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AI Algorithms, Data Structures, and Idioms in Prolog, Lisp, and Java

Editors: William A. Stubblefield, George F. Luger (Author), AI Algorithms, Data Structures, and Idioms in Prolog, Lisp, and Java
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Algorithms: 1. Binary Search: - Prolog: Recursive implementation using pattern matching. - Lisp: Recursive or iterative implementation. - Java: Iterative implementation using loops. 2. Quick Sort: - Prolog: Implementation using partitioning and recursion. - Lisp: Often implemented with recursion. - Java: Efficient implementation with recursion and pivot selection. 3. Breadth-First Search (BFS): - Prolog: Using a queue and recursion. - Lisp: Queue-based iterative implementation. - Java: Queue-based iterative implementation using LinkedList or ArrayDeque. 4. **Depth-First Search (DFS)**: - Prolog: Recursive implementation. - Lisp: Recursive implementation. - Java: Recursive implementation or stack-based iterative implementation. Data Structures: 1. **Lists**: - Prolog: Native support for lists, commonly used in various algorithms. - Lisp: Fundamental data structure, used extensively. - Java: Implementations like ArrayList and LinkedList. 2. **Trees**: - Prolog: Often represented using recursive predicates. - Lisp: Represented using lists or dedicated tree structures. - Java: Implementations like BinarySearchTree, AVLTree, etc. 3. **Graphs**: - Prolog: Represented using predicates and facts. - Lisp: Represented using adjacency lists or matrices. - Java: Typically implemented using adjacency lists or matrices. Idioms: 1. **Recursion**: - Prolog: Fundamental to the language; many problems are solved recursively. - Lisp: Core to the language's paradigm; recursion is heavily used. - Java: Recursion is used where appropriate, but iterative solutions are often preferred due to performance considerations. 2. **Pattern Matching**: - Prolog: Integral to Prolog's logic programming paradigm. - Lisp: Can be achieved using functions like `cond` or `case`. - Java: Not a built-in feature; achieved through if-else or switch-case statements. 3. **Higher-order Functions**: - Prolog: Supports higher-order predicates. - Lisp: Functions are first-class citizens; higher-order functions are common. - Java: Introduced in Java 8 with lambdas and functional interfaces. 4. Immutable Data: - Prolog: Variables are typically not mutated once assigned. - Lisp: Promotes immutability, though mutable structures are possible. - Java: Immutable classes are encouraged for thread safety and predictable behavior. 5. **Tail Recursion Optimization**: - Prolog: Automatically optimized by most Prolog implementations. - Lisp: Supported by most Lisp implementations. - Java: Not directly supported, but tail recursion can be manually optimized in some cases. These are just a few examples, and there are many more algorithms, data structures, and idioms that can be implemented in each language. The choice often depends on the problem domain, language capabilities, and performance requirements.

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