Influence Models Group Decision Making by Luo Hang (24 results)

hardcover. Condition: Very Good.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

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Hardcover. Condition: new. Hardcover. This book examines influence among decision-makers in group decision-making. It is quite common that people influence and are influenced by each other in group decision-making. Likewise, artificial intelligences can influence and be influenced by each other in interaction or collaboration, and both a person and an artificial intelligence can be called an agent. The author explores how humans or artificial intelligences can interact with and influence each other during the decision-making process, where such influence can reshape the outcome of the group decision. With an interdisciplinary approach, various applications are considered including: computer science (distributed computing, distributed artificial intelligence, particularly multi-agent system); economics and management (joint-stock company voting); and politics (domestic elections and international organization decision-making). The book presents settings of group decision-making where agents preferences/choices are influenced (and thus changed) by each other. As the influence of reality faced by an agent usually comes from more than one agent simultaneously, the author provides both cardinal and ordinal approaches, building social influence functions and a matrix influence function, to address multiple sources of influence in group decision-making. To better describe the complex influence in reality, the author provides a framework of the three levels of influence and its mathematical models to address individual, coalitional, and structural influence and their mixed effects in the context of group decision-making. Even though it is not easy to address the influence of structures on an agent as the influencing subject and the influenced object are disparate, the former is the inter-relationships between agents while the latter is the preference/choice of a single agent. Furthermore, the author considers combinatorial and collective decision-making and provides a framework model of influence across multiple agents and issues. As the influence of reality faced by an agent usually comes from more than one agent simultaneously, the author provides both cardinal and ordinal approaches, building social influence functions and a matrix influence function, to address multiple sources of influence in group decision-making. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condition: New.

Condition: New.

Condition: As New. Unread book in perfect condition.

Buch. Condition: Neu. Neuware -This book examines influence among decision-makers in group decision-making. It is quite common that people influence and are influenced by each other in group decision-making. Likewise, artificial intelligences can influence and be influenced by each other in interaction or collaboration, and both a person and an artificial intelligence can be called an agent. The author explores how humans or artificial intelligences can interact with and influence each other during the decision-making process, where such influence can reshape the outcome of the group decision. With an interdisciplinary approach, various applications are considered including: computer science (distributed computing, distributed artificial intelligence, particularly multi-agent system); economics and management (joint-stock company voting); and politics (domestic elections and international organization decision-making). The book presents settings of group decision-making where agents preferences/choices are influenced (and thus changed) by each other. As the influence of reality faced by an agent usually comes from more than one agent simultaneously, the author provides both cardinal and ordinal approaches, building social influence functions and a matrix influence function, to address multiple sources of influence in group decision-making. To better describe the complex influence in reality, the author provides a framework of the three levels of influence and its mathematical models to address individual, coalitional, and structural influence and their mixed effects in the context of group decision-making. Even though it is not easy to address the influence of structures on an agent as the influencing subject and the influenced object are disparate, the former is the inter-relationships between agents while the latter is the preference/choice of a single agent.Furthermore, the author considers combinatorial and collective decision-making and provides a framework model of influence across multiple agents and issues. 116 pp. Englisch.…

Buch. Condition: Neu. Neuware -This book examines influence among decision-makers in group decision-making. It is quite common that people influence and are influenced by each other in group decision-making. Likewise, artificial intelligences can influence and be influenced by each other in interaction or collaboration, and both a person and an artificial intelligence can be called an agent. The author explores how humans or artificial intelligences can interact with and influence each other during the decision-making process, where such influence can reshape the outcome of the group decision. With an interdisciplinary approach, various applications are considered including: computer science (distributed computing, distributed artificial intelligence, particularly multi-agent system); economics and management (joint-stock company voting); and politics (domestic elections and international organization decision-making). The book presents settings of group decision-making where agents preferences/choices are influenced (and thus changed) by each other. As the influence of reality faced by an agent usually comes from more than one agent simultaneously, the author provides both cardinal and ordinal approaches, building social influence functions and a matrix influence function, to address multiple sources of influence in group decision-making. To better describe the complex influence in reality, the author provides a framework of the three levels of influence and its mathematical models to address individual, coalitional, and structural influence and their mixed effects in the context of group decision-making. Even though it is not easy to address the influence of structures on an agent as the influencing subject and the influenced object are disparate, the former is the inter-relationships between agents while the latter is the preference/choice of a single agent.Furthermore, the author considers combinatorial and collective decision-making and provides a framework model of influence across multiple agents and issues. 116 pp. Englisch.…

