Discrete event modeling and simulation technologies: a tapestry of systems and AI-based theories and methodologies ; a tribute to the 60th birthday of Bernard P. Zeigler
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| Format: | Book |
|---|---|
| Language: | English |
| Published: |
New York [u.a.]
Springer
2001
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XXIX, 397 S. graph. Darst. : 24 cm |
| ISBN: | 0387950656 |
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| 245 | 1 | 0 | |a Discrete event modeling and simulation technologies |b a tapestry of systems and AI-based theories and methodologies ; a tribute to the 60th birthday of Bernard P. Zeigler |c Hessam S. Sarjoughian ... (ed.) |
| 264 | 1 | |a New York [u.a.] |b Springer |c 2001 | |
| 300 | |a XXIX, 397 S. |b graph. Darst. : 24 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 600 | 1 | 4 | |a Zeigler, Bernard P. <1940-> |
| 650 | 7 | |a Discrete gebeurtenissen |2 gtt | |
| 650 | 7 | |a Kunstmatige intelligentie |2 gtt | |
| 650 | 4 | |a Modèles mathématiques - Congrès | |
| 650 | 7 | |a Numerieke wiskunde |2 gtt | |
| 650 | 7 | |a Simulatie |2 gtt | |
| 650 | 4 | |a Simulation par ordinateur - Congrès | |
| 650 | 4 | |a Mathematisches Modell | |
| 650 | 4 | |a Computer simulation |v Congresses | |
| 650 | 4 | |a Mathematical models |v Congresses | |
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| 650 | 0 | 7 | |a Diskretes Ereignissystem |0 (DE-588)4196828-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Computersimulation |0 (DE-588)4148259-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Systemtheorie |0 (DE-588)4058812-9 |2 gnd |9 rswk-swf |
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| 700 | 1 | |a Sarjoughian, Hessam S. |e Sonstige |4 oth | |
| 700 | 1 | |a Zeigler, Bernard P. |4 hnr | |
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Record in the Search Index
| _version_ | 1816444448302694400 |
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| adam_text |
CONTENTS
FOREWORD
.
V
PREFACE
.
IX
CONTRIBUTORS
.
.
.
XI
LIST
OF
FIGURES
.
XXV
LIST
OF
TABLES
.
XXXI
1.
TOWARD
A
UNIFIED
FOUNDATION
SIMULATION-BASED
ACQUISITION
_
1
H.S.
SARJOUGHIAN
AND
F.E.
CELLIER
1.1
INTRODUCTION
.
1
1.2
AI,
M&S,
AND
SE:
A
UNIFIED
PERSPECTIVE
.
3
1.2.1
DISCRETE-EVENT
WORLDVIEW
AND
DISTRIBUTED
COMPUTATION
.
5
1.2.2
A
BRIEF
ACCOUNT
OF
ARTIFICIAL
INTELLIGENCE
AND
SOFTWARE
ENGINEERING
.
6
1.2.3
INTEROPERABILITY,
COMPOSABILITY,
AND
DISTRIBUTED
COMPUTING
.
7
1.2.4
CONTINUOUS
AND
DISCRETE-EVENT
MODELING
AND
SIMULATION
.
8
1.3
SIMULATION
BASED
ACQUISITION
.
9
1.4
CONCLUSIONS
.
12
REFERENCES
.
12
2.
WHY
ENGINEERING
MODELS
DO
NOT
HAVE
A
FRAME
PROBLEM
.
15
N.
FOO
2.1
THE
FRAME
PROBLEM
.
15
2.2
MODELS
IN
ENGINEERING
.
16
2.3
MODELS
IN
AI
.
19
2.3.1
PREDICTION,
ABDUCTION
AND
INTERPOLATION
.
20
2.3.2
INERTIA
.
21
2.3.3
PARALLELS
.
23
2.4
SO,
DO
WE
NEED
FRAME
AXIOMS?
.
24
2.5
FUTURE
DIRECTIONS
AND
CONCLUSION
.
25
ACKNOWLEDGEMENTS
.
25
REFERENCES
.
26
3.
ADAPTIVE
DESIGNS
FOR
MULTIRESOLUTION,
MULTIPERSPECTIVE
MODELING
(MRMPM)
.
27
P.K.
DAVIS
3.1
INTRODUCTION
.
27
3.1.1
PREFACING
COMMENTS
.
