Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Deepak Khemani"'
Publikováno v:
Logic and Its Applications ISBN: 9783031266881
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ac8932d65db7f5267643e27ef5597ce
https://doi.org/10.1007/978-3-031-26689-8_4
https://doi.org/10.1007/978-3-031-26689-8_4
Autor:
Deepak Khemani
Publikováno v:
Resonance. 25:33-41
Autor:
Shikha Singh, Deepak Khemani
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 35:15893-15894
The ability of an agent to distinguish the ramification effects of an action from its direct effects adds value to the explainability of its decisions. In this work, we propose to encode the ramification effects of ontic and epistemic actions as sing
Autor:
Baskaran Sankaranarayanan, Deepak Khemani, P. Sreenivasa Kuma, Nestor Rychtyckyj, Venkatesh Raman
Publikováno v:
AI Magazine; Vol 38, No 1: Spring 2017; 49-60
For over twenty-five years Ford Motor Company has been utilizing an AI-based system to manage process planning for vehicle assembly at its assembly plants around the world. The scope of the AI system, known originally as the Direct Labor Management S
Publikováno v:
Proceedings of the Advances in Robotics 2019.
This paper presents use of a cost graph as a representation of a multi-floor building to enable the multi-floor autonomous navigation capability for a team of robot(s). A method for global path planning on this cost graph have been presented. A navig
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 32
Regular expressions are an important building block of rule-based information extraction systems. Regexes can encode rules to recognize instances of simple entities which can then feed into the identification of more complex cross-entity relationship
Autor:
Deepak Khemani, Shashank Shekhar
Publikováno v:
KI 2015: Advances in Artificial Intelligence ISBN: 9783319244884
KI
KI
The design of domain independent heuristic functions often brings up experimental evidence that different heuristics perform well in different domains. A promising approach is to monitor and reduce the error associated with a given heuristic function
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cae824c4ae3ab543dc2b994f59b4f686
https://doi.org/10.1007/978-3-319-24489-1_27
https://doi.org/10.1007/978-3-319-24489-1_27
Publikováno v:
Mining Intelligence and Knowledge Exploration ISBN: 9783319268316
MIKE
MIKE
Search and recommender systems benefit from effective integration of two different kinds of knowledge. The first is introspective knowledge, typically available in feature-theoretic representations of objects. The second is external knowledge, which
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3b307c8cea2e5ee00c9c0bee6d69203
https://doi.org/10.1007/978-3-319-26832-3_1
https://doi.org/10.1007/978-3-319-26832-3_1
Autor:
Deepak Khemani, Shashank Shekhar
Publikováno v:
Mining Intelligence and Knowledge Exploration ISBN: 9783319268316
MIKE
MIKE
Recent literature reveals that different heuristic functions perform well in different domains due to the varying nature of planning problems. This nature is characterized by the degree of interaction between subgoals and actions. We take the approac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6214825cb74d3b7e957e36beadcc1c2d
https://doi.org/10.1007/978-3-319-26832-3_9
https://doi.org/10.1007/978-3-319-26832-3_9
Publikováno v:
IndraStra Global.
This paper presents a survey of Simultaneous Localization And Mapping (SLAM) algorithms for unmanned ground robots. SLAM is the process of creating a map of the environment, sometimes unknown a priori, while at the same time localizing the robot in t