The complexity and generality of learning answer set programs

Inductive Learning of Answer Set Programs

Generality Relations in Answer Set Programming

This paper studies generality relations on logic programs. Intuitively, a program P1 is more general than another program P2 if P1 gives us more information than P2. In this paper, we define various kinds of generality relations over nonmonotonic programs in the context of answer set programming. The semantic properties of generality relations are investigated based on domain theory, and both a...

the effect of task complexity on lexical complexity and grammatical accuracy of efl learners’ argumentative writing

بر اساس فرضیه شناخت رابینسون (2001 و 2003 و 2005) و مدل ظرفیت توجه محدود اسکهان (1998)، این تحقیق تاثیر پیچیدگی تکلیف را بر پیچیدگی واژگان و صحت گرامری نوشتار مباحثه ای 60 نفر از دانشجویان زبان انگلیسی بررسی کرد. میزان پیچیدگی تکلیف از طریق فاکتورهای پراکندگی-منابع تعیین شد. همه ی شرکت کنندگان به صورت نیمه تصادفی به یکی از سه گروه: (1) گروه موضوع، (2) گروه موضوع + اندیشه و (3) گروه موضوع + اندی...

Communicating Answer Set Programs

Answer set programming is a form of declarative programming that has proven very successful in succinctly formulating and solving complex problems. Although mechanisms for representing and reasoning with the combined answer set programs of multiple agents have already been proposed, the actual gain in expressivity when adding communication has not been thoroughly studied. We show that allowing ...

Iterative Learning of Answer Set Programs from Context Dependent Examples

In recent years, several frameworks and systems have been proposed that extend Inductive Logic Programming (ILP) to the Answer Set Programming (ASP) paradigm. In ILP, examples must all be explained by a hypothesis together with a given background knowledge. In existing systems, the background knowledge is the same for all examples; however, examples may be context-dependent. This means that som...