Clolog is a small, experimental logic programming language implemented in Clojure. It aims to bring the declarative power of Prolog to Clojure, allowing developers to define facts and rules, and then query those facts and rules using logical inference. Clolog supports basic Prolog features such as unification, backtracking, and recursion, and integrates seamlessly with existing Clojure code and data structures. While it's not a full-fledged Prolog implementation, it provides a lightweight and accessible way to experiment with logic programming within the Clojure ecosystem.
The post describes solving a logic puzzle reminiscent of Professor Layton games using Prolog. The author breaks down a seemingly complex word problem about arranging differently-sized boxes on shelves into a set of logical constraints. They then demonstrate how Prolog's declarative programming paradigm allows for a concise and elegant solution by simply defining the problem's rules and letting Prolog's inference engine find a valid arrangement. This showcases Prolog's strength in handling constraint satisfaction problems, contrasting it with a more imperative approach that would require manually iterating through possible solutions. The author also briefly touches on performance considerations and different strategies for optimizing the Prolog code.
Hacker News users discuss the cleverness of using Prolog to solve a puzzle involving overlapping colored squares, with several expressing admiration for the elegance and declarative nature of the solution. Some commenters delve into the specifics of the Prolog code, suggesting optimizations and alternative approaches. Others discuss the broader applicability of logic programming to similar constraint satisfaction problems, while a few debate the practical limitations and performance characteristics of Prolog in real-world scenarios. A recurring theme is the enjoyment derived from using a tool perfectly suited to the task, highlighting the satisfaction of finding elegant solutions. A couple of users also share personal anecdotes about their experiences with Prolog and its unique problem-solving capabilities.
This 1986 paper explores representing the complex British Nationality Act 1981 as a Prolog program. It demonstrates how Prolog's declarative nature and built-in inference mechanisms can effectively encode the Act's intricate rules regarding citizenship acquisition and loss. The authors translate legal definitions of British citizenship, descent, and residency into Prolog clauses, showcasing the potential of logic programming to represent and reason with legal statutes. While acknowledging the limitations of this initial attempt, such as simplifying certain aspects of the Act and handling time-dependent clauses, the paper highlights the potential of using Prolog for legal expert systems and automated legal reasoning. It ultimately serves as an early exploration of applying computational logic to the domain of law.
Hacker News users discussed the ingenuity of representing the British Nationality Act as a Prolog program, highlighting the elegance of Prolog for handling complex logic and legal rules. Some expressed nostalgia for the era's focus on symbolic AI and rule-based systems. Others debated the practicality and maintainability of such an approach for real-world legal applications, citing the potential difficulty of updating and debugging the code as laws change. The discussion also touched on the broader implications of encoding law in a computationally interpretable format, considering the benefits for automated legal reasoning and the potential risks of bias and misinterpretation. Some users shared their own experiences with Prolog and other logic programming languages, and pondered the reasons for their decline in popularity despite their inherent strengths for certain problem domains.
C Plus Prolog is a project that embeds a Prolog interpreter within C++ code, allowing for logic programming within a C++ application. It aims to provide a seamless integration where Prolog predicates can be called directly from C++ and vice-versa, enabling the combination of Prolog's declarative power with C++'s performance and imperative features. The project leverages a modified version of SWI-Prolog, a popular open-source Prolog implementation, and offers a bidirectional interface for data exchange between the two languages. This facilitates the development of applications that benefit from both efficient procedural code and the logical reasoning capabilities of Prolog.
Hacker News users discussed the practicality and niche appeal of C Plus Prolog. Some expressed interest in its potential for specific applications like implementing rule engines or program analysis tools, while others questioned the performance implications of embedding Prolog within C++. One commenter suggested that a cleaner approach might involve interfacing Prolog with a language like Rust. Several pointed out the project's age and apparent inactivity, raising concerns about maintainability and documentation. The potential for improved tooling using C++-based IDEs was mentioned as a possible benefit. Overall, the discussion centered around the specialized nature of the project and the trade-offs involved in its approach.
The blog post demonstrates how to implement symbolic differentiation using definite clause grammars (DCGs) in Prolog. It leverages the elegant, declarative nature of DCGs to parse mathematical expressions represented as strings and simultaneously construct their derivative. By defining grammar rules for basic arithmetic operations (addition, subtraction, multiplication, division, and exponentiation), including the chain rule and handling constants and variables, the Prolog program can effectively differentiate a wide range of expressions. The post highlights the concise and readable nature of this approach, showcasing the power of DCGs for tackling symbolic computation tasks.