Buch. Condition: Neu. Neuware -Introduction.- Background.- Social Influence Functions based on Social Choice.- Matrix Influence Function based on Ordering Matrix.- Graphical and Mathematical Expressions of the Three Levels of Influence.- Addressing Coalitional and Structural Influence: A Probabilistic Approach.- Multiple Sources of Influence across Agents and Issues.- Multiple Weighted Influences.- One Dominant Influence.- Discussion, Conclusion, and Future Work.…

Hardcover. Condition: Brand New. 114 pages. 9.44x6.61x9.61 inches. In Stock.

Condition: New.

Buch. Condition: Neu. Neuware - This book examines influence among decision-makers in group decision-making. It is quite common that people influence and are influenced by each other in group decision-making. Likewise, artificial intelligences can influence and be influenced by each other in interaction or collaboration, and both a person and an artificial intelligence can be called an agent. The author explores how humans or artificial intelligences can interact with and influence each other during the decision-making process, where such influence can reshape the outcome of the group decision. With an interdisciplinary approach, various applications are considered including: computer science (distributed computing, distributed artificial intelligence, particularly multi-agent system); economics and management (joint-stock company voting); and politics (domestic elections and international organization decision-making). The book presents settings of group decision-making where agents preferences/choices are influenced (and thus changed) by each other. As the influence of reality faced by an agent usually comes from more than one agent simultaneously, the author provides both cardinal and ordinal approaches, building social influence functions and a matrix influence function, to address multiple sources of influence in group decision-making. To better describe the complex influence in reality, the author provides a framework of the three levels of influence and its mathematical models to address individual, coalitional, and structural influence and their mixed effects in the context of group decision-making. Even though it is not easy to address the influence of structures on an agent as the influencing subject and the influenced object are disparate, the former is the inter-relationships between agents while the latter is the preference/choice of a single agent.Furthermore, the author considers combinatorial and collective decision-making and provides a framework model of influence across multiple agents and issues.…

Gebundene Ausgabe. Condition: Neu. This book examines influence among decision-makers in group decision-making. It is quite common that people influence and are influenced by each other in group decision-making. Likewise, artificial intelligences can influence and be influenced by each other in interaction or collaboration, and both a person and an artificial intelligence can be called an agent. The author explores how humans or artificial intelligences can interact with and influence each other during the decision-making process, where such influence can reshape the outcome of the group decision. With an interdisciplinary approach, various applications are considered including: computer science (distributed computing, distributed artificial intelligence, particularly multi-agent system); economics and management (joint-stock company voting); and politics (domestic elections and international organization decision-making). The book presents settings of group decision-making where agents? preferences/choices are influenced (and thus changed) by each other. As the influence of reality faced by an agent usually comes from more than one agent simultaneously, the author provides both cardinal and ordinal approaches, building social influence functions and a matrix influence function, to address multiple sources of influence in group decision-making. To better describe the complex influence in reality, the author provides a framework of the three levels of influence and its mathematical models to address individual, coalitional, and structural influence and their mixed effects in the context of group decision-making. Even though it is not easy to address the influence of structures on an agent as the influencing subject and the influenced object are disparate, the former is the inter-relationships between agents while the latter is the preference/choice of a single agent. Furthermore, the author considers combinatorial and collective decision-making and provides a framework model of influence across multiple agents and issues. Sprache: Englisch Gewicht in Gramm: 327.…

