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Springer Handbook of Automation pp 249–268Cite as

Artificial Intelligence and Automation

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Abstract

Artificial intelligence (AI) focuses on getting machines to do things that we would call intelligent behavior. Intelligence – whether artificial or otherwise – does not have a precise definition, but there are many activities and behaviors that are considered intelligent when exhibited by humans and animals. Examples include seeing, learning, using tools, understanding human speech, reasoning, making good guesses, playing games, and formulating plans and objectives. AI focuses on how to get machines or computers to perform these same kinds of activities, though not necessarily in the same way that humans or animals might do them.

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Abbreviations

AI:

artificial intelligence

CFG:

context-free grammar

CP:

constraint programming

CP:

coordination protocol

DNA:

deoxyribonucleic acid

EDA:

electronic design automation

HMM:

hidden Markov model

HTN:

hierarchical task network

MDP:

Markov decision process

NASA:

National Aeronautics and Space Administration

NLP:

natural-language processing

NP:

nominal performance

NP:

nondeterministic polynomial-time

OWL:

web ontology language

PCFG:

probabilistic context-free grammar

PDDL:

planning domain definition language

PDF:

probability distribution function

Prolog:

programming in logics

RTDP:

real-time dynamic programming

TALplanner:

temporal action logic planner

TLPlan:

temporal logic planner

UAV:

unmanned aerial vehicle

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Authors and Affiliations

  1. Department of Computer Science, University of Maryland, A.V. Williams Bldg., 20742, College Park, MD, USA

    Dana S. Nau Dr

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  1. Dana S. Nau Dr
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Correspondence to Dana S. Nau Dr .

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  1. PRISM Center, and School of Industrial Engineering, Purdue University, 315 N. Grant Street, 47907, West Lafayette, IN, USA

    Shimon Y. Nof

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Nau, D.S. (2009). Artificial Intelligence and Automation. In: Nof, S. (eds) Springer Handbook of Automation. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78831-7_14

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  • DOI: https://doi.org/10.1007/978-3-540-78831-7_14

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