27
3.1.2
OBJECTIVE
.
28
XVI
CONTENTS
3.2
BACKGROUND
.
28
3.2.1
DEFINITIONS
.
28
3.2.2
MOTIVATIONS
.
29
3.2.3
FEASIBILITY
OF
MRM
AND
MRMPM
.
29
3.2.3.1
THE
IDEAL
.
29
3.2.3.2
THE
REALITY
.
30
3.2.4
THE
CHALLENGE:
ENABLING
THE
IDEAL
.
30
3.3
UNDERSTANDING
THE
PROBLEM
WITH
A
PARABLE
.
31
3.3.1
ILLUSTRATIVE
PROBLEM
.
31
3.3.2
A
PARABLE
BEGINS:
BOSS
'
S
IMAGE
OF
A
SOLUTION
.
31
3.3.3
THE
SECOND
ACT
.
34
3.3.4
THE
APPARENT
CONCLUSION
-
PERHAPS
UNSATISFACTORY
.
35
3.3.5
OBSERVATIONS
.
35
3.4
INTERLUDE
FOR
KEY
PRINCIPLES
.
35
3.4.1
NEED
FOR
HIERARCHICAL
TREES
.
35
3.4.2
NEED
TO
ACCOUNT
FOR
BRANCHES
.
36
3.4.3
APPROXIMATIONS
ARE
FINE
BUT
MUST
BE
CONTEXT
DEPENDENT
.
38
3.4.4
THE
ISSUE
OF
CONSISTENCY
.
38
3.5
MILKING
OUR
EXAMPLE
FOR
MORE
INSIGHTS
.
40
3.5.1
A
FIRST
SIMPLIFICATION
.
40
3.5.2
AN
ALTERNATIVE
PERSPECTIVE
OF
THE
SAME
PROBLEM
.
42
3.5.3
THE
EQUIVALENT-PROGRAMMER
APPROXIMATION
.
44
3.6
INFERENCES
AND
CONCLUSIONS
.
48
3.6.1
WHAT
WE
NOW
UNDERSTAND
BETTER
.
48
3.6.2
THE
ROLE
OF
THE
MODELING
ENVIRONMENT
.
49
3.6.3
OPPORTUNITIES
FOR
THE
FUTURE
.
50
REFERENCES
.
51
4.
THE
ROLE
OF
UNCERTAINTY
IN
SYSTEMS
MODELING
.
53
G.J.
KIIR
4.1
INTRODUCTION
.
53
4.2
GENERALIZED
INFORMATION
THEORY
.
54
4.3
NEW
UNCERTAINTY
THEORIES:
RELEVANT
CONCEPTS
AND
NOTATION
.
55
4.3.1
DEMPSTER-SHAFER
THEORY
(DST)
.
56
4.3.2
GENERALIZED
POSSIBILITY
THEORY
(GPT)
.
59
4.4
UNCERTAINTY
MEASURES:
KEY
REQUIREMENTS
.
61
4.5
UNCERTAINTY
MEASURES
IN
DST
AND
GPT
.
62
4.5.1
NONSPECIFICITY
.
62
4.5.2 ENTROPY-LIKE
UNCERTAINTY
.
64
4.5.3
AGGREGATE
UNCERTAINTY
.
65
4.6
PRINCIPLES
OF
UNCERTAINTY
.
65
CONTENTS
XVII
4.6.1
PRINCIPLE
OF
MINIMUM
UNCERTAINTY
.
66
4.6.2
PRINCIPLE
OF
MAXIMUM
UNCERTAINTY
.
67
4.6.3
PRINCIPLE
OF
UNCERTAINTY
INVARIANCE
.
68
4.7
OPEN
PROBLEMS
AND
UNDEVELOPED
AREAS
.
70
4.8
CONCLUSIONS
.
72
REFERENCES
.
72
5.
LINGUISTIC
DYNAMIC
SYSTEMS
AND
COMPUTING
WITH
WORDS
FOR
MODELING,
SIMULATION,
AND
ANALYSIS
OF
COMPLEX
SYSTEMS
_
75
F.
WANG,
Y.
LIN,
AND
J.B.
PU
5.1
INTRODUCTION
.
75
5.2
FUZZY
SETS
AS
POINTS
.
;
.
79
5.3
FORMULATION
OF
LINGUISTIC
DYNAMIC
SYSTEMS
.
