CUCKOO SEARCH ALGORITHM
Cuckoo is an optimization algorithm developed by Xin she Yang and Sushan Deb in 2009. This optimization algorithm is inspired by the life of a bird family, called Cuckoo. Special lifestyle of these birds and their characteristics in egg laying and breeding has been the basic motivation for development of this new evolutionary optimization algorithm.Lets discuss about this concept through this article. Cuckoo’s breeding behavior:

Cuckoo has the habit of laying their eggs in the nest of some host birds The mother removes one egg laid by the host mother, lays her own and flies off with the host egg in her bill. The whole process takes barely ten seconds.Some parasitic female cuckoo replicate the color and prototype of eggs of a few chosen host species.If the host bird ascertain the eggs are not their own they may either obliterate the cuckoo eggs or build a new nest. Some of these eggs which are more similar to the host bird’s eggs have the opportunity to grow up and become a mature cuckoo. The grown eggs reveal the suitability of the nests in thatarea. The more eggs survive in an area, the more profit is gained in that area.Cuckoos search for the most suitable area to lay eggs in order to maximize their eggs survival rate. After remained eggs grow and turn into a mature cuckoo, they make some societies. Each society has its habitat region to live in. The best habitat of all societies will be the destination for the cuckoos in other societies. Then they immigrate toward this best habitat. They will inhabit somewhere near the best habitat. Considering the number of eggs each cuckoo has and also the cuckoo’s distance to the goal point (best habitat), some egg laying radii is dedicated to it. Then, cuckoo starts to lay eggs in some random nests inside her egg laying radius. This process continues until the best position...

...Best-first search is a searchalgorithm which explores a graph by expanding the most promising node chosen according to a specified rule.
Judea Pearl described best-first search as estimating the promise of node n by a "heuristic evaluation function f(n) which, in general, may depend on the description of n, the description of the goal, the information gathered by the search up to that point, and most important, on any extra knowledge about the problem domain."[1] [2]
Some authors have used "best-first search" to refer specifically to a search with a heuristic that attempts to predict how close the end of a path is to a solution, so that paths which are judged to be closer to a solution are extended first. This specific type of search is called greedy best-first search.[2]
Efficient selection of the current best candidate for extension is typically implemented using a priority queue.
The A* searchalgorithm is an example of best-first search. Best-first algorithms are often used for path finding in combinatorial search.
ALGO:-
OPEN = [initial state]
while OPEN is not empty
do
1. Remove the best node from OPEN, call it n.
2. If n is the goal state, backtrace path to n (through recorded parents) and return path.
3. Create n's successors.
4. Evaluate each successor,...

...Action-Based Discretization for AI Search
Dr. Todd W. Neller*
Department of Computer Science Gettysburg College Campus Box 402 Gettysburg, PA 17325-1486 Introduction As computer gaming reaches ever-greater heights in realism, we can expect the complexity of simulated dynamics to reach further as well. To populate such gaming environments with agents that behave intelligently, there must be some means of reasoning about the consequences of agent actions. Such ability to seek out the ramifications of various possible action sequences, commonly called “lookahead”, is found in programs that play chess, but there are special challenges that face game programmers who wish to apply AI search techniques to complex continuous dynamical systems. In particular, the game programmer must “discretize” the problem, that is, approximate the continuous problem as a discrete problem suitable for an AI searchalgorithm. As a concrete example, consider the problem of navigating a simulated submarine through a set of static obstacles. This continuous problem has infinite possible states (e.g. submarine position and velocity) and infinite possible trajectories. The standard approach to discretize the problem is to define a graph of “waypoints” between which the submarine can easily travel. A simple waypoint graph can be searched, but this approach is not without significant disadvantages. First, the dynamics of such approximate...

...Cuckoo’s Nest + Restrepo
Conflict is a major issue confronting the world today as it comes in many forms such as individual, social and political. We are confronted by conflict in our day to day lives in many contexts and circumstances. Although conflict is often seen as a negative aspectconflict can be also be perceived as positive. we see this in “One Flew over the Cuckoo’s Nest” and the visual “Restrepo”
Many characters in “One Flew over the Cuckoo’s Nest” suffer inner-conflict, along with mental illness and anxiety, resulting in a lack of confidence and independence, we also see this conflict in Restrepo. Remember to link to the question – consider positive outcomes and growth – this has to be a brief statement that will allow you to connect your ideas to the question. Example: However, Mc Murphy’s arrival and the negative conflict he initiates enables the patients to grow, allowing them to enjoy freedom for the very first time. The idea of positive outcomes and opportunities as a result of conflict is challenged in the film Restrepo trailer, with the film exploring the negative impact of war.
Remember your first sentence should be your topic/ statement sentence – your argument which addresses the question - Inner-conflict is shown in the character Chief Bromden as he experiences an inner-conflict as to whether he should “come out of the fog”, befriend the other men on the ward and take a stand along with them against Nurse Ratched.
When the novel begins,...

