A Las Vegas algorithm is a randomized algorithm that always gives the correct result but gambles with resources.. Monte Carlo simulations are a broad class of algorithms that use repeated random sampling to obtain numerical results.. Monte Carlo simulations are typically used to simulate the behaviour of other systems.; Monte Carlo algorithms, on the other hand, are randomized algorithms whose. ** Las Vegas (LV) Algorithms - Are randomized algorithms which always give the correct answer**. The running time however is not fixed (not deterministic), that is it can vary for the same input. For eg. Randomized Quick Sort always gives a correctly s.. 3 Monte Carlo Algorithms Deﬁnition 1. A randomized algorithm is called a Monte Carlo algorithm if it may fail or return incorrect answers, but has runtime independent of the randomness. 1Some materials are from a note by Samuel Haney for this class in Fall 2014 and a note by Allen Xiao for COMPSCI 532 in Fall 2015. 11-

Also, this Wikipedia section points out the in my opinion key difference between Las Vegas type and Monte Carlo type algorithms: the first one does not necessarily return a correct result in a finite time whereas the latter one does. In turn, the first one returns a correct result whereas the latter one does return a probably correct result. Las Vegas Algorithms (LV) Always give the correct answer. But slow (Comparatively) and need resources. e.g: randomized quicksort, randomized selection. 2. Monte Carlo Algorithms (MC) Not always 100% correct. But fast. e.g: Karger's algorithm (Min cut) We will first discuss Randomized Quicksort, which comes under LV algorithms

What are randomized algorithms? What is the difference between Las Vegas and Monte Carlo approaches? What are the various complexity classes of randomized algorithms? 2.Design a Monte Carlo algorithm for searching an element in an array ? Design a Las Vegas algorithm for searching an element in an array. Nov 19 2020 08:14 PM differences between las vegas and montecarlo algorithms I'm studying the last Vegas version of the quicksort algorithm and and the MONTECARLO version of the Minimum Cut in graphs algorithm while in the LVquicksort choosing a random pivot makes it a probabilistic algorithm I can't figure out why the Min cut algorithm is considered probabilist too (a) Explain the similarities and differences between Monte Carlo algorithms and Las Vegas algo- (2 marks) rithms. (b) Suppose that a Monte Carlo algorithm A for a decision problem X is yes-biased, runs in linear time, and has false negative rate 1/2. Explain how to obtain a .999-correct algorithm for X (3 marks) that runs in linear time A **Las** **Vegas** **algorithm** for this task is to keep picking a random element until we find a 1. A **Monte** **Carlo** **algorithm** for the same is to keep picking a random element until we either find 1 or we have tried maximum allowed times say k. The **Las** **Vegas** **algorithm** always finds an index of 1, but time complexity is determined as expect value * The difference between a Las Vegas algorithm and a Monte Carlo algorithm is that a Las Vegas algorithm is always correct but its running time may be large with small probability*, whereas a Monte Carlo algorithm always has the same time complexity but may give wrong results with small probability

Monte Carlo and Las Vegas Randomized Algorithms for Systems and Control 195 Randomized algorithms belong to the class of computational algorithms known as Monte Carlo methods. This class has been widely used for simula- tions of various physical and mathematical systems that are often too difficult to carry out by determi- nistic methods Monte Carlo type algorithms and Las Vegas type algorithms. A Las Vegas algorithm will always produce the same result on a given input. Randomization will only affect the order of the internal executions. In the case of Monte Carlo algorithms, the result may might change, even be wrong. However, a Monte Carlo Las Vegas VS Monte Carlo. So, you've decided that you need a break from your favourite online casino and from work in general, where's the best place to go on holiday if you think you'll still want to play some games? Well, two candidates immediately jump out- the city of sin itself, the legendary Las Vegas and the jewel of Monaco, Monte Carlo, both famous for being quality holiday. inequality, and the difference between Las Vegas and Monte Carlo algorithms. We will also see a randomized algorithm for the maximum satisﬁability problem and analyze its performance. 2 Random Variables and Expectation In this section, we review some basic deﬁnitions and properties involving random variables and expectation

