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E-CARGO and Role-Based Collaboration

Modeling and Solving Problems in the Complex World

Zhu, Haibin

IEEE Series on Systems Science and Engineering


1. Auflage Dezember 2021
400 Seiten, Hardcover
Wiley & Sons Ltd

ISBN: 978-1-119-69306-2
John Wiley & Sons

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E-CARGO and Role-Based Collaboration

A model for collaboratively solving complex problems

E-CARGO and Role-Based Collaboration offers a unique guide that explains the nature of collaboration, explores an easy-to-follow process of collaboration, and defines a model to solve complex problems in collaboration and complex systems. Written by a noted expert on the topic, the book initiates the study of an effective collaborative system from a novel perspective. The role-based collaboration (RBC) methodology investigates the most important aspects of a variety of collaborative systems including societal-technical systems. The models and algorithms can also be applied across system engineering, production, and management.

The RBC methodology provides insights into complex systems through the use of its core model E-CARGO. The E-CARGO model provides the fundamental components, principles, relationships, and structures for specifying the state, process, and evolution of complex systems. This important book:
* Contains a set of concepts, models, and algorithms for the analysis, design, implementation, maintenance, and assessment of a complex system
* Presents computational methods that use roles as a primary underlying mechanism to facilitate collaborative activities including role assignment
* Explores the RBC methodology that concentrates on the aspects that can be handled by individuals to establish a well-formed team
* Offers an authoritative book written by a noted expert on the topic

Written for researchers and practitioners dealing with complex problems in collaboration systems and technologies, E-CARGO and Role-Based Collaboration contains a model to solve real world problems with the help of computer-based systems.


Part 1 Backgrounds

Chapter 1 Introduction



Collaboration, Collaboration Systems, Components of Collaboration, Nature of Collaboration, Complex Systems, Collectivism, Individualism, Problem Solving.

1.1 Collaboration and Collaboration Systems

1.1.1 Collaboration

1.1.2 Collaboration Systems

1.2 Collaboration as "Divide and Conquer"

1.3 Key Components of Collaboration

1.4 The Nature of Collaboration

1.5 The Complexity of Collaboration

1.6 Collectivism or Individualism

1.7 Collaboration and Complex Systems

1.7.1 What are Complex Systems?

1.7.2 Examples of Complex Systems

1.8 Collaboration and Problem Solving

1.9 Summary



Chapter 2 Role Concepts



2.1 Terminology

2.2 Modeling-Roles

2.2.1 Evolution of Objects

2.2.2 Fundamental Modeling Concepts

2.2.3 Interfaces between Objects

2.2.4 Separation of Concerns

2.2.5 Modeling-Roles in Specification and Design

2.3 Roles in Agent Systems

2.4 Role-Based Access Control (RBAC)

2.4.1 Evolution of RBAC-Roles

2.4.2 Applications of RBAC-Roles

2.5 Roles in CSCW Systems

2.6 Roles in Social Psychology and Management

2.7 Convergence of Role Concepts

2.8 Summary



Part 2 Methodologies and Models

Chapter 3 Role-Based Collaboration



3.1 Requirements for Role-Based Collaboration

3.2 Architecture of an RBC system

3.3 The Environment Established by Role-Based Collaboration

3.4 The Process of Role-Based Collaboration

3.5 Fundamental Principles of RBC

3.5.1 Object principles

3.5.2 Agent principles

3.5.3 Role principles

3.5.4 Group principles

3.6 Benefits of Role-Based Collaboration

3.6.1 Establish trust in collaboration

3.6.2 Establish Dynamics

3.6.3 Facilitate Interaction

3.6.4 Support adaptation

3.6.5 Information Sharing

3.6.6 Other benefits

3.7 Summary



Chapter 4 The E-CARGO Model



4.1 First Class Components

4.1.1 Objects and Classes

4.1.2 Roles and Environments

4.1.3 Agents and Groups

4.2 Second Class Components

4.2.1 Users or Human Users

4.2.2 Message

4.2.3 System

4.3 Fundamental Relationships in E-CARGO

4.3.1 The Relations among Roles Role Classes and Instances Inheritance Relation Promotion relations Report-to Relations Request relations Derived relations Conflict relations

