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Artificial Intelligence and Automation

  • Dana S. NauEmail author
Part of the Springer Handbooks book series (SHB)

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.

Keywords

Markov Decision Process Parking Space Classical Planning Nonterminal Symbol Bayesian Reasoning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of MarylandCollege ParkUSA

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