1. Explain the di erence between a deterministic, Monte Carlo, and Las Vegas algorithm using exact pattern matching as an example. You don't have to explain how the algorithms work inside, just what they achieve. 2. What is the Karp-Rabin-style ngerprint ˚ r? State the lemma describin In this paper, we present an introduction to Monte Carlo and Las Vegas randomized algorithms for systems and control. Specific applications of these algorithms include stability analysis, Lyapunov functions, and distributed consensus problems Certainly it cannot be said that gambling in Las Vegas is always correct. ;-) There is a third kind of algorithm named after a famous gambling city, the Atlantic City algorithm: Two common classes of probabilistic algorithms are Monte Carlo and Las Vegas methods. Monte Carlo algorithms are always fast, but only probably correct

Randomized algorithm: Las Vegas and Monte Carlo Algorithm CS174 Lecture 2 Summary . Monte-Carlo vs. Las Vegas. A random algorithm is Las Vegas if it always produces the correct answer. The running time depends on the random choices made in the algorithm. Random Quicksort is a Las Vegas algorithm

One has to distinguish between algorithms that use the random input so that they always terminate with the correct answer, but where the expected running time is finite (Las Vegas algorithms, for example Quicksort), and algorithms which have a chance of producing an incorrect result (Monte Carlo algorithms, for example the Monte Carlo algorithm. Monte Carlo Algorithm vs Las Vegas Algorithm. Las Vegas (LV) Algorithms - Are randomized algorithms that always give the correct answer. The running time however is not fixed (not deterministic), that is it can vary for the same input. For eg. Randomized Quick Sort always gives a correctly sorted array as its output From Wikipedia about randomized algorithms. One has to distinguish between algorithms that use the random input to reduce the expected running time or memory usage, but always terminate with a correct result in a bounded amount of time, and probabilistic algorithms, which, depending on the random input, have a chance of producing an incorrect result (Monte Carlo algorithms) or fail to produce.

- Monte Carlo Algorithm: A Monte Carlo algorithm is a type of resource-restricted algorithm that returns answers based on probability. As a result, the solutions.
- TTBOMK, stochastic algorithm is not a standard term. Randomized algorithm is, however, and it's probably what is meant here. Randomized: Uses randomness somehow. There are two flavours: Monte Carlo algorithms always finish in bounded time, but don't guarantee an optimal solution, while Las Vegas algorithms aren't necessarily guaranteed to finish in any finite time, but promise to find the.
- istic in principle. They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other.
- Las Vegas - Monte Carlo Price Comparison Chart. The Cost of living in Las Vegas compared to Monte Carlo shows that in United States sometimes you would SAVE 1,032 USD (760 EUR) for the Monaco same items. Compare Cost of living between Las Vegas and Monte Carlo Las Vegas Monte Carlo Taxi Fuel Typical Meal Rice Potato 0$ 5$ 10$ 15$ USD

Source: Wikipedia, 2021. 4. is a capital city. Las Vegas. Monaco. National capital status indicates that a city is of great importance for political and diplomatic matters. Source: Wikipedia, 2021. 5. Gambling is legal within the city. Las Vegas These are called Monte Carlo randomized algorithms. Las Vegas Algorithms. A randomized algorithm Aon input I could always return the correct solution A(I), however, the running time T A(I) is a random variable. In particular, if one is unlucky the algorithm may just run for ever. For these algorithms, what is more of interest is the expected. Pages 4 ; Ratings 100% (1) 1 out of 1 people found this document helpful; This preview shows page 3 - 4 out of 4 pages.preview shows page 3 - 4 out of 4 pages Second, not all Monte Carlo algorithms are qualiﬁed in the new formal model. As depicted in Figure 1, we explore a constraint on the difference between Las Vegas algorithms and Monte Carlo algorithms. If an algorithm belongs to Las Vegas random algorithm family, then the algorithm always produce

- inequality, and the
**difference****between****Las****Vegas****and****Monte****Carlo****algorithms**. We will also see a randomized**algorithm**for the maximum satisﬁability problem and analyze its performance. 2 Random Variables and Expectation In this section, we review some basic deﬁnitions and properties involving random variables and expectation - 4. Las Vegas vs Monte Carlo algorithms. It is possible for a randomized algorithm to fail some of the time but still be useful; we just need a bound on the probability of failure. We typically consider two classes of algorithms: Las Vegas algorithms The algorithm fails with some probability, but we can tell when it fails
- Las Vegas algorithm than a Monte Carlo algorithm: we aim to get perfect samples of a quantity with an algorithm that has random running times. We denote this approach Markov Chain Las Vegas with Kmaximum steps (MCLV- ). arXiv:1711.08442v1 [cs.LG] 22 Nov 201

