Multi-Level Evolution for Robotic Design
نویسندگان
چکیده
منابع مشابه
Simultaneous Multi-Level Evolution
A Genetic Algorithm (GA) is a form of complex system in which various structures interact via sufficiently complicated operators and rules that it is difficult to characterize the behavior of the system exactly. However, competition at this level is in the control of upper-level structure(such as genetic operators and corresponding parameter setting, etc.). Thus, how to optimize this structure ...
متن کاملMulti-level spatial modeling for stochastic distributed robotic systems
We propose a combined spatial and non-spatial probabilistic modeling methodology motivated by an inspection task performed by a group of miniature robots. Our models explicitly consider spatiality and yield accurate predictions on system performance. An agent’s spatial distribution over time is modeled by the Fokker–Planck diffusion model and complements current non-spatial microscopic and macr...
متن کاملEvolution of fuzzy behaviors for multi-robotic system
In a multi-robotic system, robots interact with each other in a dynamically changing environment. The robots need to be intelligent both at the individual and group levels. In this paper, the evolution of a fuzzy behavior-based architecture is discussed. The behavior-based architecture decomposes the complicated interactions of multiple robots into modular behaviors at different complexity leve...
متن کاملA decentralized multi-level leader-follower game for network design of a competitive supply chain
This paper develops a decentralized leader-follower game for network design of a competitive supply chain problem in which a new chain as the leader enters a market with one existing supply chain as a follower. Both chains produce an identical product, customer demand is inelastic and customer utility function is based on Huff gravity-based model. The leader wants to shape his network and set a...
متن کاملMulti Level Modeling for Engineering Design Optimization
Physical systems can be modeled at many levels of approximation The right model de pends on the problem to be solved In many cases a combination of models will be more e ective than a single model alone Our research investigates this idea in the context of en gineering design optimization We present a family of strategies that use multiple models for unconstrained optimization of engineering de...
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: Frontiers in Robotics and AI
سال: 2021
ISSN: 2296-9144
DOI: 10.3389/frobt.2021.684304