000 03655nam a22004815i 4500
001 978-1-4020-3069-7
003 DE-He213
005 20161121230930.0
007 cr nn 008mamaa
008 100301s2005 ne | s |||| 0|eng d
020 _a9781402030697
_9978-1-4020-3069-7
024 7 _a10.1007/1-4020-3069-X
_2doi
050 4 _aB53
072 7 _aHP
_2bicssc
072 7 _aPHI021000
_2bisacsh
072 7 _aTEC000000
_2bisacsh
082 0 4 _a601
_223
100 1 _aThielscher, Michael.
_eauthor.
245 1 0 _aReasoning Robots
_h[electronic resource] :
_bThe Art and Science of Programming Robotic Agents /
_cby Michael Thielscher.
264 1 _aDordrecht :
_bSpringer Netherlands,
_c2005.
300 _aXIV, 328 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aApplied Logic Series,
_x1386-2790 ;
_v33
505 0 _aSpecial Fluent Calculus -- Special FLUX -- General Fluent Calculus -- General FLUX -- Knowledge Programming -- Planning -- Nondeterminism -- Imprecision* -- Indirect Effects: Ramification Problem* -- Troubleshooting: Qualification Problem -- Robotics.
520 _aThe book provides an in-depth and uniform treatment of a mathematical model for reasoning robotic agents. The book also contains an introduction to a programming method and system based on this model. The mathematical model, known as the "Fluent Calculus,'' describes how to use classical first-order logic to set up symbolic models of dynamic worlds and to represent knowledge of actions and their effects. Robotic agents use this knowledge and their reasoning facilities to make decisions when following high-level, long-term strategies. The book covers the issues of reasoning about sensor input, acting under incomplete knowledge and uncertainty, planning, intelligent troubleshooting, and many other topics. The mathematical model is supplemented by a programming method which allows readers to design their own reasoning robotic agents. The usage of this method, called "FLUX,'' is illustrated by many example programs. The book includes the details of an implementation of FLUX using the standard programming language PROLOG, which allows readers to re-implement or to modify and extend the generic system. The design of autonomous agents, including robots, is one of the most exciting and challenging goals of Artificial Intelligence. Reasoning robotic agents constitute a link between knowledge representation and reasoning on the one hand, and agent programming and robot control on the other. The book provides a uniform mathematical model for the problem-driven, top-down design of rational agents, which use reasoning for decision making, planning, and troubleshooting. The implementation of the mathematical model by a general PROLOG program allows readers to practice the design of reasoning robotic agents. Since all implementation details are given, the generic system can be easily modified and extended.
650 0 _aPhilosophy.
650 0 _aComputer programming.
650 0 _aArtificial intelligence.
650 1 4 _aPhilosophy.
650 2 4 _aPhilosophy of Technology.
650 2 4 _aProgramming Techniques.
650 2 4 _aArtificial Intelligence (incl. Robotics).
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781402030680
830 0 _aApplied Logic Series,
_x1386-2790 ;
_v33
856 4 0 _uhttp://dx.doi.org/10.1007/1-4020-3069-X
912 _aZDB-2-SMA
950 _aMathematics and Statistics (Springer-11649)
999 _c506070
_d506070