Archives for reward functions
Recently, a team of researchers from Google Brain, Vector Institute and the University of Toronto showed that the entropy, information gain, and empowerment of reinforcement learning agents correlate strongly with a human behaviour similarity metric. In the past few years, reinforcement learning has made several achievements in solving complex problems. From playing complex mind games…
The post Can RL Agents Behave More Human-Like Without Relying On Task Rewards? appeared first on Analytics India Magazine.
A reinforcement learning system consists of four main elements: An agent A policy A reward signal, and A value function An agent’s behaviour at any point of time is defined in terms of a policy. A policy is like a blueprint of the connections between perception and action in an environment. In the next section,…
The post On-Policy VS Off-Policy Reinforcement Learning appeared first on Analytics India Magazine.
With recent AI developments, there has been considerable research about its possible influence on human work. Research scientists have been trying to foretell the industries and jobs that will be affected. People also want to know what professions will be most in demand. Recently, there has been a new technology under development wherein developers are…
The post Understanding The Role Of Reward Functions In Reinforcement Learning appeared first on Analytics India Magazine.
Embracing the open-ended is considered by many futurists and experts, to be the last grand frontier for the artificial intelligence to invade. The concept of the open-ended can be explained in terms of natural evolution. Just like the way a species that has survived over millennia, makes course correction under new environments, machines too will…
The post Can Uber’s POET Address AI’s Open-Ended Endeavours? appeared first on Analytics India Magazine.