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Title:
Prospective Logic Agents
Publication date:
October 2009
Citation:
prospective-ijris09
Abstract:
Facing the possibility of modelling agent systems capable of nondeterministic self-evolution, we are confronted with the problem of having several different possible futures for any single agent. This brings the challenge of how to allow such evolving agents to be able to look ahead, prospectively, into their hypothetical futures, in order to determine best courses of evolution from their present, and thence to prefer amongst them. The concept of prospective logic programs is presented to address such issues. We build on previous theoretical background, on evolving programs and on abduction, to construe a framework for prospection and describe an abstract procedure for its materialization. We take on several examples of modelling prospective logic programs to illustrate the proposed concepts and briefly discuss the ACORDA system, an implementation of the previously presented procedure. We conclude elaborating on current limitations of the system and examining future work scenaria.
Journal
Authors:
Luís Moniz Pereira
,
Gonçalo Lopes
Journal:
International Journal of Reasoning-based Intelligent Systems (IJRIS)
Publisher:
Inderscience
Address:
http://www.inderscience.com/browse/index.php?journalCODE=ijris
Volume:
1
Number:
3/4
Pages:
200-208
ISBN:
1755-0556
ISSN:
-
Note:
-
Url address:
http://centria.di.fct.unl.pt/~lmp/publications/online-papers/ijris09-acorda.pdf
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Plain text:
Luís Moniz Pereira and Gonçalo Lopes, Prospective Logic Agents, International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 1, No. 3/4, Pag. 200-208, Inderscience, http://www.inderscience.com/browse/index.php?journalCODE=ijris, ISBN 1755-0556, (http://centria.di.fct.unl.pt/~lmp/publications/online-papers/ijris09-acorda.pdf), October 2009.
HTML:
<b><a href="/people/members/view.php?code=6175f826202ff877fba2ad77784cb9cb" class="author">Luís Moniz Pereira</a> and <a href="/people/members/view.php?code=70944c933ceb5d837aed2c1540ec2d6c" class="author">Gonçalo Lopes</a></b>, <u>Prospective Logic Agents</u>, International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 1, No. 3/4, Pag. 200-208, Inderscience, http://www.inderscience.com/browse/index.php?journalCODE=ijris, ISBN 1755-0556, (<a href="http://centria.di.fct.unl.pt/~lmp/publications/online-papers/ijris09-acorda.pdf" target="_blank">url</a>), October 2009.
BibTeX:
@article {prospective-ijris09, author = {Lu\'{\i}s Moniz Pereira and Gon\c{c}alo Lopes}, title = {Prospective Logic Agents}, journal = {International Journal of Reasoning-based Intelligent Systems (IJRIS)}, publisher = {Inderscience}, address = {http://www.inderscience.com/browse/index.php?journalCODE=ijris}, volume = {1}, number = {3/4}, pages = {200-208}, isbn = {1755-0556}, url = {http://centria.di.fct.unl.pt/~lmp/publications/online-papers/ijris09-acorda.pdf}, abstract = {Facing the possibility of modelling agent systems capable of nondeterministic self-evolution, we are confronted with the problem of having several different possible futures for any single agent. This brings the challenge of how to allow such evolving agents to be able to look ahead, prospectively, into their hypothetical futures, in order to determine best courses of evolution from their present, and thence to prefer amongst them. The concept of prospective logic programs is presented to address such issues. We build on previous theoretical background, on evolving programs and on abduction, to construe a framework for prospection and describe an abstract procedure for its materialization. We take on several examples of modelling prospective logic programs to illustrate the proposed concepts and briefly discuss the ACORDA system, an implementation of the previously presented procedure. We conclude elaborating on current limitations of the system and examining future work scenaria.}, keywords = {Evolving Agents; Future Prospection; Abduction; Preferences; Logic Programming; Abductive Stable Models; ACORDA; XSB-XASP system}, month = {October}, year = {2009}, }
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