TY - GEN
T1 - Information Shaping for Enhanced Goal Recognition of Partially-Informed Agents
AU - Keren, Sarah
AU - Xu, Haifeng
AU - Kwapong, Kofi
AU - Parkes, David
AU - Grosz, Barbara
N1 - Publisher Copyright: Copyright c 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2020
Y1 - 2020
N2 - We extend goal recognition design to account for partially informed agents. In particular, we consider a two-Agent setting in which one agent, the actor, seeks to achieve a goal but has only incomplete information about the environment. The second agent, the recognizer, has perfect information and aims to recognize the actor s goal from its behavior as quickly as possible. As a one-Time offline intervention and with the objective of facilitating the recognition task, the recognizer can selectively reveal information to the actor. The problem of selecting which information to reveal, which we call information shaping, is challenging not only because the space of information shaping options may be large, but also because more information revelation need not make it easier to recognize an agent s goal. We formally define this problem, and suggest a pruning approach for efficiently searching the search space.We demonstrate the effectiveness and efficiency of the suggested method on standard benchmarks.
AB - We extend goal recognition design to account for partially informed agents. In particular, we consider a two-Agent setting in which one agent, the actor, seeks to achieve a goal but has only incomplete information about the environment. The second agent, the recognizer, has perfect information and aims to recognize the actor s goal from its behavior as quickly as possible. As a one-Time offline intervention and with the objective of facilitating the recognition task, the recognizer can selectively reveal information to the actor. The problem of selecting which information to reveal, which we call information shaping, is challenging not only because the space of information shaping options may be large, but also because more information revelation need not make it easier to recognize an agent s goal. We formally define this problem, and suggest a pruning approach for efficiently searching the search space.We demonstrate the effectiveness and efficiency of the suggested method on standard benchmarks.
UR - http://www.scopus.com/inward/record.url?scp=85097350691&partnerID=8YFLogxK
M3 - منشور من مؤتمر
T3 - AAAI 2020 - 34th AAAI Conference on Artificial Intelligence
SP - 9908
EP - 9915
BT - AAAI 2020 - 34th AAAI Conference on Artificial Intelligence
T2 - 34th AAAI Conference on Artificial Intelligence, AAAI 2020
Y2 - 7 February 2020 through 12 February 2020
ER -