Hacker News users discussed the elegance and power of using definite clause grammars (DCGs) for symbolic differentiation, praising the conciseness and declarative nature of the approach. Some commenters pointed out the historical connection between Prolog and DCGs, highlighting their suitability for symbolic computation. A few users expressed interest in exploring further applications of DCGs beyond differentiation, such as parsing and code generation. The discussion also touched upon the performance implications of using DCGs and compared them to other parsing techniques. Some commenters raised concerns about the readability and maintainability of complex DCG-based systems.
The blog post "The Simplicity of Prolog" argues that Prolog's declarative nature makes it easier to learn and use than imperative languages for certain problem domains. It demonstrates this by building a simple genealogy program in Prolog, highlighting how its concise syntax and built-in search mechanism naturally express relationships and deduce facts. The author contrasts this with the iterative loops and explicit state management required in imperative languages, emphasizing how Prolog abstracts away these complexities. The post concludes that while Prolog may not be suitable for all tasks, its elegant approach to logic programming offers a powerful and efficient solution for problems involving knowledge representation and inference.
Hacker News users generally praised the article for its clear introduction to Prolog, with several noting its effectiveness in sparking their own interest in the language. Some pointed out Prolog's historical significance and its continued relevance in specific domains like AI and knowledge representation. A few users highlighted the contrast between Prolog's declarative approach and the more common imperative style of programming, emphasizing the shift in mindset required to effectively use it. Others shared personal anecdotes of their experiences with Prolog, both positive and negative, with some mentioning its limitations in performance-critical applications. A couple of comments also touched on the learning curve associated with Prolog and the challenges in debugging complex programs.
Summary of Comments ( 43 )
https://news.ycombinator.com/item?id=43695620
HN commenters generally expressed interest in Clolog, praising its simplicity and elegance. Some highlighted its potential as a pedagogical tool for introducing logic programming concepts. Others discussed its limitations, particularly around performance and the lack of certain features found in Prolog, like cut and negation. There was a short thread comparing it to miniKanren, with a commenter pointing out Clolog's more traditional Prolog-like syntax. A few users shared their experiences experimenting with the code, including porting it to other Lisps. Overall, the reception was positive, with many appreciating the project as a clean and understandable implementation of core logic programming ideas.
The Hacker News post titled "Clolog" (https://news.ycombinator.com/item?id=43695620) discussing the Clolog project (https://github.com/bobschrag/clolog) has several comments exploring various aspects of the project and its implications.
One commenter highlights the historical context of logic programming within Lisp, mentioning the development of the LOGLISP system in the early 1980s and its integration of logic programming paradigms into a Lisp environment. They also touch upon the challenges of efficiently implementing such systems, especially considering the performance limitations of hardware at the time.
Another commenter expresses their intrigue with the project, particularly the choice of Clojure as the implementation language. They appreciate the elegance of Clojure and suggest that it might provide a suitable foundation for a logic programming system. They also inquire about the project's performance characteristics and the author's motivations for choosing Clojure.
A subsequent comment raises the question of the project's practical applications and expresses curiosity about the types of problems it is designed to solve. They seem to be looking for concrete examples or use cases to better understand the scope and potential of Clolog.
Further down, a commenter delves deeper into the technical aspects of the project, specifically discussing the unification algorithm employed by Clolog. They inquire about the chosen approach and its implications for performance and expressiveness. This comment sparks a short discussion about different unification strategies and their trade-offs.
Another commenter brings up the topic of constraint logic programming and wonders if Clolog supports or plans to support constraints. They posit that constraint programming features could significantly enhance the project's applicability to a wider range of problems.
The discussion also touches upon the broader context of logic programming and its place in the current programming landscape. One commenter laments the relative decline in popularity of logic programming and expresses hope that projects like Clolog can help revitalize interest in this paradigm.
Overall, the comments reflect a mixture of curiosity, technical analysis, and historical perspective. They explore the project's design choices, potential applications, and its relationship to the broader field of logic programming. The commenters express interest in the project's performance, the chosen unification algorithm, and the possibility of adding constraint programming features.