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Dynamic programming problems are to be solved with tabular methods

breadth-first search

Memorize the value of pi You should always try to remember the value of pi as far as possible, 3.1415926535897932384626433832795, certainly the part in italics. The judges may not give the value in the question, and if you use values like 22/7 or 3.1416 or 3.142857, then it is very likely that some of the critical judge inputs will cause you to get the wrong answer. You can also get the value of pi as a compiler-defined constant or from the following code: Pi=2*acos(0)

design pattern is a widely accepted solution to a recurring design problem in OOP a design pattern describes how to structure classes to meet a given requirement provides a general blueprint to follow when implementing part of a program does not describe how to structure the entire application does not describe specific algorithms focuses on relationships between classes

design patterns: make you more productive help you write cleaner code Observer and Singleton are just two of the many available if you like design patterns, try these resources: GoF book -- Design Patterns: Elements of Reusable Object-oriented Software design pattern examples in Java, see Design Patterns in Java Reference and Example Site

learn what a design pattern is

In computer science, hill climbing is a mathematical optimization technique which belongs to the family of local search. It is relatively simple to implement, making it a popular first choice. Although more advanced algorithms may give better results, in some situations hill climbing works just as well. Hill climbing can be used to solve problems that have many solutions, some of which are better than others. It starts with a random (potentially poor) solution, and iteratively makes small changes to the solution, each time improving it a little. When the algorithm cannot see any improvement anymore, it terminates. Ideally, at that point the current solution is close to optimal, but it is not guaranteed that hill climbing will ever come close to the optimal solution. For example, hill climbing can be applied to the traveling salesman problem. It is easy to find a solution that visits all the cities but will be very poor compared to the optimal solution. The algorithm starts with such a solution and makes small improvements to it, such as switching the order in which two cities are visited. Eventually, a much better route is obtained. Hill climbing is used widely in artificial intelligence, for reaching a goal state from a starting node. Choice of next node and starting node can be varied to give a list of related algorithms.

The Belief-Desire-Intention (BDI) software model (usually referred to simply, but ambiguously, as BDI) is a software model developed for programming intelligent agents. Superficially characterized by the implementation of an agent's beliefs, desires and intentions, it actually uses these concepts to solve a particular problem in agent programming. In essence, it provides a mechanism for separating the activity of selecting a plan (from a plan library) from the execution of currently active plans. Consequently, BDI agents are able to balance the time spent on deliberating about plans (choosing what to do) and executing those plans (doing it). A third activity, creating the plans in the first place (planning), is not within the scope of the model, and is left to the system designer and programmer.

The Belief-Desire-Intention (BDI) software model (usually referred to simply, but ambiguously, as BDI) is a software model developed for programming intelligent agents. Superficially characterized by the implementation of an agent's beliefs, desires and intentions, it actually uses these concepts to solve a particular problem in agent programming. In essence, it provides a mechanism for separating the activity of selecting a plan (from a plan library) from the execution of currently active plans. Consequently, BDI agents are able to balance the time spent on deliberating about plans (choosing what to do) and executing those plans (doing it). A third activity, creating the plans in the first place (planning), is not within the scope of the model, and is left to the system designer and programmer.