80
5.4
STABILITY
DEFINITIONS
OF
LINGUISTIC
DYNAMIC
SYSTEMS
.
82
5.5
CELL
SPACES
ON
FUZZY
HYPERCUBES
.
85
5.6
ANALYSIS
OF
LDS
USING
CELL-TO-CELL
MAPPINGS
.
87
5.7
DESIGN
OF
OPTIMAL
CONTROL
IN
CELL
SPACES
.
89
5.8
CONCLUSIONS
.
91
REFERENCES
.
91
6.
TOWARDS
A
MODELING
FORMALISM
FOR
CONFLICT
MANAGEMENT
.
93
T.I.
OREN
6.1
INTRODUCTION
.
93
6.2
TOWARDS
A
MODELING
FORMALISM
AND
AN
ASSOCIATED
SIMULATION
FORMALISM
.
95
6.2.1
BACKGROUND
FOR
MULTISTAGE
MODELING
FORMALISM
.
96
6.2.1.1
MULTIMODELS
.
97
6.2.1.2
SPECIAL
CASES
OF
MULTIMODELS
.
98
6.2.1.3
EVOLUTIONARY
MODELS
.
98
6.2.2
MULTISTAGE
MODELS
AND
MULTISIMULATION
.
98
6.2.3
STATEMACHINES
.
99
6.2.4
MULTISTAGE
STATE
MACHINES
.
100
6.2.5
SOME
OTHER
MULTISTAGE
MODELING
FORMALISMS
.
102
6.3
CONCLUSION
AND
CHALLENGES
.
102
ACKNOWLEDGEMENTS
.
103
REFERENCES
.
103
7.
SYSTEMS
DESIGN:
A
SIMULATION
MODELING
FRAMEWORK
.
107
J.W.
ROZENBLIT
7.1
INTRODUCTION
AND
MOTIVATION
.
107
7.1.1
SYSTEM
DESIGN
AND
MODELING:
SYNERGIES
.
109
7.2
THE
MDB
METHODOLOGY
.
110
7.3
MBD
PROCESS
ELEMENTS
.
ILL
7.3.1
SYSTEM
SPECIFICATIONS
.
ILL
XVIII
CONTENTS
7.3.2
MODELING
.
HL
7.3.2.1
OBJECT
MODELING
.
112
7.3.2.2
PRUNING
.
116
7.3.2.3
BEHAVIORAL
MODEL
SPECIFICATION
.
119
7.3.3
SIMULATION
.
120
7.3.4
EXPERIMENTAL
FRAME
CPUS
UTILIZATION
.
123
7.3.4.1
GENERATOR
.
123
7.3.4.2
TRANSDUCER
.
123
7.3.4.3
ACCEPTOR
.
123
7.3.5
DESIGN
MODIFICATIONS
AND
REFINEMENT
.
123
7.3.6
PARTITIONING
AND
TECHNOLOGY
ASSIGNMENT
.
124
7.4
TOWARDS
AN
INTEGRATED
DESIGN
SUPPORT
ENVIRONMENT
.
126
7.5
SUMMARY
.
127
ACKNOWLEDGEMENTS
.
127
REFERENCES
.
127
DEVS
FRAMEWORK
FOR
SYSTEMS
DEVELOPMENT:
UNIFIED
SPECIFICATION
FOR
LOGICAL
ANALYSIS,
PERFORMANCE
EVALUATION
AND
IMPLEMENTATION
.
131
T.G.
KIM,
S.M.
CHO,
AND
W.B.
LEE
8.1
INTRODUCTION
.
131
8.2
EXTENDED
DEVS
FORMALISMS
.
134
8.2.1
DEVS
FORMALISM
.
134
8.2.2
COMMUNICATING
DEVS(C-DEVS)
FORMALISM
.
135
8.2.3
REAL-TIME
DEVS
(RT-DEVS)
FORMALISM
.
137
8.3
LOGICAL
ANALYSIS:
VERIFICATION
.
138
8.3.1
VERIFICATION
FRAMEWORK
.
138
8.3.2
COMPOSITIONAL
VERIFICATION
.
138
8.3.2.1
COMPOSITION
.
140
8.3.2.2
MINIMIZATION
.
142
8.4
PERFORMANCE
EVALUATION
.
143
8.5
IMPLEMENTATION:
REAL-TIME
SIMULATION
.
146
8.5.1
METHODOLOGY
OVERVIEW
.
