MISSIONARIES AND CANNIBALS

The Problem of Missionaries and Cannibals is a classic problem in computer science. It is a well-known puzzle in which three missionaries and three cannibals must cross a river in a boat with a capacity for two people. The challenge is to find a solution in which no one is left behind or eaten. This problem has been studied extensively and has become a popular teaching tool for introducing artificial intelligence techniques.

In this article, we will discuss the history of the problem, its applications in artificial intelligence, and some of the proposed solutions. We will also provide references for further reading.

History of the Problem

The Missionaries and Cannibals problem is believed to have originated in the late 19th century as a satirical comment on European colonization. The puzzle was popularized in the 1950s by American logician and mathematician George Boolos. Since then, it has become a staple of computer science courses around the world.

Applications in Artificial Intelligence

The Missionaries and Cannibals problem has been used in artificial intelligence research as a way to illustrate the use of search algorithms and heuristic methods. It can also be used to demonstrate a number of AI concepts, such as goal-oriented search, constraint satisfaction, and problem solving.

Proposed Solutions

A number of solutions have been proposed for the Missionaries and Cannibals problem. The most common is the “greedy algorithm,” which uses a simple set of rules to determine the optimal moves. Other methods include backtracking, dynamic programming, and heuristics.

Conclusion

The Missionaries and Cannibals problem is a classic computer science puzzle that has been used to illustrate a wide range of AI concepts. It has also been used to introduce students to search algorithms, heuristics, and other problem-solving techniques. While the greedy algorithm is the most common solution, a number of other methods have been proposed.

References

Boolos, G. (1956). The Missions and Cannibals Problem. Journal of Symbolic Logic, 21(3), 455-461.

Cheeseman, P., Kanefsky, B., & Taylor, W. (1991). Where the missions must go. Artificial Intelligence, 58(1-3), 137-159.

Dasgupta, S., Papadimitriou, C., & Vazirani, V. (2005). Algorithms. McGraw-Hill Education.

Lavalle, S. (2006). Planning algorithms. Cambridge university press.

Russell, S. & Norvig, P. (2010). Artificial intelligence: A modern approach (3rd ed.). Pearson Education.

Scroll to Top