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Computer Science
Q3) Assume that a rook can move on a chessboard any number of squares in a straight line, vertically or horizontally, but cannot jump over other pieces.
Give two possible admissible heuristics.
Which one is more informed than the other (dominates the other). Explain your answer.
Explain how we can combine the two heuristics in such a way the give a better heuristic that is still admissible.
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- Let's revisit our first problem, where we want to set up a series of chess matches so we can rank six players in our class. As we did before, we will assume that everyone keeps their chess rating a private secret; however, when two players have a chess match, the person with the higher rating wins 100% of the time. But this time, we are only interested in identifying the BEST of these six players and the WORST of these six players. (We don't care about the relative ordering or ranking of the middle four players.) Your goal is to devise a comparison-based algorithm that is guaranteed to identify the player with the highest rating and the player with the lowest rating. Because you are very strong at Algorithm Design, you know how to do this in the most efficient way. Here are five statements. A. There exists an algorithm to solve this problem using 6 matches, but there does not exist an algorithm using only 5 matches. B. There exists an algorithm to solve this problem using 7 matches,…What flaws does the following logic have, if any? Every horse has the same coloration. The proof is provided through induction based on the number of horses. The foundation of the induction is straightforward: If there is only one horse, the coloration is definitely that animal's own. Assume there are n horses, numbered 1 to n. The induction hypothesis states that all of the horses are the same color—let's say black. Horse 2 is quite dark. According to the induction hypothesis, horses 2 through n are all the same colour. Horses 2 through n and m must all be the same colour as horse 2. As a result, all of the horses are the same colour.Correct answer will be upvoted else downvoted. Monocarp's realm has n urban communities. To vanquish new grounds he intends to construct one Monument in every city. The game is turn-based and, since Monocarp is as yet beginner, he fabricates precisely one Monument for each turn. Monocarp has m focuses on the guide he'd prefer to control utilizing the developed Monuments. For each point he knows the distance among it and every city. Landmarks work in the accompanying manner: when implicit some city, a Monument controls all focuses at distance all things considered 1 to this city. Next turn, the Monument controls all focuses at distance all things considered 2, the turn after — at distance all things considered 3, etc. Monocarp will construct n Monuments in n turns and his domain will overcome all focuses that are constrained by somewhere around one Monument. Monocarp can't sort out any system, so during each turn he will pick a city for a Monument arbitrarily among every…
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- The Head Chef learns the level of motivation and satisfaction of his chefs. The chef's motivation and satisfaction can be represented as a whole. The Great Chef wants to know the smallest value of a single satisfaction value and the source value of the various N values. Satisfaction rates and incentives may apply to the same chef or different chefs. With the provision of two identical members, the same first members show the amount of motivation and the same second members reflect the level of satisfaction of the chefs. We can find a set of statistics (add one part to the first list and one to the second). For each question (defined by the whole number qi (i = 1 to Q), Q means the number of questions), find the qi th element in the mathematical set (in the unadulterated order) using Python language. Input: 1 31 123 456 4 Output: 7the knowledge-based agent is not an arbitrary program for calculating actions. It is amenable to a description at the knowledge level, where we need specify only what the agent knows and what it goains are, in order to fix its behavior. Give an Example:For problem 2, you should provide two answers for each of the search strategies: the states expanded and the solution. Problem 2 Alice the agent wants to go skiing right after AI class is over. She starts in the lecture hall (the "Start" state below) and wants to make it to Alta (the "Goal" state) as soon as possible. There are several possible paths she can take denoted in the graph below ( refer to image ): The available actions at each state are denoted by arrows with a path cost label above each arrow. For each of the following graph search strategies, figure out the order in which states are expanded as well as the path returned by graph search. When choosing an arbitrary order of state expansions (to break ties), use alphabetical ordering. Remember that in graph search, states are expanded only once. Depth-first search Breadth-first search Uniform cost search A* search
- 1. StrangeNEWS® just reported that suddenly a very VERY strange planet appeared out of nowhere! Three species, A, B and C are living on this planet. Any two different species can mate. If they do, two children will be born and they themselves will die. The planet will fail if there only one kind of specie left (therefore, no more mating can take place). We denote mating between two individuals from B and C species by a. Similarly, we define b and c. We want to draw an automaton for any given initial number of species on the planet that tells us whether a sequence of mating is possible and/or causes the planet to fail. For example, let's say there is only one individual of species A and one of species B. Then, the only way that a mating can happens is if these two individual mate with each other (mating of type c). We can draw a finite automaton for it as below: 110 As you can see, final state in this automoton is when the planet failes (not more mating possible or, in other words,…Article: The ethics of non-human agents: A growing number of digital agents are non-human and in some cases are increasingly capable of autonomy (robots, drones, self-driving cars, etc.). Algorithms are responsible for decisions in a wide range of areas these days (for example in stock marketing trading), and any algorithm that makes decisions is not ethically neutral. Some algorithms are adaptive, able to learn and adjust their behavior over time. We have to understand how such actors affect us and our societies. Autonomous systems, such as self-driving cars will react to changing conditions and deal with circumstances that they have never encountered before, without human intervention. Does it make sense to think of these technological systems as ethical agents in their own right? Is there a fundamental ethical priciple based on 'global' human values? What is the ethical status of machines that are increasingly autonomous and might even, at some point, be described as…Correct answer will be upvoted else Multiple Downvoted. Computer science. You are given an integer n (n>1). Your assignment is to find a succession of integers a1,a2,… ,ak with the end goal that: every simulated intelligence is completely more prominent than 1; a1⋅a2⋅… ⋅ak=n (I. e. the result of this grouping is n); ai+1 is separable by simulated intelligence for every I from 1 to k−1; k is the most extreme conceivable (I. e. the length of this grouping is the greatest conceivable). In case there are a few such groupings, any of them is adequate. It tends to be demonstrated that somewhere around one substantial grouping consistently exists for any integer n>1. You need to answer t autonomous experiments. Input The primary line of the input contains one integer t (1≤t≤5000) — the number of experiments. Then, at that point, t experiments follow. The main line of the experiment contains one integer n (2≤n≤1010). It is ensured that the amount of n…
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