146
8.5.2
EVENT
DRIVEN
SCHEDULING
.
147
8.5.3
SCHEDULING
FEASIBILITY
.
148
8.5.4
REAL-TIME
SIMULATION
ENVIRONMENT
.
151
8.5.5
REAL-TIME
SIMULATOR
ALGORITHMS
.
152
8.6
EXAMPLE:
LOGICAL
ANALYSIS
AND
IMPLEMENTATION
.
154
8.6.1
SYSTEM
DESCRIPTION
.
155
8.6.2
COMPOSITIONAL
VERIFICATION:
LOGICAL
ANALYSIS
.
155
8.6.2.1
OPERATIONAL
C-DEVS
MODELING
.
155
8.6.2.2
ASSERTIONAL
C-DEVS
MODELING
.
157
8.6.2.3
INCREMENTAL
COMPOSITION
AND
MINIMIZATION
.
158
CONTENTS
XIX
8.6.2.4
CONFORMATION
CHECKING
.
161
8.6.3
IMPLEMENTATION
.
161
8.6.3.1
SCHEDULING
FEASIBILITY
ANALYSIS
.
161
8.6.3.2
REAL-TIME
EXECUTION
AND
RESULT
.
161
8.7
CONCLUSIONS
.
164
REFERENCES
.
165
9.
REPRESENTATION
OF
DYNAMIC
STRUCTURE
DISCRETE
EVENT
MODELS:
A
SYSTEMS
THEORY
APPROACH
.
167
F.J.
BARROS
9.1
INTRODUCTION
.
167
9.2
DISCRETE
EVENT
SYSTEM
SPECIFICATION
.
168
9.3
STRUCTURED
DISCRETE
EVENT
SYSTEM
SPECIFICATION
(SDEVS)
.
170
9.4 DYNAMIC
STRUCTURE
DISCRETE
EVENT
SYSTEM
SPECIFICATION
.
172
9.5
SIMULTANEOUS
EVENTS
.
178
9.6
ABSTRACT
SIMULATORS
.
179
9.6.1
THE
SYNCHRONIZER.
.
179
9.6.2
THE
SIMULATOR
.
180
9.6.3
THE
NETWORKSIMULATOR
.
181
9.7
CONCLUSIONS
.
184
ACKNOWLEDGEMENTS
.
184
REFERENCES
.
184
10.
TIMED
CELL-DEVS:
MODELING
AND
SIMULATION
OF
CELL
SPACES.
187
G.
WAINER
AND
N.
GIAMBIASI
10.1
INTRODUCTION
.
187
10.2
TIMED
CELL-DEVS
ATOMIC
MODELS
.
189
10.3
COUPLED
CELL-DEVS
.
193
10.4
IMPLEMENTATION
MODELS
FOR
DEVS-CELLS
.
196
10.4.1
DEFINITION
OF
CELL-DEVS
IMPLEMENTATION
MODELS
.
196
10.4.2
IMPLEMENTATION
OF
A
CELL-DEVS
SIMULATION
FRAMEWORK
.
198
10.4.2.1
BASIC
STRUCTURE
OF
THE
TOOL
.
198
10.4.2.2
CD++
MESSAGE
INTERACTION
.
200
10.4.2.3
SUPPORT
FOR
N-DIMENSIONAL
MODELS
.
201
10.4.2.4
FLAT
SIMULATION
OF
THE
CELL
SPACES
.
201
10.5
DEVELOPMENT
EXPERIENCES
WITH
CELLULAR
MODELS
.
203
10.6
PRESENT
WORK
.
209
10.6.1
PARALLEL
CELL-DEVS
.
209
10.6.2
EXTENSIONS
TO
THE
CELL
'
S
SPECIFICATION
LANGUAGE
.
210
10.6.3
APPLICATIONS
.
210
10.7
CONCLUSIONS
.
212
XX
CONTENTS
ACKNOWLEDGEMENTS
.
212
REFERENCES
.
213
11.
DEVS-BASED
MODELING
AND
SIMULATION
FOR
INTELLIGENT
TRANSPORTATION
SYSTEMS
.
215
S-D.
CHI
AND
J-K.
LEE
11.1
INTRODUCTION
.
215
11.2
BACKGROUND
ON
TRAFFIC
SIMULATION
SYSTEMS
.
216
11.3
DESIGN
METHODOLOGY
FOR
ITS
SIMULATION
.