...Algorithms Homework – Fall 2000
8.1-1 Using Figure 8.1 as a model, illustrate the operation of PARTITION on the array A =
13 19 9 5 12 8 7 4 11 2 6 21
i j j
6 19 9 5 12 8 7 4 11 2 13 21
i i j j
6 2 9 5 12 8 7 4 11 19 13 21
i ………………………… j
return 11, SPLIT = and
8.1-2 What value of q does PARTITION return when all elements in the array A[p…r] have the same value?
q = (p+r)/2, where p = index 0, and r = highest index
8.1-3 Give a brief argument that the running time of PARTITION on a subarray of size n is (n).
In the worst case, PARTITION must move the j pointer by one element (to the 2nd to last element), and the i pointer all the way to j, making a comparison at each element along the way. Since there are n comparisons made, the running time is (n)
In the average (and best) case, PARTITION must move the j pointer to an element at or near the half-way point in the array and the i pointer all the way to j, making a comparison at each element along the way. Once again there are n comparisons made and the running time is (n)
8.2-1 Show that the running time of QUICKSORT is (n lg n) when all elements of array A have the same value.
T(n) =...

...INFORMATION TECHNOLOGY ASSIGNMENT
ON ALGORITHM
Done by
Densil Hamilton
INTRODUCTION
This Assignment was done to show the methods of algorithm. It outlines the meaning of algorithm and steps to be carried out to complete a give problem. Examples were also shown for the methods of representing algorithm.
What is an Algorithm?
An algorithm consists of a set of explicit and unambiguous finite steps which, when carried out for a given set of initial conditions, produce the corresponding output and terminate in finite time. (How to Solve it by Computer, RG Dromey, Prentice Hall UK, 1982)
This is done by a series of steps:
1. Input: there are zero or more quantities which are externally supplied;
2. Output: at least one quantity is produced;
3. Definiteness: each instruction must be clear and unambiguous;
4. Finiteness: if we trace out the instructions of an algorithm, then for all cases the algorithm will terminate after a finite number of steps;
5. Effectiveness: every instruction must be sufficiently basic that a person using only pencil and paper can in principle carry it out. It is not enough that each operation is definite, but it must also be feasible.
WAYS OF REPRESENTING ALGORITHMS
Two ways of represent an algorithm are:
Flowcharts
Pseudo Code
FLOWCHARTS
This is a...

...
MGMT 801-HR IN THE GLOBAL FIRM
MARK CHAN CASE STUDY
1. Background information
Mark Chan had spent the past six years working overseas and Mark’s past international experience helped him to get the job at Energem, a diversified, global company with market-leading positions in a number of industries. Headquartered in the UK. By the end of his third year at Energem Mark was offered a three-year international assignment opportunity at the corporate headquarters in London. The job was another promotion and he would now be part of the company’s senior management. This was a great opportunity and with the expatriate benefits package and Mark’s wife Linda would not have to work and could stay at home with their two children who were still very young. She could always go back to work as a private banker when they returned to Singapore. This assignment would be a big stepping stone for Mark’s career when he returned.
Mark had very little trouble settling into his new position, his past experience as an expatriate had equipped him well. He and his family quickly adapted to life in the English country side and with his salary plus the benefits they were able to afford to a very comfortable lifestyle. They made many friends both inside the company as well as in the community.
The time has come for Mark and his family to decide if they want to return to Singapore or ask to stay in London. Mark has been trying to find a suitable position within Energem that would allow him to...

...In computer science, the analysis of algorithms is the determination of the amount of resources (such as time and storage) necessary to execute them. Most algorithms are designed to work with inputs of arbitrary length. Usually, the efficiency or running time of an algorithm is stated as a function relating the input length to the number of steps (time complexity) or storage locations (space complexity).
Algorithm analysis is an important part of a broader computational complexity theory, which provides theoretical estimates for the resources needed by any algorithm which solves a given computational problem. These estimates provide an insight into reasonable directions of search for efficient algorithms.
In theoretical analysis of algorithms it is common to estimate their complexity in the asymptotic sense, i.e., to estimate the complexity function for arbitrarily large input. Big O notation, Big-omega notation and Big-theta notation are used to this end. For instance, binary search is said to run in a number of steps proportional to the logarithm of the length of the list being searched, or in O(log(n)), colloquially "in logarithmic time". Usually asymptotic estimates are used because different implementations of the same algorithm may differ in efficiency. However the efficiencies of any two "reasonable" implementations of a...