physics & Astronomy
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 1982 2016
Policy gradient reinforcement learning with separated knowledge: Environmental dynamics and action-values in policies
Ishihara, S. & Igarashi, H., 2016, In : IEEJ Transactions on Electronics, Information and Systems. 136, 3, p. 282-289 8 p.Research output: Contribution to journal › Article
Reinforcement learning
Gradient methods
Policy gradient method using fuzzy controller in policies and its application
Noor Imanina, N. H. & Igarashi, H., 2014, International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2014, Held at the 3rd World Congress on Computing and Information Technology, WCIT. Society of Digital Information and Wireless Communications (SDIWC), p. 167-174 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Gradient methods
Reinforcement learning
Fuzzy rules
Fuzzy control
Learning algorithms
Agent Control in Multiagent Systems: Reinforcement Learning of Weight Parameters in Particle Swarm Optimization
Igarashi, H., H, M., a, A., Ishihara, S. & Sasano, I., 2012 Mar 31, In : The research reports of Shibaura Institute of Technology -- Natural Sciences and Engineering. 56, p. 1-8Research output: Contribution to journal › Article
Learning of Soccer Player Agents Using a Policy Gradient Method : Coordination between Kicker and Receiver during Free Kicks
Igarashi, H. & Ishihara, H. IKS., 2011 Apr 4, In : International Journal of Artificial Intelligence and Expert Systems. 2, p. 123-135Research output: Contribution to journal › Article
Policy gradient approach for learning of soccer player agents: Pass selection of midfielders
Igarashi, H., Fukuoka, H. & Ishihara, S., 2011, Lecture Notes in Electrical Engineering. Vol. 70 LNEE. p. 137-148 12 p. (Lecture Notes in Electrical Engineering; vol. 70 LNEE).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Gradient methods