217
11.3.1
LAYER
I:
HIERARCHICAL,
MODULAR
AND
DISTRIBUTED
MODELING
&
SIMULATION
ENVIRONMENT
.
218
11.3.2
LAYER
II:
MODEL
ABSTRACTION
.
219
11.3.3
LAYER
III:
MICROSCOPIC
AND
MACROSCOPIC
TRAFFIC
MODELING
.
219
11.3.3.1
MICROSCOPIC
TRAFFIC
MODELING
.
219
11.3.3.2
MACROSCOPIC
TRAFFIC
MODELING
.
221
11.3.3.3
LAYER
IV
:
ITS
SIMULATION
SYSTEM
.
221
11.4
CASE
STUDY:
I3D2
TRANSPORTATION
SIMULATION
SYSTEM
.
222
11.5
CONCLUSIONS
.
225
ACKNOWLEDGMENTS
.
226
REFERENCES
.
226
12.
DYNAMIC
NEURONAL
ENSEMBLES:
NEUROBIOLOGICALLY
INSPIRED
DISCRETE
EVENT
NEURAL
NETWORKS
------
--
.
-------------
.
229
S.
VAHIE
12.1
INTRODUCTION.
229
12.1.1
TERMS
&
DEFINITIONS
.
230
12.1.2
OBJECTIVE
OF
THE
CHAPTER
.
231
12.1.3
STRUCTURE
OF
THE
PRESENTATION
.
231
12.2
BACKGROUND
.
232
12.2.1
HISTORY
OF
NEURAL
NETWORKS
.
232
12.2.2
RESURGENCE
IN
ANNS
.
233
12.3
REQUIREMENTS
FOR
DYNAMIC
NEURON
ENSEMBLES
.
234
12.3.1
EMBEDDING
KNOWLEDGE
(DOMAIN
DEPENDENT
DESIGN)
.
234
12.3.2
IMPLEMENTING
HEBBIAN
LEARNING
.
236
12.3.3
LIMITATIONS
OF
DIFFERENTIAL
EQUATION/ADVANTAGES
OF
DISCRETE
EVENT
MODELS
.
238
12.3.4
REAL-TIME
EXECUTION
AND
LEARNING
.
239
12.4
DYNAMIC
NEURONAL
ENSEMBLES
.
241
12.4.1
THE
DYNAMIC
NEURON
.
241
12.4.2
ENSEMBLES
OF
DYNAMIC
NEURONS
.
249
12.5
EXAMPLE:
A
DNE
MODEL
TO
DISTINGUISH
THREATS
FROM
ANNOYANCES
IN
THE
ENVIRONMENT
.
249
12.5.1
THE
GILL-WITHDRAWAL
REFLEX
OF
THE
APLYSIA
.
250
CONTENTS
XXI
12.5.2
DNE
MODEL
OF
APLYSIA
.
250
12.5.3
RESPONSE
OF
DNE
MODEL
TO
MILD
STIMULI
.
251
12.5.4
RESPONSE
OF
DNE
MODEL
TO
STRONG
STIMULI
.
252
12.5.5
RESULTS
OF
DNE
APLYSIA
MODELING
.
254
12.6
DNE
CONTROL
APPLICATION:
DYNAMIC
CONTROL
IN
A
CHEMICAL
PLANT
.
255
12.7
CONCLUSIONS
AND
FUTURE
WORK
.
259
12.7.1
DYNAMIC
NEURONAL
ENSEMBLES:
COMPLEMENTING
CURRENT
ANNS
.
259
12.7.2
HOW
DNES
EXPLOIT
THE
DEVS
FORMALISM
AND
OBJECT-ORIENTATION
.
259
12.7.3
RELATION
TO
OTHER
DISCRETE
EVENT
BIOLOGICALLY
RELEVANT
NEURON
MODELS
.
260
ACKNOWLEDGEMENTS
.
261
REFERENCES
.
261
13.
SIMULATION
FOR
MEANING
GENERATION:
MULTISCALE
COALITIONS
OF
AUTONOMOUS
AGENTS
.
263
A.M.
MEYSTEL
13.1
GLOBAL
SEMIOTICS
OF
VIRTUAL
AGENTS:
SIMULATING
COMPLEX
SYSTEMS
.
263
13.2
THE
WORLDS
ARE
MULTIMODAL
.
