Missionaries and cannibals

Author: f | 2025-04-25

The solution to the Missionaries and Cannibals problem. missionaries-and-cannibals missionaries-and-cannibals-problem Updated ; Python;

Solved Missionaries and Cannibals The Missionaries

Here are 34 public repositories matching this topic... Code Issues Pull requests Missionaries and cannibals problem resolved with Breadth-First Search Updated Jun 17, 2015 Python Code Issues Pull requests Updated Dec 14, 2017 Common Lisp Code Issues Pull requests Implementation of classic search algorithms in Common Lisp Updated Jan 9, 2018 Common Lisp Code Issues Pull requests AI Based Missionaries and Cannibals Problem done in python using pygame Library Updated Feb 15, 2018 Python Code Issues Pull requests Python program that solves the Missionaries and Cannibals problem, a toy problem in AI, with iterative deepening search. Updated Feb 17, 2018 Python Code Issues Pull requests Three missionaries and three cannibals are on one side of a river, along with a boat that can hold one or two people. Find a way to get everyone to the other side without ever leaving a group of missionaries in one place outnumbered by the cannibals in that place. Updated Feb 17, 2018 Python Code Issues Pull requests Missionaries and cannibals solver written in common Lisp Updated Mar 11, 2018 Common Lisp Code Issues Pull requests Solution for the Missionaries and Cannibals problem using Message Queues and Multiprocessing Updated Mar 24, 2018 C++ Code Issues Pull requests This Python implementation is a scaled up version of the Missionaries and Cannibals problem with arbitary number of missionaries, cannibals and boat capacity Updated Nov 25, 2018 Python Code Issues Pull requests AI Lab Offlines and Onlines Updated Dec 2, 2018 Java Code Issues Pull requests Updated Feb 14, 2019 C++ Code Issues Pull requests Assignments of Artificial Intelligence Sessional Course CSE 318 in Level-3, Term-2 of CSE, BUET Updated Feb 15, 2019 C++ Code Issues Pull requests missionaries and cannibals problem as desribed to learn to use the aima library Updated Mar 31, 2019 Java Code Issues Pull requests Missionaries and Cannibals Problem Updated Apr 7, 2019 C++ Code Issues Pull requests Artificial Intelligence Assignment 2 Updated Dec 16, 2019 Python Code Issues Pull requests Resolvendo o problema dos Missionarios e Canibais, usando BFS (Breadth-First Search). Updated Dec 16, 2019 Python Code Issues Pull requests Os Missionary and Cannibal Problem in PrologWrite the PROLOG code for the missionaries and cannibals problem as follows: The problem involves three missionaries and three cannibals, all six of whom are originally on one side of a river. There is one boat that will be used to ferry the missionaries and cannibals to the other side of the river. The boat holds two occupants at most, and there is no way to send the boat across the river without having at least one occupant in the boat. The threat is that, if the cannibals outnumber the missionaries in any circumstance, then the cannibals will cook and eat the missionaries. Use the search superstructure to design a Prolog program that searches for ways to ferry all six persons to the other side of the river. Suggestion: Use state representation [M,C,B] where M is the number of missionaries and C is the number of cannibals on bank B. B is 'e' to indicate the near (east) bank and is 'w' to indicate the far (west) bank. The start state is [3,3,e], and the goal state is [3,3,w]. Write specifications for 'start', 'goal', 'next_state' and 'safe_state', and add them to the search superstructure to obtain a complete program to solve this puzzle. Your program should be able to calculate two distinct minimal solutions each involving eleven boat trips across the river. a. Execute this code and draw a graph of the search space. b. Verify if altering the rule ordering produces alternative solution paths by changing all the rules of missionaries and cannibals crossing river in reverse order.

