Reinforcement Learning with Linear Function Approximation.

‘Guest Posts and Printosynthesis Group’

Guest Post by
Jung hoon.

In this modern world, reinforcement learning (RL) has got massive importance and attention. RL with linear function is quite easy to determine with the use of a linear approximation calculator. The advancement in technology also led to the advancement in math concepts and also for other subjects.

What is Reinforcement Learning?

The scientists proposed the linear MDP assumptions that make it possible to attain logarithmic regret for RL. It indicates the gap that sub-optimally exists in the active-value function. Machine learning that includes the intelligence agents for maximizing the cumulative reward is known as reinforcement learning (RL).

Indeed, it is one of the most fabulous and exciting paradigms of machine learning which can either be supported with unsupervised learning and supervised learning. Multivariable linear approximation calculation makes it easier to deal with the coordinates quite smoothly. A linear approximation calculator is a highly accessible one that lets students and professionals in their mathematical calculations.

Let us exemplify it to make the idea much clearer to understand. For instance, let’s suppose there is a cat that is performing the function of an agent. Now, there is no supervisor on it, and the only thing that exists is the reward signal or real number. RL comes in two different types, which include positive and negative ones.

RL with Linear Function Approximation:

The RL problems of the single agent must be dealt with with optimal policies for the investigation of parallelization. The main agent that helps in this regard is the SARSA (λ) algorithm. It includes the value functions, which are reflected through the linear function approximates.

The linear function approximation is the part of calculus and math, which includes the determination of general function through linear expression. The linear approximation calculator is such a tool that helps in bringing ease in life by making calculations easier. It addresses the errors and risks which are associated with manual calculations.

Linear Approximation Formula:

Linear approximation calculator is also known as tangent line approximation calculator. The main formula that lies behind the calculation of linear approximation for a variety of functions is:


Here, the x–x0 points at the tangent line, while m is the indicative slope of the line. However, a and b are the points located on the line. Linearization calculation demands only a strong internet connection to provide the facilitated outcomes to the user.

In a Nutshell:

There exist a variety of researches for efficient knowledge about the logarithmic regret for RL. The accuracy of the linear approximation calculator is ideal and assists in making the function quite simple and smooth. The accurate linear approximation of the RL represents that the point x is equal to k. However, moving away from x = k will represent that the accuracy of linear function approximation is the least. Indeed, it is a method to define the curve direction with super ease. However, it is unable to predict or define the concavity of the curves.

Autonomous Transportation technology – pros and cons

Autonomous technology can operate without any human help. Robots can do work for humans such as Roomba Vacuum. (See, AUTONOMOUS TECHNOLOGY)

History of The Technology

Following is a timeline of autonomous vehicle technology.

1500 A.D.

(See, Self-Propelled Cart)

Leonardo da Vinci designed the world’s first autonomous cart. The robot cart moves without any human help.  Leonardo da Vinci designed a self-propelled cart capable of moving without being pushed.  Many consider da Vinci’s self-propelled cart invention to be the world’s first robot.  (See, Leonardo Da Vinci Automovile (1495))

 1800 A.D.

 Whitehead torpedo

The Whitehead torpedo in an autonomous aircraft that can travel several hundred yards underwater. (See, Whitehead torpedo)

1900 A.D.

The first aircraft was Mechanical Mike Sperry Corporation developed in 1933. It was incorporated by two gyroscopes and operated with the help of compressed air and hydraulic pressure. This was similar to three-axis autopilot.

(See, First Autopilots Installed on Airplanes )

   2000 A.D.

The Darpa had an Urban Challenge in 2007. This event was about autonomous vehicles. Basically, it was based on driving, merging, and parking at the intersection while using multi-sensors.  DARPA developed an autonomous control system which is called GA-ASI(General atomics aeronautical), UAS( Predator C Avenger unmanned aircraft system. Both systems were used during the air to air missions.  (See, DARPA Urban Challenge 2007 driverless car competition

2016 A.D.

In 2016 Starship Robot (See, Starship Robot) started delivery robots that are self driving and can deliver food or other items within 405 miles. (See, This invention changed flying forever | CNBC Reports).

Benefits of Self-driving technology

Because of these autonomous technology complex multi-sensors in the system the autonomous technology. The autonomous technology has complex multi-sensors in the system. Autonomous technologies hardware and software can handle different levels of neural workload that means it can connect the nodes.

The autonomous technology can be used with GPS.


Current State and growth of Technology

More than 5 different levels for autonomous technology for control.

Level 0, we can drive the car has no control.

Level 1, the autonomous vehicle has the ability to support the driver.

Level 2, Autonomous feature can control the accelerator and brakes.

Level3, Autonomous has advanced features that can operate according to human request.

Level 4, an autonomous vehicle can drive by itself.

Level 5, Autonomous feature can perform driving without any human interaction. 

Growth- The advancement in autonomous technology changing rapidly. This technology can give comfort and secure transportation. Autonomous technology is rising in the investment in the autonomous sector.

Difference between self-driving and autonomous

Autonomous vehicles in levels 4 and 5 are considered self-driving.  However, a self-driving vehicle in level 3 and under is not self-driving since it requires a human driver to take control when needed.  

Self-Driving Technology’s possible effects on end-users

Future benefits consist of safety and good health. Self-driving is likely to result in day-to-day lifestyle improvements for people of every age. We are likely to use less energy with a lesser impact on the environment. (See, Autonomous Vehicles).

Questions To Ponder From Assignment

a- What is more valuable autonomous technology or self-driving?

b-What is the difference between autonomous technology or self-driving?

c-What will be the benefit for the environment from autonomous technology?

d-Can autonomous technology will bring more employment?

e- What will be the use of autonomous technology?

f-What would happen when autonomous technology will take over human’s jobs?

 After browsing the history of autonomous technology now we can assume how technology is changed in more than 100 years. The first automation flight Changed flying forever.  According to history, we are aware of autonomous technology for a long long time.  Maybe we were not exactly familiar with the term but we were using it somehow. We bought Roomba in 2003.  Drones technology was effective in 2015. Now with the improved technology and the need for autonomous technology, is giving us more exposure to new things.  As we are learning about autonomous technology some of us love technology but others are scared. As time goes by, people will begin to use self-driving technology, just like how people got used to listening to radio or watching television.