The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
The Cambridge Handbook of Artificial Intelligence
Open accessAbstract
Artificial intelligence, or AI, is a cross-disciplinary approach to understanding, modeling, and creating intelligence of various forms. It is a critical branch of cognitive science, and its influence is increasingly being felt in other areas, including the humanities. AI applications are transforming the way we interact with each other and with our environment, and work in artificially modeling intelligence is offering new insights into the human mind and revealing new forms mentality can take. This volume of original essays presents the state of the art in AI, surveying the foundations of the discipline, major theories of mental architecture, the principal areas of research, and extensions of AI such as artificial life. With a focus on theory rather than technical and applied issues, the volume will be valuable not only to people working in AI, but also to those in other disciplines wanting an authoritative and up-to-date introduction to the field.
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Citations
Cites
Reinforcement Learning: A Survey
Kaelbling, L. P., Littman, M. L., & Moore, A. W. (1996) · Journal of Artificial Intelligence Research · doi:10.1613/jair.301 · Cited by 8,972
A robust layered control system for a mobile robot
Brooks, R. (1986) · IEEE Journal on Robotics and Automation · doi:10.1109/jra.1986.1087032 · Cited by 7,799
STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving
Fikes, R. E., & Nilsson, N. J. (1971) · Artificial Intelligence · doi:10.1016/0004-3702(71)90010-5 · Cited by 4,882
Multiagent systems: A survey from a machine learning perspective
Stone, P., & Veloso, M. (2000) · Autonomous Robots · doi:10.1023/a:1008942012299 · Cited by 1,218
Cited by
Ray, P. P. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.04.003 · Cited by 2,463
Global evolution of research in artificial intelligence in health and medicine: a bibliometric study
Tran, B. X., Vu, G. T., Ha, G. H., Vuong, Q.-H., Ho, M.-T., Vuong, T.-T., La, V.-P., Ho, M.-T., Nghiem, K.-C. P., Nguyen, H. L. T., et al. (2019) · Journal of Clinical Medicine · doi:10.3390/jcm8030360 · Cited by 472
Ethical framework for Artificial Intelligence and Digital technologies
Ashok, M., Madan, R., Joha, A., & Sivarajah, U. (2022) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2021.102433 · Cited by 469
Ethical Decision Making during Automated Vehicle Crashes
Goodall, N. J. (2014) · Transportation Research Record: Journal of the Transportation Research Board · doi:10.3141/2424-07 · Cited by 292
Advertising benefits from ethical Artificial Intelligence algorithmic purchase decision pathways
Rodgers, W., & Nguyen, T. (2022) · Journal of Business Ethics · doi:10.1007/s10551-022-05048-7 · Cited by 137
Metadata
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2014-06-12
- OpenAlex
- W3162616674
- Cited by
- 267
- References
- 4
- FWCI
- 1.90
- Type
- book
- Language
- en
- Open access
- green
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Data sources
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.