TY - GEN
T1 - Metaphysics of planning domain descriptions
AU - Srivastava, Siddharth
AU - Russell, Stuart
AU - Pinto, Alessandro
N1 - Publisher Copyright:
© Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2016
Y1 - 2016
N2 - STRIPS-like languages (SLLs) have fostered immense advances in automated planning. In practice, SLLs are used to express highly abstract versions of real-world planning problems, leading to more concise models and faster solution times. Unfortunately, as we show in the paper, simple ways of abstracting solvable real-world problems may lead to SLL models that are unsolvable, SLL models whose solutions are incorrect with respect to the real-world problem, or models that are inexpressible in SLLs. There is some evidence that such limitations have restricted the applicability of AI planning technology in the real world, as is apparent in the case of task and motion planning in robotics. We show that the situation can be ameliorated by a combination of increased expressive power-for example, allowing angelic nondeterminism in action effects-And new kinds of algorithmic approaches designed to produce correct solutions from initially incorrect or non-Markovian abstract models.
AB - STRIPS-like languages (SLLs) have fostered immense advances in automated planning. In practice, SLLs are used to express highly abstract versions of real-world planning problems, leading to more concise models and faster solution times. Unfortunately, as we show in the paper, simple ways of abstracting solvable real-world problems may lead to SLL models that are unsolvable, SLL models whose solutions are incorrect with respect to the real-world problem, or models that are inexpressible in SLLs. There is some evidence that such limitations have restricted the applicability of AI planning technology in the real world, as is apparent in the case of task and motion planning in robotics. We show that the situation can be ameliorated by a combination of increased expressive power-for example, allowing angelic nondeterminism in action effects-And new kinds of algorithmic approaches designed to produce correct solutions from initially incorrect or non-Markovian abstract models.
UR - http://www.scopus.com/inward/record.url?scp=85007271172&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85007271172&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85007271172
T3 - 30th AAAI Conference on Artificial Intelligence, AAAI 2016
SP - 1074
EP - 1080
BT - 30th AAAI Conference on Artificial Intelligence, AAAI 2016
PB - AAAI press
T2 - 30th AAAI Conference on Artificial Intelligence, AAAI 2016
Y2 - 12 February 2016 through 17 February 2016
ER -