Agent-based hybrid intelligent systems: an agent-based framework for complex problem solving
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin [u.a.]
Springer
2004
|
| Schriftenreihe: | Lecture notes in computer science
2938 : Tutorial |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIV, 196 S. graph. Darst. |
| ISBN: | 3540209085 |
Internformat
MARC
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| 100 | 1 | |a Zhang, Zili |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Agent-based hybrid intelligent systems |b an agent-based framework for complex problem solving |c Zili Zhang ; Chengqi Zhang |
| 246 | 1 | 3 | |a Agent based hybrid intelligent systems |
| 264 | 1 | |a Berlin [u.a.] |b Springer |c 2004 | |
| 300 | |a XIV, 196 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Lecture notes in computer science |v 2938 : Tutorial | |
| 650 | 7 | |a Agent intelligent |2 rasuqam | |
| 650 | 4 | |a Agents intelligents (Logiciels) | |
| 650 | 4 | |a Informatique douce | |
| 650 | 7 | |a Informatique douce |2 rasuqam | |
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| 650 | 7 | |a Système hybride (Informatique) |2 rasuqam | |
| 650 | 4 | |a Systèmes experts (Informatique) | |
| 650 | 4 | |a Expert systems (Computer science) | |
| 650 | 4 | |a Hybrid computers | |
| 650 | 4 | |a Intelligent agents (Computer software) | |
| 650 | 4 | |a Soft computing | |
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Datensatz im Suchindex
| _version_ | 1804130551925309440 |
|---|---|
| adam_text | CONTENTS
PART
I
FUNDAMENTALS
OF
HYBRID
INTELLIGENT
SYSTEMS
AND
AGENTS
1
INTRODUCTION
...............................................
3
1.1
HYBRID
INTELLIGENT
SYSTEMS
ARE
ESSENTIAL
FOR
SOLVING
COMPLEX
PROBLEMS
............................
4
1.2
HYBRIDS
ARE
COMPLEX
....................................
5
1.3
AGENT
PERSPECTIVES
ARE
SUITABLE
FOR
HYBRIDS
................
7
1.4
MOTIVATION
AND
TARGETS
..................................
11
2
BASICS
OF
HYBRID
INTELLIGENT
SYSTEMS
.......................
13
2.1
TYPICAL
INTELLIGENT
TECHNIQUES.............................
14
2.1.1
EXPERT
SYSTEMS
...................................
14
2.1.2
FUZZY
SETS
AND
FUZZY
LOGIC.........................
15
2.1.3
NEURAL
NETWORKS
..................................
16
2.1.4
GENETIC
ALGORITHMS................................
19
2.2
ADVANTAGES
AND
DISADVANTAGES
OF
TYPICAL
INTELLIGENT
TECHNIQUES
..........................
21
2.2.1
KNOWLEDGE
ACQUISITION.............................
21
2.2.2
BRITTLENESS........................................
21
2.2.3
EXPLANATION
......................................
22
2.3
CLASSIFICATION
OF
HYBRID
INTELLIGENT
SYSTEMS
.................
23
2.3.1
MEDSKER S
CLASSIFICATION
SCHEME
.....................
23
2.3.2
GOONATILAKE S
CLASSIFICATION
SCHEME..................
26
2.4
CURRENT
PRACTICE
IN
TYPICAL
HYBRID
INTELLIGENT
SYSTEM
DEVELOPMENT............................................
27
3
BASICS
OF
AGENTS
AND
MULTI-AGENT
SYSTEMS
.................
29
3.1
CONCEPTS
OF
AGENTS
AND
MULTI-AGENT
SYSTEMS................
29
3.2
AGENTS
AS
A
PARADIGM
FOR
SOFTWARE
ENGINEERING..............
30
3.3
AGENTS
AND
OBJECTS......................................
31
3.4
AGENTS
AND
EXPERT
SYSTEMS...............................
33
X
CONTENTS
3.5
APPROACHES
TO
AGENTIFICATION..............................
33
3.5.1
IMPLEMENTING
A
TRANSDUCER.........................
34
3.5.2
IMPLEMENTING
A
WRAPPER
...........................
34
3.5.3
REWRITING
........................................
34
3.5.4
STEPS
FOR
IMPLEMENTING
A
WRAPPER...................
34
3.6
APPROACHES
TO
INCORPORATING
INTELLIGENT
TECHNIQUES
INTO
AGENTS
.............................................
35
3.7
AGENT-BASED
HYBRID
SYSTEMS:
STATE
OF
THE
ART
..............
35
3.7.1
THE
MIX
MULTI-AGENT
PLATFORM
.....................