- istic polynomial-time algorithm for primality (cf. Complexity theory)
- randomized algorithms, Las Vegas and Monte Carlo. Las Vegas algorithms always generate a correct solution, but their runtimes vary depending on the distribution of inputs. In contrast, Mote Carlo algorithms may sometimes produce an incorrect solution, but they run in a predictable amount of time
- Such algorithms are called Monte Carlo Algorithms and are easier to analyse for worst case. On the other hand, time complexity of other randomized algorithms (other than Las Vegas) is dependent on value of random variable. Such Randomized algorithms are called Las Vegas Algorithms. These algorithms are typically analysed for expected worst case

Park MGM Las Vegas vs MGM Grand Las Vegas. Both properties are highly recommended by expert writers. On balance, Monte Carlo Resort & Casino scores marginally better than MGM Grand Hotel and Casino. Monte Carlo Resort & Casino comes in at 81 with endorsements from 10 reviewers such as Oyster, Fodor's and Gayot From Monte Carlo to Las Vegas: Improving Restricted Boltzmann Machine Training Through Stopping Sets We propose a Las Vegas transformation of Markov Chain Monte Carlo (MCMC) estimators of Restricted Boltzmann Machines (RBMs). (LVS-K) for RBMs and explore the correspondence and differences between LVS-K and Contrastive Divergence (CD-K. ized algorithm design, and the probabilistic tools and techniques used to analyze randomized algorithms. Among other accomplishments, they will have: An understanding of the major categories of approaches to using randomness to solve problems, and the difference between Las Vegas and Monte Carlo algorithms An Introduction to Bioinformatics Algorithms www.bioalgorithms.info Two Types of Randomized Algorithms • Las Vegas Algorithms - always produce the correct solution (ie. RandomizedQuickSort) • Monte Carlo Algorithms - do not always return the correct solution. • Las Vegas Algorithms are always preferred, but they are often hard to come by

- The purpose of Monte Carlo methods is to use them in cases in which mathematical solutions are not available. True False The trimmed mean is preferred to... the standard deviation the arithmetic mean, in the presence of outliers the median the interquartile range The idea behind Monte Carlo methods is... to simulate the stochastic process of interest to win big in Las Vegas to win big in.
- Monte Carlo theory, methods and examples I have a book in progress on Monte Carlo, quasi-Monte Carlo and Markov chain Monte Carlo. Several of the chapters are polished enough to place here. I'm interested in comments especially about errors or suggestions for references to include
- istic computation. And this restriction is the same as the restriction one uses to deﬁne Monte Carlo computation as a restricted nondeter
- ate quickly on any input, however it has a probability of returning the wrong result. Whereas a Las Vegas algorithm is guaranteed to be correct, but only ter

Las Vegas and Monte Carlo Algorithms; Two Simple Examples . A Monte Carlo algorithm; A Las Vegas algorithm; Randomized Quicksort . Expected running time of randomized quicksort; Randomized Selection . Expected running time of randomized selection; Occupancy Problems . Number of balls in each bin; Number of empty bins; Balls falling into the. The Las Vegas complexity of with respect to a class of algorithms is the minimum (best) Las Vegas complexity among all for . The -Monte Carlo complexity of with respect to is the minimum number such that there is an algorithm in which has for all a probability of at least to find an optimum within the first function evaluations A little history about Monte Carlo simulation, which is the topic of today's lecture. The concept was invented by the Polish American mathematician, Stanislaw Ulam. Probably more well known for his work on thermonuclear weapons than on mathematics, but he did do a lot of very important mathematics earlier in his life A Beginner's Guide to Markov Chain Monte Carlo, Machine Learning & Markov Blankets. Markov Chain Monte Carlo is a method to sample from a population with a complicated probability distribution. Sample - A subset of data drawn from a larger population. (Also used as a verb to sample; i.e. the act of selecting that subset