266
13.3
THE
WORLD
IS
MEANINGFUL
IF
THE
PROPERTY
OF
CLOSURE
HOLDS
.
266
13.4
THE
MEANING
IS
MULTIRESOLUTIONAL!
.
269
13.5
MEANING
IN
BIOPHYSICS
IS
CONVEYED
VIA
SEMIOTIC
AGENTS
.
273
13.6
THE
INNER
MEANING
OF
SEMIOTIC
AGENTS
.
274
13.7
THE
MEANING
OF
KNOWLEDGE
REPRESENTATION
REGULATED
BY
MAXWELL
DEMONS
.
278
13.8
GENERALIZATION
BY
COARSENING
PRODUCED
BY
GFS-TRIPLET
.
281
13.9
PROPAGATION
OF
MEANING
RUN
BY
SYMBOLS
O
AGENTS
.
283
13.10
EMERGENCE
OF
THE
MULTISCALE
COMMUNITIES
OF
AGENTS
.
285
13.10.1
SIMPLE
RATIONAL
AGENTS
.
285
13.10.2
AUTONOMOUS
AGENTS
.
286
13.10.3
SOFTWARE
AGENTS,
OR
MOBILE
AGENTS
.
288
13.10.4
INDIVIDUAL
AGENTS
VS
COALITIONS
OF
AGENTS
.
289
13.10.5
HIERARCHIES
OF
PROCESSING
WITHIN
COALITIONS
OF
AGENTS
AT
EACH
LEVEL
OF
RESOLUTION
.
290
13.10.6
INTEGRATING
THE
SOURCES
OF
MEANING:
TOWARD
SEMIOTIC
TOOLS
OF
SIMULATION
.
293
REFERENCES
.
295
14.
EVOLUTIONARY
LEARNING
IN
AGENT-BASED
MODELING.
297
S.
TAKAHASHI
14.1
INTRODUCTION
.
297
XXII
CONTENTS
14.2
INTERNAL
MODEL
PRINCIPLE
FOR
AGENT-BASED
MODELING
.
300
14.3
BASIC
STEPS
AND
METHOD
FOR
EVOLUTIONARY
LEARNING
IN
AGENT-BASED
MODELING
.
301
14.3.1
BASIC
STEPS
.
301
14.3.2
GENETIC
ALGORITHM
.
302
14.4
HYPERGAME
MODEL
FOR
EVOLUTIONARY
LEARNING
.
302
14.5
SIMULATION
OF
EVOLUTIONARY
LEARNING
BASED
ON
NETWORK
TYPE
DYNAMIC
HYPERGAME
.
306
14.5.1
ASSUMPTIONS
.
306
14.5.2
STEPS
OF
THE
SIMULATION
.
307
14.5.3
FITNESS
.
308
14.5.4
SELECTION
AND
CROSSOVER
.
310
14.6
RESULTS
.
310
14.7
CONCLUSIONS.
311
REFERENCES
.
312
15.
A
SYSTEM
THEORETIC
APPROACH
TO
CONSTRUCTING
TEST
BEDS
FOR
MULTI-AGENT
SYSTEMS
.
315
A.M.
UHRMACHER
15.1
INTRODUCTION.
315
15.2
DEVS
.
317
15.3
A
FORMALISM
TO
DESCRIBE
REFLECTIVE
DYNAMIC
SYSTEMS
.
319
15.3.1
DYNAMIC
DEVS
NETWORKS
.
322
15.3.2
AN
ABSTRACT
SIMULATOR
FOR
DYNAMIC
DEVS
.
323
15.4
JAMES
.
326
15.4.1
DELIBERATIVE
AGENTS
IN
JAMES
.
327
15.4.2
CONCURRENT
SIMULATION
OF
AGENTS
.
332
15.4.3
DISTRIBUTED
SIMULATION
OF
AGENTS
.
334
15.5
CONCLUSIONS.
337
ACKNOWLEDGMENTS
.
338
REFERENCES
.
338
16.
A
METHODOLOGY
FOR
THE
TRANSLATION
OF
KNOWLEDGE
BETWEEN
HETEROGENEOUS
PLANNERS
.
341
S.
RAMACHANDRAN
AND
M.M.
MAREFAT
16.1
INTRODUCTION.
341
16.2
PROBLEM
FORMULATION
.
344
16.2.1
THE
COMMON
ONTOLOGY
.