35
3.7.2
THE
PREDICTOR
SYSTEM
.........................
36
3.7.3
INTELLIGENT
MULTI-AGENT
HYBRID
DISTRIBUTED
ARCHITECTURE
......................................
37
3.7.4
MULTI-AGENT
ARCHITECTURE
FOR
FUZZY
MODELING..........
38
3.7.5
GENERIC
ARCHITECTURE
FOR
HYBRID
INTELLIGENT
SYSTEMS....
38
3.7.6
SUMMARY.........................................
38
PART
II
METHODOLOGY
AND
FRAMEWORK
4
AGENT-ORIENTED
METHODOLOGIES
.............................
43
4.1
TRADITIONAL
METHODOLOGIES
................................
43
4.2
GAIA
METHODOLOGY.......................................
44
4.3
COORDINATION-ORIENTED
METHODOLOGY
.......................
45
4.4
PROMETHEUS
METHODOLOGY.................................
45
4.5
METHODOLOGY
FOR
ANALYSIS
AND
DESIGN
OF
AGENT-BASED
HYBRIDS
..................................
46
4.5.1
OUTLINE
OF
THE
METHODOLOGY.........................
46
4.5.2
ROLE
MODEL
.......................................
49
4.5.3
INTERACTION
MODEL
.................................
51
4.5.4
ORGANIZATIONAL
RULES...............................
52
4.5.5
AGENT
MODEL......................................
53
4.5.6
SKILL
MODEL
.......................................
53
4.5.7
KNOWLEDGE
MODEL
.................................
54
4.5.8
ORGANIZATIONAL
STRUCTURES
AND
PATTERNS
..............
54
4.6
SUMMARY...............................................
55
5
AGENT-BASED
FRAMEWORK
FOR
HYBRID
INTELLIGENT
SYSTEMS
...
57
5.1
A
UNIFYING
AGENT
FRAMEWORK
FOR
HYBRID
INTELLIGENT
SYSTEMS
..
57
5.2
ISSUES
ON
ONTOLOGIES
.....................................
59
5.2.1
WHY
ONTOLOGIES?
..................................
60
5.2.2
ONTOLOGIES
IN
FINANCE
..............................
60
5.2.3
CONSTRUCTION
OF
FINANCIAL
ONTOLOGY
..................
61
5.3
SUMMARY...............................................
63
CONTENTS
XI
6
MATCHMAKING
IN
MIDDLE
AGENTS
............................
65
6.1
DESCRIPTION
OF
THE
PROBLEM
...............................
66
6.2
RELATED
WORK
OF
MATCHMAKING
IN
MIDDLE
AGENTS
............
67
6.3
IMPROVEMENTS
TO
MATCHMAKING
ALGORITHMS
IN
MIDDLE
AGENTS..
73
6.3.1
REPRESENTATION
OF
TRACK
RECORDS
....................
73
6.3.2
ACCUMULATION
OF
TRACK
RECORDS
.....................
74
6.3.3
GENERATION
OF
INITIAL
VALUES.........................
74
6.3.4
USE
OF
TRACK
RECORDS
..............................
85
6.3.5
IMPACT
OF
TRACK
RECORDS
ON
MATCHMAKING
............
88
6.4
DISCUSSION
..............................................
90
PART
III
APPLICATION
SYSTEMS
7
AGENT-BASED
HYBRID
INTELLIGENT
SYSTEM
FOR
FINANCIAL
INVESTMENT
PLANNING
.........................
93
7.1
INTRODUCTION
TO
SOME
MODELS
INTEGRATED
IN
THE
SYSTEM
.......
94
7.1.1
FINANCIAL
RISK
TOLERANCE
MODEL
.....................
94
7.1.2
ASSET
ALLOCATION
MODEL
............................
95
7.1.3
PORTFOLIO
SELECTION
MODELS
..........................
96
7.1.4
INTEREST
PREDICTION
MODELS..........................
99
7.1.5
ORDERED
WEIGHTED
AVERAGING
OPERATION
..............100
7.2
ANALYSIS
OF
THE
SYSTEM
...................................104
7.3
DESIGN
OF
THE
SYSTEM
....................................108
7.4
ARCHITECTURE
OF
THE
SYSTEM
...............................111
7.5
IMPLEMENTATION
OF
THE
SYSTEM.............................112
7.5.1
INTERNAL
STRUCTURES
OF
AGENTS
.......................113
7.5.2
PRACTICAL
ARCHITECTURE
OF
THE
SYSTEM.................115
7.6
CASE
STUDY
.............................................116
7.6.1
A
TYPICAL
SCENARIO
FOR
INVESTMENT...................117
7.6.2
EXAMPLE
.........................................117
7.6.3
RUNNING
THE
SYSTEM
...............................121
7.6.4
EMPIRICAL
EVALUATION
OF
THE
AGGREGATED
RESULTS
.......122
8
AGENT-BASED
HYBRID
INTELLIGENT
SYSTEM
FOR
DATA
MINING
...