Monte Carlo integration or approximation (the two terms can be used however integration is generally better) is probably an old method (the first documented reference to the method can be found in some publications by mathematician Comte de Buffon in the early 18th century) but was only given its current catchy name sometime in the mid 1940s With the rise of Monte Carlo analysis as the most commonly used method of conducting financial planning analyses for clients, 'probability of success' has become the dominant metric that financial advisors rely on to assess and report a client's prospects for financial security in retirement. It is the focal point of communicating results in most planning software Las Vegas Strip is one of the most popular tourist destinations in the United States, as well as in the world. Many of the world's largest hotels, casinos and resort properties are located on the Las Vegas Strip. Luxury hotels and resorts like Flamingo Luxor, Mandalay Bay, Bellagio, MGM Grand, Monte Carlo and Wynn are found in the Las Vegas. What is the difference between an optimization problem and a Machine Learning problem? What are deterministic algorithms? (nothing random) What are Las vegas algorithms? (exact or no solution, random resources) What are Monte Carlo algorithms? (approximate solution with random error) Adversarial Networks. Discuss state-of-the-art attack. A simulation algorithm based on the law of large number and Monte Carlo method in the classical computer environment is presented. During the simulation of the original quantum BB84 protocol in ideal environment, the sender Alice tries to send classical bit 0 or 1 to the receiver Bob, and the eavesdropper Eve tries to get the transmission information by intercepting and resending the quantum.

makes Monte Carlo methods prohibitive for design iterations and detailed whole-core analysis. Method overview and implementation . The tracking phase of the Monte Carlo simulation is undisturbed by this extension. Particle Las Vegas, NV, April 18-23, 2010, ANS (2010). Monte Carlo methods are a class of techniques for randomly sampling a probability distribution. There are many problem domains where describing or estimating the probability distribution is relatively straightforward, but calculating a desired quantity is intractable. This may be due to many reasons, such as the stochastic nature of the domain or an exponential number of random variables View Randomized Algorithms.pptx from CS 501 at Dr. A.P.J. Abdul Kalam Technical University. Randomized Algorithms Introduction An algorithm that uses Random Numbers to decide what to d Rome2rio makes travelling from Las Vegas to Monte Carlo easy. Rome2rio is a door-to-door travel information and booking engine, helping you get to and from any location in the world. Find all the transport options for your trip from Las Vegas to Monte Carlo right here

Flying time from Las Vegas, NV to Monte Carlo, Monaco. The total flight duration from Las Vegas, NV to Monte Carlo, Monaco is 12 hours, 13 minutes.. This assumes an average flight speed for a commercial airliner of 500 mph, which is equivalent to 805 km/h or 434 knots ** What are Monte Carlo algorithms? I will keep on adding more questions to both this list and my GitHub repository **. Moreover, my plan is to add answers to these questions as well Monte Carlo simulations have been performed to model the gamma ray emission and attenuation properties of common rocks. In geologic materials, 40 K, 238 U, and 232 Th are responsible for most gamma ray production. If the concentration of these radioelements and attenuation factors such as degree of water saturation are known, an estimate of the gamma-ray exposure rate can be made

Get cheap flights from Las Vegas to Monte Carlo with Skyscanner Australia. Our search engine is a consumer favourite and recommended in Australia as a comprehensive and fast way to find cheap flights.We are rated highest on Product Review amongst similar travel service providers ** The accuracy of a calculated dose distribution compared to the actual dose administered to a patient undergoing electron radiation treatment is dependent upon the configured electron dose calculation algorithm in the treatment planning system (TPS)**. Configuration of the electron Monte Carlo (eMC) algorithm in the Eclipse TPS requires a variety of beam scan data Fionn created algorithms that count every word in the scene and its relation to every other word - it's called the Monte Carlo method because you examine every possible permutation, Ganz explains

** Macau in spite of being touted as the Las Vegas is nowhere near Las Vegas (literally and figuratively)**. But if you are interested in gambling and have tons of money to burn, then Macau is the place to go. Entertainment as far as westerners are used to are virtually non-existent but like all other places it has its seedy side Search and compare cheap flights from Las Vegas to Monte Carlo. Find information on direct flights and the cheapest month to fly to Monte Carlo. COVID-19 travel info. Navigate travel entry restrictions and quarantine requirements for any destination with our live map. And get updates when things change The term stands for Markov Chain Monte Carlo, because it is a type of Monte Carlo (i.e., a random) method that uses Markov chains (we'll discuss these later). MCMC is just one type of Monte Carlo method, although it is possible to view many other commonly used methods as simply special cases of MCMC Finally, the results of Monte Carlo simulations were used as the input data of MATLAB software, and the percentage dose difference for each new configuration (i.e. different thickness of inhomogenity at different distances from the source) was estimated using the 2D interpolation of MATLAB