348
16.2.2
KNOWLEDGE
SHARING
BETWEEN
PLANNERS
.
348
16.2.3
KNOWLEDGE
EQUIVALENCE
.
349
16.3
KNOWLEDGE
TRANSLATION
.
350
16.3.1
TRANSLATING
QUERIES
.
351
16.3.2
TRANSLATING
PLANS
.
353
16.3.2.1
PARTITIONING
PLANS
FOR
TRANSLATION
.
353
CONTENTS
XXIII
16.3.2.2
PLAN
TRANSLATION
.
354
16.4
EXAMPLE
AND
RESULTS
.
355
16.5
LEARNING
NEW
KNOWLEDGE
.
359
16.6
RELATED
WORK
AND
DISCUSSION
.
362
16.7
CONCLUSIONS
.
363
REFERENCES
.
364
17.
TOWARDS
A
SYSTEMS
METHODOLOGY
FOR
OBJECT-ORIENTED
SOFTWARE
ANALYSIS
.
367
H.
PRAEHOFER
17.1
INTRODUCTION
.
367
17.2
THE
UNIFIED
SOFTWARE
DEVELOPMENT
PROCESS
.
368
17.2.1
DEFICIENCIES
OF
THE
UNIFIED
PROCESS
.
371
17.3
A
SHORT
REVIEW
OF
THE
SYSTEM
MODELING
METHODOLOGY
.
372
17.3.1
HIERARCHY
OF
SYSTEM
SPECIFICATIONS
.
372
17.3.2
MODELING
.
373
17.3.3
SYSTEM
MORPHISMS
AS
A
FUNDAMENTAL
MEANS
FOR
BUILDING
ABSTRACTIONS
.
373
17.3.4
USE
CASE
DRIVEN
DESIGN
IN
THE
SYSTEM
MODELING
PERSPECTIVE
.
374
17.4
IMPROVED
SOFTWARE
DEVELOPMENT
PROCESS
.
375
17.4.1
SYSTEM-CENTERED
APPROACH
FOR
USE
CASE
DESCRIPTIONS
.
375
17.4.2
ARCHITECTURE
FOR
EMBEDDED
SYSTEMS
.
376
17.4.3
SYSTEM
MORPHISMS
AS
A
MEANS
TO
BUILD
INFORMATION
MODELS
.
378
17.5
APPLICATION
EXAMPLE:
ELEVATOR
CONTROL
SYSTEM
.
380
17.6
SUMMARY
.
385
REFERENCES
.
387
INDEX
.
389 |
| any_adam_object | 1 |
| building | Verbundindex |
| bvnumber | BV013916337 |
| callnumber-first | Q - Science |
| callnumber-label | QA76 |
| callnumber-raw | QA76.9.C65 |
| callnumber-search | QA76.9.C65 |
| callnumber-sort | QA 276.9 C65 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | ST 340 |
| ctrlnum | (OCoLC)45582469 (DE-599)BVBBV013916337 |
| dewey-full | 003/.3 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 003 - Systems |
| dewey-raw | 003/.3 |
| dewey-search | 003/.3 |
| dewey-sort | 13 13 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Book |
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| genre_facet | Aufsatzsammlung Festschrift Konferenzschrift |
| id | DE-604.BV013916337 |
| illustrated | Illustrated |
| indexdate | 2024-11-22T17:26:55Z |
| institution | BVB |
| isbn | 0387950656 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-009521787 |
| oclc_num | 45582469 |
| open_access_boolean | |
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| owner_facet | DE-703 DE-19 DE-BY-UBM DE-861 DE-29T DE-706 DE-634 |
| physical | XXIX, 397 S. graph. Darst. : 24 cm |
| publishDate | 2001 |
| publishDateSearch | 2001 |
| publishDateSort | 2001 |
| publisher | Springer |
| record_format | marc |
| spelling | Discrete event modeling and simulation technologies a tapestry of systems and AI-based theories and methodologies ; a tribute to the 60th birthday of Bernard P. Zeigler Hessam S. Sarjoughian ... (ed.) New York [u.a.] Springer 2001 XXIX, 397 S. graph. Darst. : 24 cm txt rdacontent n rdamedia nc rdacarrier Zeigler, Bernard P. <1940-> Discrete gebeurtenissen gtt Kunstmatige intelligentie gtt Modèles mathématiques - Congrès Numerieke wiskunde gtt Simulatie gtt Simulation par ordinateur - Congrès Mathematisches Modell Computer simulation Congresses Mathematical models Congresses Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Diskretes Ereignissystem (DE-588)4196828-1 gnd rswk-swf Computersimulation (DE-588)4148259-1 gnd rswk-swf Systemtheorie (DE-588)4058812-9 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content (DE-588)4016928-5 Festschrift gnd-content (DE-588)1071861417 Konferenzschrift gnd-content Diskretes Ereignissystem (DE-588)4196828-1 s Computersimulation (DE-588)4148259-1 s DE-604 Systemtheorie (DE-588)4058812-9 s Künstliche Intelligenz (DE-588)4033447-8 s Sarjoughian, Hessam S. Sonstige oth Zeigler, Bernard P. hnr DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009521787&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Discrete event modeling and simulation technologies a tapestry of systems and AI-based theories and methodologies ; a tribute to the 60th birthday of Bernard P. Zeigler Zeigler, Bernard P. <1940-> Discrete gebeurtenissen gtt Kunstmatige intelligentie gtt Modèles mathématiques - Congrès Numerieke wiskunde gtt Simulatie gtt Simulation par ordinateur - Congrès Mathematisches Modell Computer simulation Congresses Mathematical models Congresses Künstliche Intelligenz (DE-588)4033447-8 gnd Diskretes Ereignissystem (DE-588)4196828-1 gnd Computersimulation (DE-588)4148259-1 gnd Systemtheorie (DE-588)4058812-9 gnd |
| subject_GND | (DE-588)4033447-8 (DE-588)4196828-1 (DE-588)4148259-1 (DE-588)4058812-9 (DE-588)4143413-4 (DE-588)4016928-5 (DE-588)1071861417 |
| title | Discrete event modeling and simulation technologies a tapestry of systems and AI-based theories and methodologies ; a tribute to the 60th birthday of Bernard P. Zeigler |
| title_auth | Discrete event modeling and simulation technologies a tapestry of systems and AI-based theories and methodologies ; a tribute to the 60th birthday of Bernard P. Zeigler |
| title_exact_search | Discrete event modeling and simulation technologies a tapestry of systems and AI-based theories and methodologies ; a tribute to the 60th birthday of Bernard P. Zeigler |
| title_full | Discrete event modeling and simulation technologies a tapestry of systems and AI-based theories and methodologies ; a tribute to the 60th birthday of Bernard P. Zeigler Hessam S. Sarjoughian ... (ed.) |
| title_fullStr | Discrete event modeling and simulation technologies a tapestry of systems and AI-based theories and methodologies ; a tribute to the 60th birthday of Bernard P. Zeigler Hessam S. Sarjoughian ... (ed.) |
| title_full_unstemmed | Discrete event modeling and simulation technologies a tapestry of systems and AI-based theories and methodologies ; a tribute to the 60th birthday of Bernard P. Zeigler Hessam S. Sarjoughian ... (ed.) |
| title_short | Discrete event modeling and simulation technologies |
| title_sort | discrete event modeling and simulation technologies a tapestry of systems and ai based theories and methodologies a tribute to the 60th birthday of bernard p zeigler |
| title_sub | a tapestry of systems and AI-based theories and methodologies ; a tribute to the 60th birthday of Bernard P. Zeigler |
| topic | Zeigler, Bernard P. <1940-> Discrete gebeurtenissen gtt Kunstmatige intelligentie gtt Modèles mathématiques - Congrès Numerieke wiskunde gtt Simulatie gtt Simulation par ordinateur - Congrès Mathematisches Modell Computer simulation Congresses Mathematical models Congresses Künstliche Intelligenz (DE-588)4033447-8 gnd Diskretes Ereignissystem (DE-588)4196828-1 gnd Computersimulation (DE-588)4148259-1 gnd Systemtheorie (DE-588)4058812-9 gnd |
| topic_facet | Zeigler, Bernard P. <1940-> Discrete gebeurtenissen Kunstmatige intelligentie Modèles mathématiques - Congrès Numerieke wiskunde Simulatie Simulation par ordinateur - Congrès Mathematisches Modell Computer simulation Congresses Mathematical models Congresses Künstliche Intelligenz Diskretes Ereignissystem Computersimulation Systemtheorie Aufsatzsammlung Festschrift Konferenzschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009521787&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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