127
8.1
TYPICAL
DATA
MINING
TECHNIQUES
..........................128
8.1.1
CLASSIFICATION
.....................................128
8.1.2
CLUSTERING
........................................130
8.1.3
ASSOCIATION
RULES
.................................131
8.2
DATA
MINING
REQUIRES
HYBRID
SOLUTIONS
....................133
8.3
REQUIREMENTS
OF
THE
AGENT-BASED
HYBRID
SYSTEMS
FOR
DATA
MINING.........................................134
8.4
ANALYSIS
AND
DESIGN
OF
THE
SYSTEM.........................135
8.5
IMPLEMENTATION
OF
THE
SYSTEM.............................138
8.6
CASE
STUDY
.............................................140
XII
CONTENTS
PART
IV
CONCLUDING
REMARKS
9
THE
LESS
THE
MORE
........................................
145
9.1
FLEXIBILITY
AND
ROBUSTNESS
TESTING.........................145
9.2
FUTURE
WORK............................................146
APPENDIX:
SAMPLE
SOURCE
CODES
OF
THE
AGENT-BASED
FINANCIAL
PLANNING
SYSTEM
................
149
A
SOURCE
CODES
FOR
DATA
SUPPLY
AGENT
(STOCKDATA)
...........150
B
SOURCE
CODES
OF
PLANNING
AGENT
FOR
PORTFOLIO
SELECTION
(STOCK).............................153
C
SOURCE
CODES
FOR
PORTFOLIO
SELECTION
AGENT
BASED
ON
MARKOWITZ S
MODEL
(MOKI)
.......................159
D
SOURCE
CODES
FOR
PORTFOLIO
SELECTION
AGENT
BASED
ON
FUZZY
LOGIC
MODEL
(FUZZ)........................162
E
SOURCE
CODES
FOR
PORTFOLIO
SELECTION
AGENT
BASED
ON
POSSIBILITY
DISTRIBUTION
MODEL
(POSS)..............165
F
SOURCE
CODES
FOR
DECISION
AGGREGATION
AGENT
BASED
ON
ORDERED
WEIGHTED
AVERAGING
OPERATORS
(AGGR)
.....168
G
SOURCE
CODES
FOR
PLANNING
AGENT
OF
INVESTMENT
DECISION-MAKING
(INVPOLICY)..................170
H
SOURCE
CODES
FOR
INVESTMENT
DECISION-MAKING
AGENT
(INVPPT).173
I
SOURCE
CODES
FOR
INTEREST
PREDICTION
AGENT
BASED
ON
FUZZY
LOGIC
AND
GENETIC
ALGORITHMS
(FLGA)
........176
J
SOURCE
CODES
FOR
INTEREST
PREDICTION
AGENT
BASED
ON
NEURAL
NETWORKS
(FFIN)
..........................179
REFERENCES
.....................................................
183
INDEX
..........................................................
