While symbolic AI systems often accept an explicit goal function, the paradigm can also be applied to neural networks and to evolutionary computing. Reinforcement learning can generate intelligent agents that appear to act in ways intended to maximize a "reward function".[14] Sometimes, rather than setting the reward function to be directly equal to the desired benchmark evaluation function, machine learning programmers will use reward shaping to initially give the machine rewards for increme

What role does reinforcement learning play in AI? a. Optimizing search algorithms b. Designing user interfaces c. Providing emotional support to AI researchers d. Teaching machines through rewards and punishments

Which important class of machine learning algorithms X is defined as follows? X is concerned with how agents take actions in an environment and changing state so as to maximize some notion of cumulative reward. Explanation-based learning Inductive logic programming Deep learning Similarity-based learning Reinforcement learning

What is the goal of reinforcement learning?Question 10Answera.To maximize the cumulative reward over timeb.To predict the outcome of an eventc.To minimize the cumulative punishment over timed.To cluster data into groups

Briefly explain the concept of reinforcement learning and how it works, indicating how it differs from supervised learning.

Reward function :• Defines the goal in an RL problem• Policy is altered to achieve this goal• Value function:• Reward function indicates what is good in an immediate sense while a value functionspecifies what is good in the long run.• Value of a state is the total amount of reward an agent can expect to accumulateover the future, starting form that state.• Model of the environment :• Predict mimic behavior of environment.• Used for planning & if Know current state and action then predict the resultant nextstate and next reward