Autonomous system (mathematics)

About: Autonomous system (mathematics) is a research topic. Over the lifetime, 1648 publications have been published within this topic receiving 38373 citations.

Can Turing machine be curious about its Turing test results? Three informal lectures on physics of intelligence.

Abstract: What is the nature of curiosity? Is there any scientific way to understand the origin of this mysterious force that drives the behavior of even the stupidest naturally intelligent systems and is completely absent in their smartest artificial analogs? Can we build AI systems that could be curious about something, systems that would have an intrinsic motivation to learn? Is such a motivation quantifiable? Is it implementable? I will discuss this problem from the standpoint of physics. The relationship between physics and intelligence is a consequence of the fact that correctly predicted information is nothing but an energy resource, and the process of thinking can be viewed as a process of accumulating and spending this resource through the acts of perception and, respectively, decision making. The natural motivation of any autonomous system to keep this accumulation/spending balance as high as possible allows one to treat the problem of describing the dynamics of thinking processes as a resource optimization problem. Here I will propose and discuss a simple theoretical model of such an autonomous system which I call the Autonomous Turing Machine (ATM). The potential attractiveness of ATM lies in the fact that it is the model of a self-propelled AI for which the only available energy resource is the information itself. For ATM, the problem of optimal thinking, learning, and decision-making becomes conceptually simple and mathematically well tractable. This circumstance makes the ATM an ideal playground for studying the dynamics of intelligent behavior and allows one to quantify many seemingly unquantifiable features of genuine intelligence.

Evolving the “Feeling” of Time Through Sensory-Motor Coordination: A Robot Based Model

Abstract: In this paper, we aim to design decision-making mechanisms for an autonomous robot equipped with simple sensors, which integrates over time its perceptual experience in order to initiate a simple signalling response. Contrary to other similar studies, in this work the decision-making is uniquely controlled by the time-dependent structures of the agent’s controller, which in turn are tightly linked to the mechanisms for sensory-motor coordination. The results of this work show that a single dynamic neural network, shaped by evolution, makes an autonomous agent capable of “feeling” time through the flow of sensations determined by its actions.

On assessing self-adaptive systems

Abstract: Self-managed communication systems are using self-adaptive algorithms to control the services they offer. It is assumed that autonomy of system operation helps to reduce operational expenses, to increase performance or even to allow the emergence of new functionalities. The comparison and the understanding of operation (jointly termed here “assessment”) of different self-managed systems require their complete description. In addition to traditional performance metrics (which these new systems still need to satisfy) this comparison must include new characteristics based on their adaptive nature. Due to the huge amount and the variety of operational conditions assumed for these systems the focus should be on the abilities of systems to solve problems rather than on their exhaustive testing. We describe this ability to solve a problem as a new metric, We will also present the process to determine the metric based on a series of performance measurements. We demonstrate that the metric helps appraise the ability of a system to cope with new and never experienced situations and to build confidence in autonomous system operation.

An Autonomous Flight Control Strategy Study of a Small-Sized Unmanned Aerial Vehicle

Abstract: The purpose of this paper is to present a case study of the development, implementation and performance analysis of an autonomous flight control strategy for a 1-meter small-sized unmanned aerial vehicle. Firstly, a learning algorithm based open-loop control is proposed by simulating a skilled human operator's manipulation of the aircraft. This is aimed to generate a set of command data inputs and investigate the multichannel control characteristics with the open-loop control. Stcondly, a feedforward plus a proportional and derivative (PD) feedback control is employed to control the vehicle in following the command data to complete the loitering flight. The PD control gains are tuned automatically according to the attitude of the vehicle using the fuzzy logic theory. Thirdly, autonomous flight experiments conducted on a 1-meter small-sized aerial vehicle demonstrated the effectiveness of the proposed method.

An effective voltage control scheme for distribution systems by means of multi-agents

Abstract: This paper proposes a new voltage control scheme for distribution networks, where various new components, such as distributed resources, are being equipped, while conventional types of tap-changing controllers are still active. The authors employ a multi-agent system to build the new control scheme for the tap-changing controllers that is suitable for an autonomous system. The effectiveness of the proposed scheme is demonstrated through several numerical simulations with successful results.