Evolution of neural networks, as implemented in NEAT, has proven itself successful on a variety of low-level control problems such as pole balancing and vehicle control. Nonethele...
Dynamic programming provides a methodology to develop planners and controllers for nonlinear systems. However, general dynamic programming is computationally intractable. We have ...
Abstract. We present a model of a recurrent neural network with homeostasic units, embodied in a minimalist articulated agent with a single link and joint. The configuration of th...
The objective herein is to demonstrate the feasibility of a real-time digital control of an inverted pendulum for modeling and control, with emphasis on nonlinear auto regressive m...
This paper studies the design and application of the neural network based adaptive control scheme for autonomous underwater vehicle's (AUV's) depth control system that i...