193
|
| any_adam_object | 1 |
| author | Zhang, Zili Zhang, Chengqi |
| author_facet | Zhang, Zili Zhang, Chengqi |
| author_role | aut aut |
| author_sort | Zhang, Zili |
| author_variant | z z zz c z cz |
| building | Verbundindex |
| bvnumber | BV017880353 |
| callnumber-first | Q - Science |
| callnumber-label | QA76 |
| callnumber-raw | QA76.76.I58 |
| callnumber-search | QA76.76.I58 |
| callnumber-sort | QA 276.76 I58 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | SS 4800 |
| classification_tum | DAT 700f |
| ctrlnum | (OCoLC)54371618 (DE-599)BVBBV017880353 |
| dewey-full | 006.3/3 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/3 |
| dewey-search | 006.3/3 |
| dewey-sort | 16.3 13 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Book |
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| id | DE-604.BV017880353 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T19:22:50Z |
| institution | BVB |
| isbn | 3540209085 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-010727562 |
| oclc_num | 54371618 |
| open_access_boolean | |
| owner | DE-739 DE-384 DE-91G DE-BY-TUM DE-706 DE-11 |
| owner_facet | DE-739 DE-384 DE-91G DE-BY-TUM DE-706 DE-11 |
| physical | XIV, 196 S. graph. Darst. |
| publishDate | 2004 |
| publishDateSearch | 2004 |
| publishDateSort | 2004 |
| publisher | Springer |
| record_format | marc |
| series | Lecture notes in computer science |
| series2 | Lecture notes in computer science |
| spelling | Zhang, Zili Verfasser aut Agent-based hybrid intelligent systems an agent-based framework for complex problem solving Zili Zhang ; Chengqi Zhang Agent based hybrid intelligent systems Berlin [u.a.] Springer 2004 XIV, 196 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Lecture notes in computer science 2938 : Tutorial Agent intelligent rasuqam Agents intelligents (Logiciels) Informatique douce Informatique douce rasuqam Système expert rasuqam Système hybride (Informatique) rasuqam Systèmes experts (Informatique) Expert systems (Computer science) Hybrid computers Intelligent agents (Computer software) Soft computing Mehragentensystem (DE-588)4389058-1 gnd rswk-swf Lernendes System (DE-588)4120666-6 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf Financial Engineering (DE-588)4208404-0 gnd rswk-swf Expertensystem (DE-588)4113491-6 gnd rswk-swf Lernendes System (DE-588)4120666-6 s Mehragentensystem (DE-588)4389058-1 s DE-604 Expertensystem (DE-588)4113491-6 s Data Mining (DE-588)4428654-5 s Financial Engineering (DE-588)4208404-0 s Zhang, Chengqi Verfasser aut Lecture notes in computer science 2938 : Tutorial (DE-604)BV000000607 2938 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010727562&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Zhang, Zili Zhang, Chengqi Agent-based hybrid intelligent systems an agent-based framework for complex problem solving Lecture notes in computer science Agent intelligent rasuqam Agents intelligents (Logiciels) Informatique douce Informatique douce rasuqam Système expert rasuqam Système hybride (Informatique) rasuqam Systèmes experts (Informatique) Expert systems (Computer science) Hybrid computers Intelligent agents (Computer software) Soft computing Mehragentensystem (DE-588)4389058-1 gnd Lernendes System (DE-588)4120666-6 gnd Data Mining (DE-588)4428654-5 gnd Financial Engineering (DE-588)4208404-0 gnd Expertensystem (DE-588)4113491-6 gnd |
| subject_GND | (DE-588)4389058-1 (DE-588)4120666-6 (DE-588)4428654-5 (DE-588)4208404-0 (DE-588)4113491-6 |
| title | Agent-based hybrid intelligent systems an agent-based framework for complex problem solving |
| title_alt | Agent based hybrid intelligent systems |
| title_auth | Agent-based hybrid intelligent systems an agent-based framework for complex problem solving |
| title_exact_search | Agent-based hybrid intelligent systems an agent-based framework for complex problem solving |
| title_full | Agent-based hybrid intelligent systems an agent-based framework for complex problem solving Zili Zhang ; Chengqi Zhang |
| title_fullStr | Agent-based hybrid intelligent systems an agent-based framework for complex problem solving Zili Zhang ; Chengqi Zhang |
| title_full_unstemmed | Agent-based hybrid intelligent systems an agent-based framework for complex problem solving Zili Zhang ; Chengqi Zhang |
| title_short | Agent-based hybrid intelligent systems |
| title_sort | agent based hybrid intelligent systems an agent based framework for complex problem solving |
| title_sub | an agent-based framework for complex problem solving |
| topic | Agent intelligent rasuqam Agents intelligents (Logiciels) Informatique douce Informatique douce rasuqam Système expert rasuqam Système hybride (Informatique) rasuqam Systèmes experts (Informatique) Expert systems (Computer science) Hybrid computers Intelligent agents (Computer software) Soft computing Mehragentensystem (DE-588)4389058-1 gnd Lernendes System (DE-588)4120666-6 gnd Data Mining (DE-588)4428654-5 gnd Financial Engineering (DE-588)4208404-0 gnd Expertensystem (DE-588)4113491-6 gnd |
| topic_facet | Agent intelligent Agents intelligents (Logiciels) Informatique douce Système expert Système hybride (Informatique) Systèmes experts (Informatique) Expert systems (Computer science) Hybrid computers Intelligent agents (Computer software) Soft computing Mehragentensystem Lernendes System Data Mining Financial Engineering Expertensystem |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010727562&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV000000607 |
| work_keys_str_mv | AT zhangzili agentbasedhybridintelligentsystemsanagentbasedframeworkforcomplexproblemsolving AT zhangchengqi agentbasedhybridintelligentsystemsanagentbasedframeworkforcomplexproblemsolving AT zhangzili agentbasedhybridintelligentsystems AT zhangchengqi agentbasedhybridintelligentsystems |