Using genetic algorithm, maintain a balance between these two species in such a way that the overall population is stronger, and its chances of survival are better collectively. Marks will be awarded based on the completeness, clarity and correctness of your solution.

Q: Scheduling classes for the next semester. After students input their preferred course load, an…

A: In the context of the example provided, the school recognizes the practical limitations of…

Q: Please answer each of the following questions in detail and provide examples for better clarity…

A: k nearest neighbor algorithm for prediction with example  Bayer algorithm for estimating probability…

Q: This issue asks you to develop a Julia programme that does the following: When provided a policy,…

A: Given: The process of discovering various policy choices that might handle your issue, comparing…

Q: The next two questions refer to the following chart. The chart below has a single point for every…

A: From the given scatter plot, the points are accumulated at the beginning means that for the smaller…

Q: Consider the DFA M = (Q,Σ,δ,q1,F) where Q = {q1,q2,q3,q4},Σ = {a,b},F = {q4} and δ(q1,a) = q2,…

A: To convert a regular expression to a DFA (deterministic finite automaton), you can use algorithms…

Q: For a genetic algorithm the population size is 4.  The encoding is permutation, the selection method…

A: GA is a search based optimization technique based on principles of the genetic and natural…

Q: Which of the following would be considered a characteristic of the “Bootstrap” concept? a. Success…

A: We are going to understand bootstrapping situation and will find its characteristic among the…

Q: You want to cut a rectangular pan of brownies, made up of n square-shaped brownies, but you can only…

A: You want to cut a rectangular pan of brownies, made up of n square-shaped brownies, but you can only…

Intelligent Machines

Machines that use artificial intelligence to learn from the environment and past experiences to perform better in the presence of variability and uncertainty are called intelligent machines. Intelligence develops according to environment and experience. It is human-like behavior. When the computer system or any programmed machine learns from the inputs and corresponding outputs, it can be called an intelligent machine.