The cheapest way to get from Las Vegas Airport (LAS) to Monte Carlo costs only 373€, and the quickest way takes just 15¼ hours. Find the travel option that best suits you The Monte Carlo method provides powerful geometric modeling capabilities for large problem domains in 3-D; therefore, the Monte Carlo method is becoming popular for 3-D fuel depletion analyses to compute quantities of interest in spent nuclear fuel including isotopic compositions. The Monte Carlo approach has not been fully embraced due to unresolved issues concerning the effect of Monte Carlo. We recall from that, by Markov's inequality, every Las Vegas algorithm is also (up to a factor of 1 / p in the runtime) a p-Monte Carlo algorithm. We also repeat the following statement which is a convenient tool to bound p-Monte Carlo complexities If someone could please explain the difference between run from the casino and leave the casino or make your goal vs. hit it would be greatly appreciated. For my part it kind of sounds like the difference between me going to the movies versus me going to the cinema. Those two are worlds apart as well

Compare flights from Las Vegas to Monte Carlo and find the cheapest flights with Skyscanner. Skyscanner is a fast and simple travel search engine that helps you to find cheap flights and great prices on flights from Las Vegas to Monte Carlo The Las-Vegas Processor Identity Problem (How and When to Be Unique) E the Monte-Carlo model, where the algorithm may fail with some low probability. If we are willing to tolerate erroneous termina-tion, then there exists a trivial solution that does not require some similarities and some deep differences between this model and the. Two types of randomized algorithms • Las Vegas Algorithms - always produce the correct solution • Monte Carlo Algorithms - do not always return the correct solution • Las Vegas Algorithms are always preferred, but they are often hard to come by 40. Profiles • Let s=(s Las Vegas, Las Vegas, NV,USA mehdizehtabian@yahoo.com. Received 5 May method. Several different Monte Carlo codes have been utilized for the dosimetric evalua- The exact cause of the differences between various Monte Carlo reported data generate ence between Las Vegas and Monte Carlo algorithms 1 • Learned how to employ the probabilistic method to establish properties of combinatorial structures • An understanding of the fundamentals of Markov Chains and the Monte Carlo Metho

• distinguishing **between** **Las** **Vegas** **and** **Monte** **Carlo** **algorithms** • using the moment-generating function and Chertoff bounds for analysing the tail probabilities • using the balls and bins model to solve concrete problems and analyse randomised **algorithms** • using randomised graphs to analyse the average complexity of hard problem In fact, across the top casinos on the Las Vegas strip, poker chips will range in weight from 8.5 grams to 10.6 grams. Chips are made out of clay or ceramic. All casinos have stamps or markings. Las Vegas Outlet Center (nee Belz), located a couple miles south of the main Strip area, is the larger of the two and just goes on and on and on. LVOC (nee Belz) is very popular with the TG community. Las Vegas Premium Outlets is a large open-air mall at the intersection of Bonneville and Grand Central, just southwest of dowtown. Reports are.

9. Linq Promenade vs. Linq Hotel. The Linq shopping center is between Flamingo Las Vegas and Linq Hotel & Casino. The Linq Hotel & Casino is a new name for an old hotel. As we mentioned, the Linq Hotel was previously called The Quad (for about two years, long story), and before that it was the Imperial Palace.The Linq shopping promenade is home to the world's tallest Ferris wheel, the High. Another difference between Circa and other new Las Vegas casinos is that this is new construction. Park MGM, the newest casino in Las Vegas, is an update of an old casino named Monte Carlo. Circa will be the first new casino build in downtown Las Vegas since 1980. The plans for Circa are massive The eight to nine hour time difference between Las Vegas and Germany gets to many people. Use the hire car only for short trips in the first few days until you get used to Vegas time. For more tips on dealing with jet lag, check out our special

