Synopsis of Role-Based Collaboration (RBC)

RBC 中文助记

Haibin Zhu

 

The Definition

Role-Based Collaboration (RBC) is an emerging computational and discovery methodology that uses roles as the primary underlying mechanism to facilitate collaboration activities.

 

The Model

E-CARGO

 

Fundamental Concepts

Object

Class

Role

Agent

Environment

Group

Messages

 

Fundamental Principles

Object Principles

Role Principles

Agent Principles

Group Principles

 

Fundamental Problems

Role Negotiation

Agent Evaluation

Role Assignment

Role Playing

Role Transfer

 

Fundamental Role Relations

Inheritance

Request

Promotion

Report-to

Conflict

Couple

 

The Fundamental Process

 

Potential Applications

System Engineering

Industrial Engineering

 Engineering, Production, and Human Resource Management

 Complex Systems

Cloud Computing

Internet of Things

Social Simulations

Industry 4.0

Big Data

Cyber-Physical Systems

 

Fundamental Policies

1.  名不正,则言不顺;言不顺,则事不成。” (“If terminology is not corrected, then what is said cannot be followed. If what is said cannot be followed, then work cannot be accomplished. ”)

2.  君君、臣臣、父父、子子”(“Let the ruler be a ruler, the minister be a minister, the father be a father, and the son be a son.”)

3.  人在江湖,身不由己You cannot always do as you like.

4.  未雨绸缪Make hay while the sun shines.

5.  “All the world’s a stage, and all the men and women merely players. They all have their exits and entrances, and one man in his time plays many parts.”

Fundamental Symbols

(Nomenclature)

 

Topics

Symbol

Meaning

 

 

 

 

 

Acronyms

E-CARGO

Environments - Classes, Agents, Roles, Groups, and Objects

RBC

Role-Based Collaboration

AC

Adaptive Collaboration

AE

Agent Evaluation

RT

Role Transfer

RA

Role Assignment

GRA

Group Role Assignment

GRACAR

Group Role Assignment with Conflict Agents on Roles

GRACAG

Group Role Assignment with Conflict Agents on a Group

SGRA

Static group role assignment

DGRA

Dynamic group role assignment

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Fundamental

E-CARGO

id

The identification of an object, class, role, agent, environment, message, group, human, etc. 

C

A set of classes

c

A class

O

A set of objects

Or

The set of objects accessed by a role

o

An object

A

A set of agents

Ao

The set of agents who can potentially play a role

Ap

The set of agents who played a role before

Ac

The set of agents who are currently playing a role

Ag

The set of agents of group g

a, a0, a1, a2, …

Agents

M

A set of messages

A message

R

A set of roles

rc

The current role of an agent

Rp

The set of potential roles of an agent

Ro

The set of roles played before by an agent

r, r0, r1, r2,

Roles

Mr

The set of messages specified by a role

Min

The set of incoming messages specified by a role

Mout

The set of outgoing messages specified by a role

E

A set of environments

E

An environment

Q

The role range expressed by <l, u>

w [0, 1]

The weight of role

Re

The set of roles of an environment

B

The set of tuples < r, q, w>

Ce

The class of shared objects by all the roles  in an environment

G

A set of groups

g

A group

J

The set of assignment tuples <a, r> of a group

s0

The initial state of a system

H

A set of users

h

A human being

m

=|A|, the size of the agent set A

n

= |R|, the size of the role set R

0≤i, i0, i1, i2, …<m

The indices of agents

0≤j, j0, j1, j2, …<n

The indices of roles

N

The set of nonnegative integers

å

A system

The shared object in an environment

®

The set of requirements of a role

The set of qualifications of an agent

F

The message pattern

lm{any, some, all}

The label of a message

α

The space limit

β

The time limit

 

 

 

RT

Mc

The current role matrix Mc

Mc [i, j] {0,1}

To express if agent i is currently playing  role j, where 1 means yes and 0 no

Mp

The potential role matrix Mp

Mp [i, j] {0,1}

To express if agent i can potentially play  role j, where 1 means yes and 0 no

 

 

 

 

 

GRA

L

The role range vector whose dimension is n

L[j] N

The lower range of role j

U

The upper role range vector whose dimension is n

U[j] N

The upper range of role j

W

The role weight vector whose dimension is n

W[j] [0,1]

The weight of role j

Q

The qualification matrix whose dimensions are m × n

Q[i, j] [0,1]