GitHub - kevinrosalesdev/Missionaries-and-Cannibals: Cannibals

Missionaries and Cannibals problem is very famous in Artificial Intelligence because it was the subject of the first paper that approached problem formulation from an analytical viewpoint. The problem can be stated as follow. Three missionaries and three cannibals are on one side of a river, along with a boat that can hold one or two people. Now we have to find a way to get everyone to the other side, without ever leaving a group of missionaries in one place outnumbered by the cannibals in other side.IntroductionMissionaries and Cannibals problem is very famous in Artificial Intelligence because it was the subject of the first paper that approached problem formulation from an analytical viewpoint. The problem can be stated as follow. Three missionaries and three cannibals are on one side of a river, along with a boat that can hold one or two people. Now we have to find a way to get everyone to the other side, without ever leaving a group of missionaries in one place outnumbered by the cannibals in other side. The above problem can be solved by a graph search method. Here I represent the problem as a set of states and operators. States are snapshots of the world and operators are those which transform one state into another state. States can be mapped to nodes of a graph and operators are the edges of the graph.ExplanationMissionaries and Cannibals cab be solved by using different search algorithms like Breadth first and Depth first search algorithm to find the solution. The node of the graph to be searched is represented by a state space. Each state space can be represent byState(no_of_missionaries, no_of_cannibals, side_of_the_boat)Where no_of_missonaries are the number of missionaries at left side of river, no_of_cannibals are the number of cannibals at the left side of river. The solution to the Missionaries and Cannibals problem. missionaries-and-cannibals missionaries-and-cannibals-problem Updated ; Python; Download Missionaries and Cannibals for free. Missionaries and Cannibals - In this game you need to move the missionaries and the cannibals to the opposite

GitHub - ahosanu/Missionaries-And-Cannibals: In the missionaries

Skip to content Navigation Menu Sign in GitHub Copilot Write better code with AI Security Find and fix vulnerabilities Actions Automate any workflow Codespaces Instant dev environments Issues Plan and track work Code Review Manage code changes Discussions Collaborate outside of code Code Search Find more, search less Explore All features Documentation GitHub Skills Blog By company size Enterprises Small and medium teams Startups Nonprofits By use case DevSecOps DevOps CI/CD View all use cases By industry Healthcare Financial services Manufacturing Government View all industries View all solutions Topics AI DevOps Security Software Development View all Explore Learning Pathways Events & Webinars Ebooks & Whitepapers Customer Stories Partners Executive Insights GitHub Sponsors Fund open source developers The ReadME Project GitHub community articles Repositories Topics Trending Collections Enterprise platform AI-powered developer platform Available add-ons Advanced Security Enterprise-grade security features Copilot for business Enterprise-grade AI features Premium Support Enterprise-grade 24/7 support Pricing Provide feedback --> We read every piece of feedback, and take your input very seriously. Include my email address so I can be contacted Saved searches Use saved searches to filter your results more quickly Sign in Sign up Explore Topics Trending Collections Events GitHub Sponsors # missionaries-cannibals-problem Star Here are 2 public repositories matching this topic... Language: Java Filter by language All 34 Python 17 C++ 4 C 3 Common Lisp 3 Jupyter Notebook 3 Java 2 HTML 1 shamiul94 / Artificial-Intelligence-Sessional-Cannibal-Missionary-Problem-and-n-Puzzle-problem- Star 0 Code Issues Pull requests AI Lab Offlines and Onlines a-star dfs bfs dfs-algorithm 8-puzzle 15-puzzle bfs-algorithm n-puzzle 8-puzzle-solver a-star-algorithm a-star-search missionaries-cannibals-problem cannibals-problem a-star-path-finding Updated Dec 2, 2018 Java chkrr00k / missionaries-and-cannibals Star 0 Code Issues Pull requests missionaries and cannibals problem as desribed to learn to use the aima library ai learning-exercise aima ai-learning missionaries-cannibals-problem aima-java Updated Mar 31, 2019 Java Improve this page Add a description, image, and links to the missionaries-cannibals-problem topic page so that developers can more easily learn about it. Curate this topic Add this topic to your repo To associate your repository with the missionaries-cannibals-problem topic, visit your repo's landing page and select "manage topics." Learn more And side_of_the_boat is the side of the boat at particular state. For our case Initial State => State(3, 3, 0) and Final State => State(0, 0, 1).Where 0 represents left side and 1 represents right side of river. We should make a graph search which traverse the graph from initial state and find out the final state in fewest moves. There are many AI searches that search the graphs like Breadth first search, Depth first search, or iterative deepening search. Each of these different search methods has different properties such as whether a result is guaranteed, and how much time and space is needed to carry out the search. This project uses Breadth first and Depth first search.Production rules for Missionaries and Cannibals problem Possible MovesA move is characterized by the number of missionaries and the number of cannibals taken in the boat at one time. Since the boat can carry no more than two people at once, the only feasible combinations are: Carry (2, 0). Carry (1, 0). Carry (1, 1). Carry (0, 1). Carry(0, 2). Where Carry (M, C) means the boat will carry M missionaries and C cannibals on one trip.Feasible MovesOnce we have found a possible move, we have to confirm that it is feasible. It is not a feasible to move more missionaries or more cannibals than that are present on one bank. When the state is state(M1, C1, left) and we try carry (M,C) then M must be true. When the state is state(M1, C1, right) and we try carry(M, C) then M + M1 must be true.Legal MovesOnce we have found a feasible move, we must check that is legal i.e. no missionaries must be eaten. Legal(X, X). Legal(3, X). Legal(0, X). The only safe combinations are when there are equal numbers of