4.3.2 The Relations between Roles and Agents

4.3.3 The Relations between Agents

4.3.4 Properties of an RBC system and their Applications

4.4 Kernel Mechanisms of RBC

4.4.1 Primitive roles

4.4.2 Fundamental Classes

4.4.3 Implementation

4.5 Related Work

4.6 Summary



Chapter 5 Group Role Assignment (GRA)



5.1 Role Assignment

5.2 A Real-World Problem

5.3 Extended Expression of the E-CARGO Model

5.4 Group Role Assignment Problems

5.4.1 Simple role assignment

5.4.2 Rated group role assignment

5.4.3 Weighted role assignment

5.5 General Assignment Problem and the K-M Algorithm

5.6 Solutions to GRA Problems

5.7 Implementation and Performance Experiments

5.8 Performance Analysis

5.9 Case Study by Simulation

5.10 Related Work

5.11 Summary



Chapter 6 Group Role Assignment with Constraints: GRA+



6.1 Group Multi-Role Assignment (GMRA)

6.1.1 A Real-World Scenario

6.1.2 Problem Formalization

6.1.3 The CPLEX solution and its Performance Experiments

6.1.4 Improvement of the CPLEX Solution

6.1.5 Comparisons

6.1.6 Another Real-World Example

6.2 Group Role Assignment with Conflicting Agents (GRACA)

6.2.1 A Real-World Scenario

6.2.2 Problem Formalization

6.2.3 The Benefits of Avoiding Conflicts

6.2.4 GRACAR/G Problems Are Subproblems of an NP-Complete Problem

6.2.5 Solutions with CPLEX

6.3 Group Role Assignment with Cooperation and Conflict Factors

6.3.1 A Real-World Scenario

6.3.2 Problem Formalization

6.3.3 A Practical Solution

6.3.4 Performance Experiments

6.3.5 The Benefits

6.3.6 Cooperation and conflict Factor Collection

6.4 Related Work

6.5 Summary



Chapter 7 Group Role Assignment with Multiple Objectives: GRA++



7.1 Group Role Assignment with Budget Constraints (GRABC)

7.1.1 A Real-World Scenario

7.1.2 Problem Formalization

7.1.3 Solutions with an LP Solver

7.1.4 Simulations of GRABC-WS and GRABC-Syn

7.1.5 Performance Experiments and improvements

7.1.6 Synthesis and a case Study

7.2 Good at Many things and Expert in One (GMEO)

7.2.1 A Real-World Scenario

7.2.2 Problem Formalizations

7.2.3 A Solution with CPLEX

7.2.4 Performance Experiments and Improvements

7.2.5 A Simple Formalization of GMEO with an Efficient Solution

7.2.6 A More Efficient Solution for GMEO-1

7.3 Related Work

7.4 Summary



Chapter 8 Solving Engineering Problems with GRA



8.1 Group Role Assignment with Agents' Busyness Degrees

8.1.1 A Real-World Scenario

8.1.2 Problem Formalization

8.1.3 Solutions

8.1.4 Simulations and Benefits

8.2 Group Multi-Role Assignment with Coupled Roles

8.2.1 A Real-World Scenario

8.2.2 The Problem Specification

8.2.3 The Solutions with CPLEX and Initial Results

8.2.4 Verification Experiments

8.3 Most Economical Redundant Assignment

8.3.1 A Real-World Scenario

8.3.2 Problem Formalizations

8.3.3 A Solution with CPLEX

8.3.4 A new Form of the MERA Problem and a More Efficient Solution

8.3.5 Experiments and Comparisons

8.4 Group Role Assignment with Agents' Preferences

8.4.1 A Real-World Scenario

8.4.2 Problem Formalization

8.4.3 The Benefits of Considering Agents' Preferences

8.5 Related Work

8.6 Summary



Chapter 9 Role Transfer



9.1 Role Transfer Problems

9.1.1 Algorithm to Find a Partition

9.1.2 Role Transfer Algorithm with Matrices

9.1.3 Algorithm for Role Transfer with the E-CARGO Model

9.2 The M-M Role Transfer Problems

9.2.1 M-1 Problem

9.2.2 1-M Problem

9.2.3 M-M Problem

9.3 From M-M RTPs to Role Assignment Problems

9.4 Temporal M-M Role Transfer Problems

9.4.1 Temporal Transfer with Weak Restriction

9.4.2 Temporal Transfer with Strong Restriction

