Particle swarm optimization for generating interpretable fuzzy reinforcement learning policies
نویسندگان
چکیده
منابع مشابه
Particle swarm optimization for generating interpretable fuzzy reinforcement learning policies
Fuzzy controllers are efficient and interpretable system controllers for continuous state and action spaces. To date, such controllers have been constructed manually or trained automatically either using expert-generated problem-specific cost functions or incorporating detailed knowledge about the optimal control strategy. Both requirements for automatic training processes are not found in most...
متن کاملFuzzy Particle Swarm Optimization Algorithm for a Supplier Clustering Problem
This paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. During recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decisions is usually complex and unstructured. In general, many quantitative and qualitative factors, such as quality, price, and fl...
متن کاملInterpretable Policies for Reinforcement Learning by Genetic Programming
The search for interpretable reinforcement learning policies is of high academic and industrial interest. Especially for industrial systems, domain experts are more likely to deploy autonomously learned controllers if they are understandable and convenient to evaluate. Basic algebraic equations are supposed to meet these requirements, as long as they are restricted to an adequate complexity. He...
متن کاملCooperative Fuzzy Particle Swarm Optimization
Particle swarm optimization is a population based optimization technique that is based on probability rules. In this technique each particle moves toward their best individual and group experience had occurred. Fundamental problems of standard PSO algorithm are the falling into the trap of local optimum and its low speed of convergence. One approach for solving the above problems is to combine ...
متن کاملfuzzy particle swarm optimization algorithm for a supplier clustering problem
this paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. during recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. however, the nature of these decisions is usually complex and unstructured. in general, many quantitative and qualitative factors, such as quality, price, and fl...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Engineering Applications of Artificial Intelligence
سال: 2017
ISSN: 0952-1976
DOI: 10.1016/j.engappai.2017.07.005