7 citations · 12 across the 4 of their papers we have counts for
4 papers
Impacts of Single-objective Landscapes on Multi-objective Optimization
Shoichiro Tanaka, Keiki Takadama, Hiroyuki Sato
This work revealed a relationship between a multi-objective optimization problem and single-objective optimization problems that exist in the multi-objective problem. This work foc…
Adapting Rule Representation With Four-Parameter Beta Distribution for Learning Classifier Systems
Hiroki Shiraishi, Yohei Hayamizu, Tomonori Hashiyama +3
Rule representations significantly influence the search capabilities and decision boundaries within the search space of Learning Classifier Systems (LCSs), a family of rule-based m…
Directionality Reinforcement Learning to Operate Multi-Agent System without Communication
Fumito Uwano, Keiki Takadama
This paper establishes directionality reinforcement learning (DRL) technique to propose the complete decentralized multi-agent reinforcement learning method which can achieve coope…
Guiding Robot Exploration in Reinforcement Learning via Automated Planning
Yohei Hayamizu, Saeid Amiri, Kishan Chandan +2
Reinforcement learning (RL) enables an agent to learn from trial-and-error experiences toward achieving long-term goals; automated planning aims to compute plans for accomplishing…