Buch. Condition: Neu. Neuware -This book examines influence among decision-makers in group decision-making. It is quite common that people influence and are influenced by each other in group decision-making. Likewise, artificial intelligences can influence and be influenced by each other in interaction or collaboration, and both a person and an artificial intelligence can be called an agent. The author explores how humans or artificial intelligences can interact with and influence each other during the decision-making process, where such influence can reshape the outcome of the group decision. With an interdisciplinary approach, various applications are considered including: computer science (distributed computing, distributed artificial intelligence, particularly multi-agent system); economics and management (joint-stock company voting); and politics (domestic elections and international organization decision-making). The book presents settings of group decision-making where agents' preferences/choices are influenced (and thus changed) by each other. As the influence of reality faced by an agent usually comes from more than one agent simultaneously, the author provides both cardinal and ordinal approaches, building social influence functions and a matrix influence function, to address multiple sources of influence in group decision-making. To better describe the complex influence in reality, the author provides a framework of the three levels of influence and its mathematical models to address individual, coalitional, and structural influence and their mixed effects in the context of group decision-making. Even though it is not easy to address the influence of structures on an agent as the influencing subject and the influenced object are disparate, the former is the inter-relationships between agents while the latter is the preference/choice of a single agent. Furthermore, the author considers combinatorial and collective decision-making and provides a framework model of influence across multiple agents and issues.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 104 pp. Englisch.…

Buch. Condition: Neu. Influence Models in Group Decision-Making | Hang Luo | Buch | Synthesis Lectures on Computer Science | x | Englisch | 2025 | Springer | EAN 9783032013514 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Hardcover. Condition: new. Hardcover. This book examines influence among decision-makers in group decision-making. It is quite common that people influence and are influenced by each other in group decision-making. Likewise, artificial intelligences can influence and be influenced by each other in interaction or collaboration, and both a person and an artificial intelligence can be called an agent. The author explores how humans or artificial intelligences can interact with and influence each other during the decision-making process, where such influence can reshape the outcome of the group decision. With an interdisciplinary approach, various applications are considered including: computer science (distributed computing, distributed artificial intelligence, particularly multi-agent system); economics and management (joint-stock company voting); and politics (domestic elections and international organization decision-making). The book presents settings of group decision-making where agents preferences/choices are influenced (and thus changed) by each other. As the influence of reality faced by an agent usually comes from more than one agent simultaneously, the author provides both cardinal and ordinal approaches, building social influence functions and a matrix influence function, to address multiple sources of influence in group decision-making. To better describe the complex influence in reality, the author provides a framework of the three levels of influence and its mathematical models to address individual, coalitional, and structural influence and their mixed effects in the context of group decision-making. Even though it is not easy to address the influence of structures on an agent as the influencing subject and the influenced object are disparate, the former is the inter-relationships between agents while the latter is the preference/choice of a single agent. Furthermore, the author considers combinatorial and collective decision-making and provides a framework model of influence across multiple agents and issues. As the influence of reality faced by an agent usually comes from more than one agent simultaneously, the author provides both cardinal and ordinal approaches, building social influence functions and a matrix influence function, to address multiple sources of influence in group decision-making. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Condition: new. Questo è un articolo print on demand.

Hardcover. Condition: Brand New. 114 pages. 9.44x6.61x9.61 inches. In Stock. This item is printed on demand.

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.

Hardcover. Condition: new. Hardcover. This book examines influence among decision-makers in group decision-making. It is quite common that people influence and are influenced by each other in group decision-making. Likewise, artificial intelligences can influence and be influenced by each other in interaction or collaboration, and both a person and an artificial intelligence can be called an agent. The author explores how humans or artificial intelligences can interact with and influence each other during the decision-making process, where such influence can reshape the outcome of the group decision. With an interdisciplinary approach, various applications are considered including: computer science (distributed computing, distributed artificial intelligence, particularly multi-agent system); economics and management (joint-stock company voting); and politics (domestic elections and international organization decision-making). The book presents settings of group decision-making where agents preferences/choices are influenced (and thus changed) by each other. As the influence of reality faced by an agent usually comes from more than one agent simultaneously, the author provides both cardinal and ordinal approaches, building social influence functions and a matrix influence function, to address multiple sources of influence in group decision-making. To better describe the complex influence in reality, the author provides a framework of the three levels of influence and its mathematical models to address individual, coalitional, and structural influence and their mixed effects in the context of group decision-making. Even though it is not easy to address the influence of structures on an agent as the influencing subject and the influenced object are disparate, the former is the inter-relationships between agents while the latter is the preference/choice of a single agent. Furthermore, the author considers combinatorial and collective decision-making and provides a framework model of influence across multiple agents and issues. As the influence of reality faced by an agent usually comes from more than one agent simultaneously, the author provides both cardinal and ordinal approaches, building social influence functions and a matrix influence function, to address multiple sources of influence in group decision-making. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…