-Missionaries-and-Cannibals-Backend-/Missionary and Cannibels

Fiji used to export druas or efficient and beautiful sailing canoes to Tonga.The Europeans first showed up in the late 1600s. The first Europeans to have regular contact with Fiji were the sea cucumber and sandalwood traders. The conflict was minimal between these traders and the Fijians.Then, the missionaries showed up and Britain decided it was important to reign in the traders and get them to pay tax.From the get-go, the British colonial power painted Fiji as a paradise full of cannibals. This was done to cement their control of the islands, as the colonists could see Fiji’s location had strategic value. The Fijians fought long and brutal wars against the British and the Christians. However, the disunified language groups also fought each other. When slavery became outlawed in the United States, many settlers flocked to Fiji to take advantage of the lack of land and labour laws.Conflict resumed between the Kai Colo (or mostly unchristened Fijians who fought the colonists) and the influential Fijian tribes who were cooperating with the settlers. The Kingdom of Fiji was briefly established, although it was marred by blackbirding, fighting with the Kai Colo, and the increasingly violent cotton farmers. The British then annexed Fiji and, following a devastating measles outbreak, began importing indentured South Asian labourers from their other colony – British India. The British attempted to appease the influential Fijian tribes and put in place land laws stating that Indians could not own any land – only Fijians could. These laws are still in place to this day.The 20th century saw Fiji gain its independence and navigate decolonising. While Fiji has always been a multicultural society, that’s not to say it’s been without its tension. There have been several military coups by Fijian nationalists who direct a lot of anger at Indo-Fijians