Las Vegas algorithms always output correct answers but the running time is random. The time complexity of a Las Vegas algorithm is measure by the expected running time. The concept of Las Vegas algorithm is introduced by Babai in 1979 in his seminal work on graph isomorphsm testing. A Las Vegas algorithm can be converted to a Monte Carlo. Understand the differences between probabilistic analysis and randomized algorithms, and how RAs can be used in design and analysis. Understand how to use some of the analytical tools we discussed, such as indicator variables Understand the basic difference between Las Vegas and Monte Carlo RA A small Las Vegas casino offered a blackjack rule variation called the Free Ride in which players were given a free right-to-surrender token every time they received a natural. Proper use of the token led to a player edge of 1.3%, and the casino lost an estimated $17,000 in eight hours Las Vegas became a dining destination in 1998, when the Bellagio Hotel opened, bringing celebrity chefs and restaurants, such as Jean-Georges Vongerichten and Le Cirque, to the strip. The hotels' one-upmanship means that the market for high-end dining has not abated. In the last decade, Las Vegas has become one of the most exciting. From Monte Carlo to Las Vegas: Improving Restricted Boltzmann Machine Training Through Stopping Sets Savarese, Pedro H. P., Kakodkar, Mayank, and Ribeiro, Bruno In AAAI 2018 We propose a Las Vegas transformation of Markov Chain Monte Carlo (MCMC) estimators of Restricted Boltzmann Machines (RBMs)

GOES 11 images of Las Vegas region for 6/04/2008 around 4PM (PST) with difference between corrected and reference images; (c) difference between corrected and MC Monte Carlo MTTA Mean Time to Attack MTTF Mean Time to Failur Why are Las Vegas algorithms called Las Vegas? I just found out why Monte Carlo algorithms are called that (secret, codename suggested by colleague of author), which is very underwhelming by itself, but found absolutely no information about Las. Monte Carlo simulation is considered a good way to face these problems, but there is the difficult problem to optimize. This paper presents a model of optimization under uncertainty with genetic algorithms and Monte Carlo simulation. This approach permits to get new insights for the real options theory

In addition to the casino, there is a spa salon, business center, access to the Las Vegas Monorail, a buffet and on-site restaurants. Several room sizes are available from standard rooms to. improvement can make a difference between the World Series and elimination, every pitching change matters. The input to our algorithm is the roster of the home team, the roster of the away team, statistics of all players on each team leading up to a game, and all metadata about the game, like the stadium or ﬁeld conditions Las Vegas Strip and Downtown are two different areas in Las Vegas, Nevada. Las Vegas Strip is much larger and has more glamorous mega hotels and casinos when compared to Downtown. This is the key difference between Las Vegas Strip and Downtown. Downtown Las Vegas was the original gambling city of Las Vegas The purpose of this page is to provide resources in the rapidly growing area computer simulation. This site provides a web-enhanced course on computer systems modelling and simulation, providing modelling tools for simulating complex man-made systems. Topics covered include statistics and probability for simulation, techniques for sensitivity estimation, goal-seeking and optimization. Then, the Monte Carlo method and local update algorithm were applied to estimate the distance and relativity from node 'i' to node 'e'. There could be two possible outcomes when using this methods; if the end node ' e ' could not be reached from node i , either; the node does not exist or the node was removed in the process of.

@RISK is an add-in to Microsoft Excel and Project that lets you analyze risk using Monte Carlo simulation. @RISK shows you virtually all possible outcomes for any situation—and tells you how likely they are to occur AXB agrees the Monte Carlo method within 2% in low density lung, while the AAA shows a difference of 12% (Failla et al 2010). In bone and bone-tissue interface regions, dosimetric inaccuracy as large as 6.4% in AAA calculations has been reported, whereas AXB algorithm markedly improved the situation (Han et al 2011) • Regression modeling I — Module for analyzing the relationship between a dependent variable and one or more independent variables. The CrimeStat regression module includes Normal (Ordinary Least Squares), Poisson-based and Binomial Logit regression models, estimated by Maximum Likelihood (MLE) or Markov Chain Monte Carlo (MCMC) algorithms On this enjoyable exclusive tour, you will get a comprehensive VIP tour of the Hoover Dam. This tour gets you to the dam before the crowds arrive, giving you more time to enjoy your destination! Included is a ticket for the powerplant tour INSIDE the dam, the Hoover Dam memorial bridge (where you can get beautiful photos of the dam from afar), admission to Visitor Center exhibits and. The second method is to maximise the width of exploration space under the current situation. According to the AlphaZero algorithm method in sole exception, to ensure exploration, we add noise [10, 13] to expand the width of Monte-Carlo tree search (MCTS) and search for more possible locations of CNVs. 2.3 Judgment of network structur