9.4.3 A Near-Optimal Solution to SRTP with the Kuhn-Munkres Algorithm

9.4.4 Performance Experiments

9.5 Role Transfer Tool

9.6 Related work

9.7 Summary



Chapter 10 Adaptive Collaboration Systems



10.1 Adaptation and Adaptability

10.2 A Real-World Problem

10.3 Group Performance and its parameters

10.4 Adaptive Collaboration

10.4.1 A scenario for a future battle

10.4.2 Apply E-CARGO and Related Algorithms to Solve the Problem

10.4.3 A new qualification model

10.5 The Architecture and the Self-* Properties of an Adaptive Collaboration System

10.6 A General Approach to AC

10.7 Related Work

10.8 Summary



Part 3 Applications

Chapter 11 Team Performance



11. 1 Team Performance

11.2 Static Team Performance

11.2.1 Modeling Team Performance with the E-CARGO Model

11.2.2 Refine the Predicted Team Performance by Introducing More Constraints

11.2.3 Case Study

11.3 Dynamic Team Performance

11.3.1 A Typical Dynamic Scenario of Collaboration

11.3.2 Formalization of dynamic team performance

11.3.3 Simulation Design

11.3.4 Simulation Results and Analysis

11.4 Related Work

11.5 Summary



Chapter 12 Applications of RBC and E-CARGO



12.1 Role-Based Human-Computer Interaction

12.1.1 Natural Intelligence and Artificial Intelligence

12.1.2 Interaction

12.1.3 Characteristics of Interaction

12.1.4 Classification of Interactions

12.1.5 The differences between HCI and AI3

12.1.6 Shared models for interaction

12.1.7 Roles as shared models for interaction

12.1.8 Scenarios of Role-Based Interaction

12.1.9 Case Study: Restrain Mental Workload with Roles

12.2 When to Re-staff a Late Project

12.2.1 Formalization of the Problem

12.2.2 A Solution Based on GRA

12.2.3 Simulations

12.2.4 Performances

12.2.5 Case study

12.3 An Efficient Outpatient Scheduling Approach

12.3.1 A Real-World Outpatient Scheduling Problem

12.3.2 Collaborative Outpatient Scheduling - Our Strategy

12.3.3 From the Outpatient Problem to the Group Role Assignment Problem

12.3.4 The Algorithm and Complexity

12.4 Related Work

12.5 Chapter Summary



Chapter 13 Social Simulation with RBC and E-CARGO



13.1 Social Systems, Organizations, and Individuals

13.2 Establishing the Requirement of Social Simulation

13.3 Meeting the requirements of Social Simulation with E-CARGO

13.4 Social Simulation Method with RBC and E-CARGO

13.5 Case Study 1: Peer Review and Improvement

13.5.1 Peer Review

13.5.2 The Benefits Obtained by GRA

13.6 Case Study 2: Collectivism or Individualism

13.6.1 How to Express Collectivism and Individualism

13.6.2 Overall team performances of Collectivism and Individualism

13.6.3 Simulations and Results

13.7 Case Study 3: How to Acquire the Preferred Position in a Team

13.7.1 A Real-World Scenario

13.7.2 Policies and Simulation Experiments

13.7.3 The Effects to the Group Performance

13.7.4 Results and Discussions

13.8 Related Work

13.9 Summary



Chapter 14 More to Investigate



14.1 Role Negotiation

14.2 Role Specification

14.3 Agent Evaluation

14.4 Collective Group Role Assignment

14.4.1 One-Way Collective Role Assignment

14.4.2 Two-Way Collective Role Assignment

14.5 Role Engine

14.5.1 Role Dynamics

14.5.2 Role Interaction

14.5.3 Role Presentation

14.6 Other challenges in RBC and E-CARGO

14.6.1 Optimizations

14.6.2 Agent-Oriented Software Engineering (AOSE)

14.6.3 Multi-agent systems

14.7 Not the end

HAIBIN ZHU, PHD is a Full Professor and the Chair of Department of Computer Science and Mathematics, Founding Director of Collaborative Systems Laboratory, member of Arts and Science Executive Committee, Nipissing University.