Reinforcement Learning

• Reinforcement Learning is a type of Machine Learning, and thereby also a branch of Artificial Intelligence.

• It allows machines and software agents to automatically determine the ideal behaviour within a specific context, in order to maximize its performance. Simple reward feedback is required for the agent to learn its behaviour; this is known as the reinforcement signal.

• Reinforcement learning, in the context of artificial intelligence, is a type of dynamic programming that trains algorithms using a system of reward and punishment.

• A reinforcement learning algorithm, or agent, learns by interacting with its environment. The agent receives rewards by performing correctly and penalties for performing incorrectly.

• The agent learns without intervention from a human by maximizing its reward and minimizing its penalty.

• Reinforcement learning is an approach to machine learning that is inspired by behaviorist psychology. It is similar to how a child learns to perform a new task.

• As an agent, which could be a self-driving car or a program playing chess, interacts with its environment, receives a reward state depending on how it performs, such as driving to destination safely or winning a game. 

• Conversely, the agent receives a penalty for performing incorrectly, such as going off the road or being checkmated.

• The agent over time makes decisions to maximize its reward and minimize its penalty using dynamic programming. 

• The advantage of this approach to artificial intelligence is that it allows an AI program to learn without a programmer spelling out how an agent should perform the task.

        

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Self Driving Cars

• A self-driving car (also known as an autonomous car or a driverless car) is a vehicle that is capable of sensing its environment and navigating without human input.
• Autonomous cars combine a variety of techniques to perceive their surroundings, including radar, laser light, GPS, odometry, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage.
• The potential benefits of autonomous cars include reduced mobility and infrastructure, increased safety, increased mobility, increased customer satisfaction, and reduced crime. These benefits also include a potentially significant reduction in traffic collisions.

• Including less need for insurance. Automated cars are predicted to increase traffic flow,provide enhanced mobility for children, the elderly,disabled, and the poor; relieve travelers from driving and navigation chores; lower fuel consumption; significantly reduce needs for parking space,reduce crime

• Facilitate business models for transportation as a service, especially via the sharing economy.

Levels of driving automation:

• Level 1 ("hands on"): The driver and the automated system share control of the vehicle.
• Level 2 ("hands off"): The automated system takes full control of the vehicle (accelerating, braking, and steering). The driver must monitor the driving and be prepared to intervene immediately at any time if the automated system fails to respond properly.
• Level 3 ("eyes off"): The driver can safely turn their attention away from the driving tasks, e.g. the driver can text or read a book. The vehicle will handle situations that call for an immediate response, like emergency braking. The driver must still be prepared to intervene within some limited time, specified by the manufacturer, when called upon by the vehicle to do so. 
• Level 4 ("mind off"): As level 3, but no driver attention is ever required for safety, i.e. the driver may safely go to sleep or leave the driver's seat.
• Level 5 ("steering wheel optional"): No human intervention is required at all. An example would be a robotic taxi.

        This shows the vast disruptive potential of the emerging technology.

        with the power of Artificial Intelligence!

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Robotic Process Automation

• Robotic process automation (or RPA) is an emerging form of business process automation technology based on the notion of software robots or artificial intelligence(AI) workers.
• Robotic process automation (RPA) is the use of software with artificial intelligence (AI)and machine learning capabilities to handle high-volume, repeatable tasks that previously required humans to perform. These tasks can include queries, calculations and maintenance of records and transactions.
• RPA technology, sometimes called a software robot or bot,mimics a human worker, logging into applications, entering data, calculating and completing tasks, and logging out.

• As a form of automation, the same concept has been around for a long time in the form of screenscraping but RPA is considered to be a significant technological evolution of this technique in the sense that new software platforms are emerging which are sufficiently mature, resilient, scalable and reliable to make this approach viable for use in large enterprises.

• The hosting of RPA services also aligns with the metaphor of a software robot, with each robotic instance having its own virtual workstation, much like a human worker. The robot uses keyboard and mouse controls to take actions and execute automations.

• Normally all of these actions take place in a virtual environment and not on screen; the robot does not need a physical screen to operate, rather it interprets the screen display electronically.

• The scalability of modern solutions based on architectures such as these owes much to the advent of virtualization technology, without which the scalability of large deployments would be limited by available capacity to manage physical hardware and by the associated costs.

• Implementation of RPA in business enterprises has shown dramatic cost savings when compared to traditional non-RPA solutions.

     Benefits of RPA:

    Enabling better customer service

• Ensuring business operations and processes comply with regulations and standards.

• Allowing processes to be completed much more rapidly.

• Providing improved efficiency by digitizing and auditing process data.

      

       

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