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Every normal logic program has a 2-valued Minimal Hypotheses semantics
October 2011
MHsemEPIA
We explore a unifying approach of hypotheses assumption to provide a semantics for all Normal Logic Programs (NLP), the Minimal Hypotheses (MH) semantics. This semantics takes a positive hypotheses assumption approach to guarantee the desirable properties of model existence, relevance and cumulativity, and of generalizing the Stable Models semantics. We first introduce the semantic concept of minimality of assumed positive hypotheses, define MH semantics, and analyze its properties and applicability. Abductive Logic Programming can be captured by a strategy centered on the assumption of abducibles (or hypotheses). The Argumentation perspective of Logic Programs also lends itself to an arguments (or hypotheses) assumption approach. Previous works on Abduction have depicted the atoms of default negated literals in NLPs as abducibles, i.e., assumable hypotheses. We take a complementary and more general view than these works to NLP semantics by employing positive hypotheses instead.
In proceedings
Alexandre Miguel Pinto, Luís Moniz Pereira
Procs.15th Portuguese Intl. Conf. on Artificial Intelligence (EPIA 2011)
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Associação Portuguesa para a Inteligência Artificial
www.appia.pt
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283-297
978-989-95618-4-7
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http://centria.di.fct.unl.pt/~lmp/publications/online-papers/MH.pdf
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Alexandre Miguel Pinto and Luís Moniz Pereira, Every normal logic program has a 2-valued Minimal Hypotheses semantics, , Procs.15th Portuguese Intl. Conf. on Artificial Intelligence (EPIA 2011), Associação Portuguesa para a Inteligência Artificial, www.appia.pt, ISBN 978-989-95618-4-7, Pag. 283-297, (http://centria.di.fct.unl.pt/~lmp/publications/online-papers/MH.pdf), October 2011.
<a href="/people/members/view.php?code=76dee43781430d064f62dee3fbdf47a8" class="author">Alexandre Miguel Pinto</a> and <a href="/people/members/view.php?code=6175f826202ff877fba2ad77784cb9cb" class="author">Luís Moniz Pereira</a>, <b>Every normal logic program has a 2-valued Minimal Hypotheses semantics</b>, <u>Procs.15th Portuguese Intl. Conf. on Artificial Intelligence (EPIA 2011)</u>, <a href="http://www.appia.pt/" title="Link to external entity..." target="_blank" class="publisher">Associação Portuguesa para a Inteligência Artificial</a>, www.appia.pt, ISBN 978-989-95618-4-7, Pag. 283-297, (<a href="http://centria.di.fct.unl.pt/~lmp/publications/online-papers/MH.pdf" target="_blank">url</a>), October 2011.
@inproceedings {MHsemEPIA, author = {Alexandre Miguel Pinto and Lu\'{\i}s Moniz Pereira}, title = {Every normal logic program has a 2-valued Minimal Hypotheses semantics}, booktitle = {Procs.15th Portuguese Intl. Conf. on Artificial Intelligence (EPIA 2011)}, publisher = {Associa\c{c}{\~a}o Portuguesa para a Intelig{\^e}ncia Artificial}, address = {www.appia.pt}, pages = {283-297}, isbn = {978-989-95618-4-7}, url = {http://centria.di.fct.unl.pt/~lmp/publications/online-papers/MH.pdf}, abstract = {We explore a unifying approach of hypotheses assumption to provide a semantics for all Normal Logic Programs (NLP), the Minimal Hypotheses (MH) semantics. This semantics takes a positive hypotheses assumption approach to guarantee the desirable properties of model existence, relevance and cumulativity, and of generalizing the Stable Models semantics. We first introduce the semantic concept of minimality of assumed positive hypotheses, define MH semantics, and analyze its properties and applicability. Abductive Logic Programming can be captured by a strategy centered on the assumption of abducibles (or hypotheses). The Argumentation perspective of Logic Programs also lends itself to an arguments (or hypotheses) assumption approach. Previous works on Abduction have depicted the atoms of default negated literals in NLPs as abducibles, i.e., assumable hypotheses. We take a complementary and more general view than these works to NLP semantics by employing positive hypotheses instead.}, keywords = {Hypotheses, Semantics, NLPs, Abduction, Argumentation}, month = {October}, year = {2011}, }
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