The qualification value of agent i on role j

T

The role assignment matrix whose dimensions are m × n

T[i, j] {0,1}

To express if agent i is assigned to role j, where 1 means yes and 0 no

T*

The optimal assignment matrix that follows GRA

σ=

The group performance of GRA

 

 

 

 

 

 

GRACAR/G

 

Ac

The conflicting agent matrix of a group whose dimensions are m × m

Ac[i1, i2]{0,1}

To express if agent i1 is in conflict with agent i2, where 1 means yes and 0 no

nc =

The number of conflicts

na=

The number of required agents

pc= nc / [(m-1)/2]

The conflict rate

nac=

The number of assigned conflicts in the T corresponding to GRA

λ

The benefit obtained by GRACAR/G compared with GRA

 

 

 

 

 

AC

t

The time

GS::=<A(t), R(t), Q(t), σ(t), L(t), U(t), W(t)>

Group Snapshot, i.e., the state of a group at time t

σs =

The total group performance of SGRA in time τ.

σd =

The total group performance of DGRA in time τ, where there is p times of assignments, t0=0, and tp= τ

 

 

References

[1]     H. Zhu, “Role-Based Collaboration and the E-CARO model Revisted after a Decade”, IEEE Systems, Man, and Cybernetics Magazine (In Press), 2015.

[2]     H. Zhu, “Adaptive Collaboration Systems”, IEEE Systems, Man, and Cybernetics Magazine (In Press), 2015.

[3]     H. Zhu, “Avoiding Conflicts by Group Role Assignment”, IEEE Transactions on Systems, Man, and Cybernetics: Systems (In Press), 2015, DOI: 10.1109/TSMC.2015.2438690 .

[4]     Y. Sheng, H. Zhu, X. Zhou, and W. Hu, Effective Approaches to Adaptive Collaboration via Dynamic Role Assignment”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 46, no. 1, Jan. 2016, pp. 76 - 92.

[5]     H. Zhu, M. Hou, C. Wang, and M.C. Zhou, “An Efficient Outpatient Scheduling Approach”, IEEE Transactions on Automation Science and Engineering, vol. 9, no. 4, Oct. 2012, pp. 701-709.

[6]     H. Zhu, M. Hou, and M.C. Zhou, “Adaptive Collaboration Based on the E-CARGO Model”, Int’l J. of Agent Technologies and Systems, vol. 4, no.1, 2012, pp. 59-76.

[7]     H. Zhu, M.C. Zhou, and R. Alkins, “Group Role Assignment via a Kuhn-Munkres Algorithm-based Solution”, IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, vol. 42, no. 3,2012, pp. 739-750.

[8]     H. Zhu, and M.C. Zhou, “Efficient Role Transfer Based on Kuhn–Munkres Algorithm”, IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, vol. 42, no.2, 2012, pp. 491 - 496.

[9]     H. Zhu, “Role-Based Autonomic Systems”, International Journal of Software Science and Computational Intelligence, vol. 2, no. 3, July 2010, pp. 32-51.

[10] H. Zhu, and M. Zhou, “M–M Role-Transfer Problems and Their Solutions,” IEEE Trans. on Systems, Man and Cybernetics, Part A: Systems and Humans, vol. 39, no. 2, pp. 448-459, 2009.

[11] H. Zhu, Fundamental Issues in the Design of a Role Engine, in Proc. of The 9th International Symposium on Collaborative Technologies and Systems (CTS 2008), Irvine, California, 2008, pp. 399-407.

[12] H. Zhu, and M. Zhou, “Roles in Information Systems: A Survey,” IEEE Trans. on Systems, Man and Cybernetics, Part C: Applications and Reviews, vol. 38, no. 3, pp. 377-396, 2008.

[13] H. Zhu, and M. Zhou, “Role Transfer Problems and their Algorithms,” IEEE Trans. on Systems, Man and Cybernetics, Part A: Systems and Humans, vol. 38, no. 6, pp. 1442-1450, 2008.

[14] H. Zhu, and M. Zhou, “Supporting Software Development with Roles,” IEEE Trans. on SMC, Part A: Systems and Humans, vol. 36, no. 6, pp. 1110-1123, 2006.

[15] H. Zhu, and M. Zhou, “Role-Based Collaboration and its Kernel Mechanisms,” IEEE Trans. on SMC, Part C: Applications and Reviews, vol. 36, no. 4, pp. 578-589, 2006.

[16] H. Zhu, “The Role Mechanism in Collaborative Systems,” International Journal of Production Research, vol. 44, no. 1, pp. 181-193, 2006.