Missionaries and Cannibals.ppt - MISSIONARIES AND CANNIBALS PROBLEM

The-Missionaries-and-Cannibals-ProblemA solution to The Missionaries and Cannibals Problem, using Python; DFS; BFS; heuristicThis is one part of my homework.修道士野人问题的Python求解一、 问题描述修道士(Missionaries)和野人(Cannibals)问题：在河的左岸有N个传教士（M）、N个野人（C）和一条船（Boat)，修道士们想用这条船把所有人都运过河去，但有以下条件限制： （1）修道士和野人都会划船，但船每次最多只能运K个人； （2）在任何岸边野人数目都不能超过修道士，否则修道士会被野人吃掉。约束条件：① M≧C 任何时刻两岸、船上都必须满足传教士人数不少于野人数（M=0时除外，既没有传教士）② M+C≦K 船上人数限制在K以内。二、 状态空间表示（一）状态空间在此问题的求解中，选择使用三元组（M, C, S）表示问题的状态，式中M表示起始岸修道士人数，C表示起始岸野人人数，S为0-1变量，表示船的位置，当S为0时表示船在起始岸，为1时表示船在终点岸。如：（0，3，0）表示起始岸有三个野人，没有修道士，船在起始岸。于是修道士野人问题可以描述为： 从（3，3，0）到（0，0，1）的状态转换。在此问题的状态空间中共有32 种状态，其中12种不合理状态：如（1，0，1）说明右岸有2个M，3个C；4种不可能状态：如（3，3，0）说明所有M和C都在左岸，而船在右岸，所以可用的状态共16种，组成合理的状态空间。可能的问题状态分别为：(0, 0, 1), (0, 1, 1), (0, 2, 1), (1, 0, 1), (1, 1, 0), (1, 1, 1), (1, 2, 0), (1, 2, 1), (1, 3, 0), (2, 0, 1), (2, 1, 0), (2, 1, 1), (2, 2, 0), (2, 2, 1), (2, 3, 0), (3, 1, 0), (3, 2, 0), (3, 3, 0)。 （二）操作集在此问题种定义Operation操作算符，用二元组（M, C）表示，式中M表示一次划船过程中船上修道士人数，C表示穿上野人人数。并规定，每一次使用操作算符对问题状态进行操作运算后，问题状态的S必须改变，即船必须从一岸驶向另一岸。例如，当对初始问题状态（3，3，0）使用（1，1）算符后，问题状态变成（2，2，1），这表示一个修道士和一个野人划船驶到终点岸，此时船停留在重点岸。根据左右两岸和穿上都不能出现野人人数大于修道士人数的约束，可以得到可用的操作算符共有5种，分别是（0, 1）, （0, 2）, （1, 0）, (1, 1), (2, 0)。三、 程序设计（一）存储结构1.基本问题状态和操作算符使用列表存储。由于本问题仅需使用到简单的数据插入、提取等功能，因此可用选用Python提供的基本数据结构列表完成。使用列表表示问题的状态空间为：[[0, 0, 1], [0, 1, 1], [0, 2, 1], [1, 0, 1], [1, 1, 0], [1, 1, 1], [1, 2, 0], [1, 2, 1], [1, 3, 0], [2, 0, 1], [2, 1, 0], [2, 1, 1], [2, 2, 0], [2, 2, 1], [2, 3, 0], [3, 1, 0], [3, 2, 0], [3, 3, 0]]；操作集为：[[0, 1], [0, 2], [1, 0], [1, 1], [2, 0]]；2.节点关系使用字典存储。在找到目标节点后，需要回溯从开始节点走到当前节点的路径，这需要存储节点间的关系。这里使用字典存储节点间的亲属关系，子节点为键，父节点为值。（二）算法基本思想1.首先将问题初始状态（initial_state）节点放入OPEN表中（用于临时存储）；2.从OPEN表中取出首节点，判断是否为目标节点。若为目标节点，则任务完成，输出结果；若不是目标节点，则进行下一步；３.对从OPEN表中取出的不是目标节点的当前节点进行可扩展性判断，之后根据所使用的搜索策略将其子节点存入OPEN表；若当前节点不可扩展，则程序结束，问题无解。（三）搜索策略本次使用广度优先算法、有界深度优先算法和全局启发式搜索算法分别对问题进行求解。其中全局启发式搜索算法所使用的启发式函数为f(n) = d(n) + w(n), d(n)为当前节点深度，w(n)为未渡河人数；有界深度优先算法设置深度阈值为25。（四）函数设计与调用关系1.函数设计此程序共设计并使用到10个自定义函数，其中:（1）create_vertex()和create_edges()用于初始化问题条件，生成相应的节点和边；（2）move()用于对问题状态执行操作算符并控制移动过程中各状态的合理性（如避免出现不合理状态，控制船只状态等）；（3）whether_expandable()用于判断当前节点是否可扩展；（4）get_d(), get_w()和search_heuristic()共同实现启发式搜索。get_d()用于获取当前节点深度，get_w()用于计算当前节点距离目标节点的距离，即还有多少人尚未过河；（5）search_depth()深度优先搜索算法；（6）search_breadth()广度优先搜索算法；（7）heap_adjust(), heap_create()和heap_sort()用于实现堆排序功能，此功能用于给生成的子节点进行排序。2.函数调用关系程序中函数调用关系为：（1） main()->create_vertex(), create_edges(), 搜索算法（三选一）；（2） search_breadth()->whether_expandable()->move()；（3） search_ depth ()->whether_expandable()->move()；（4） search_heuristic()->whether_expandable()->move()；search_heuristic()->get_d(), get_w()；search_heuristic()->heap_sort()->heap_adjust(), heap_create()。四、 执行结果（一） 启发式索搜可用的操作算符为： [[0, 1], [0, 2], [1, 0], [1, 1], [2, 0]]可能出现的顶点有 16 种, 分别为： [[0, 0, 1], [0, 1, 1], [0, 2, 1], [1, 0, 1], [1, 1, 0], [1, 1, 1], [1, 2, 0], [1, 2, 1], [1, 3, 0], [2, 0, 1], [2, 1, 0], [2, 1, 1], [2, 2, 0], [2, 2, 1], [2, 3, 0], [3, 1, 0], [3, 2, 0], [3, 3, 0]]渡河成功！路径为：[3, 3, 0] ->[2, 2, 1] ->[3,. The solution to the Missionaries and Cannibals problem. missionaries-and-cannibals missionaries-and-cannibals-problem Updated ; Python;

Solved Missionaries and Cannibals The Missionaries and - Chegg

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