Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Kenneth Forbus"'
Autor:
Joseph Blass, Kenneth Forbus
Publikováno v:
Frontiers in Artificial Intelligence and Applications ISBN: 9781643683645
We introduce the Illinois Intentional Tort Qualitative Dataset, a set of Illinois Common Law cases in Assault, Battery, Trespass, and Self-Defense, machine-translated into qualitative predicate representations. We discuss the cases involved, the natu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2988485bd43a228de8b5ac7ee6a76e52
https://doi.org/10.3233/faia220459
https://doi.org/10.3233/faia220459
Autor:
Kenneth Forbus, Sven Kuehne
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 3:80-83
A major limitation of today's computer games is the shallowness of interactions with non-player characters. To build up relationships with players, NPCs should be able to remember shared experiences, including conversations, and shape their responses
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::00bfe87603d5c1d8da1f76c944f87123
https://doi.org/10.1609/aiide.v3i1.18790
https://doi.org/10.1609/aiide.v3i1.18790
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 1:45-50
Today's military strategy games provide unrealistic interfaces for players to interact with their units: Commanders don't use mice and menus, they sketch. Developing strategy games currently involves grafting AI capabilities on top of a separate simu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55ad12265166d22bcfd60641e8ee4168
https://doi.org/10.1609/aiide.v1i1.18714
https://doi.org/10.1609/aiide.v1i1.18714
Autor:
Abhishek Sharma, Kenneth Forbus
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 26:669-675
How do reasoning systems that learn evolve over time? What are the properties of different learning strategies? Characterizing the evolution of these systems is important for understanding their limitations and gaining insights into the interplay bet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5f715bfb389f9fd53f9102664cb561d
https://doi.org/10.1609/aaai.v26i1.8200
https://doi.org/10.1609/aaai.v26i1.8200
Autor:
Thomas Hinrichs, Kenneth Forbus
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 26:207-213
Creating software agents that learn interactively requires the ability to learn from a small number of trials, extracting general, flexible knowledge that can drive behavior from observation and interaction. We claim that qualitative models provide a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::34c9d710d8dfdd43770994077f20f562
https://doi.org/10.1609/aaai.v26i1.8153
https://doi.org/10.1609/aaai.v26i1.8153
Autor:
Kezhen Chen, Qiuyuan Huang, Daniel McDuff, Xiang Gao, Hamid Palangi, Jianfeng Wang, Kenneth Forbus, Jianfeng Gao
Publikováno v:
Findings of the Association for Computational Linguistics: EMNLP 2021.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::26e85637b019e9f62774a4382a37294d
https://doi.org/10.18653/v1/2021.findings-emnlp.380
https://doi.org/10.18653/v1/2021.findings-emnlp.380
Action Recognition From Skeleton Data via Analogical Generalization Over Qualitative Representations
Autor:
Kezhen Chen, Kenneth Forbus
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 32
Human action recognition remains a difficult problem for AI. Traditional machine learning techniques can have high recognition accuracy, but they are typically black boxes whose internal models are not inspectable and whose results are not explainabl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::29120b99768dc3ee88c581dc78519899
https://doi.org/10.1609/aaai.v32i1.11328
https://doi.org/10.1609/aaai.v32i1.11328
Autor:
Joseph Blass, Kenneth Forbus
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 31
Understanding commonsense reasoning is one of the core challenges of AI. We are exploring an approach inspired by cognitive science, called analogical chaining, to create cognitive systems that can perform commonsense reasoning. Just as rules are cha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef825931c9a4f57270dccb6dd77be224
https://doi.org/10.1609/aaai.v31i1.11153
https://doi.org/10.1609/aaai.v31i1.11153
Autor:
Maria Chang, Kenneth Forbus
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 27:1507-1512
One of the major challenges to building intelligent educational software is determining what kinds of feedback to give learners. Useful feedback makes use of models of domain-specific knowledge, especially models that are commonly held by potential s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6f0f00e1800e274a9bc9b993e8cb9c52
https://doi.org/10.1609/aaai.v27i2.18991
https://doi.org/10.1609/aaai.v27i2.18991