Systems, Man & Cybernetics - July 2015 - 28

and systems helps people undertake collaboration in a
more efficient and satisfactory manner. In practice, such
ongoing research offers a continuous cycle of improvement. That is, a good theory of collaboration leads to
more effective collaboration systems. On the other hand,
advancements in technologies and systems allow collaboration theories to advance.
From the viewpoint of sociotech systems and our preferred taxonomy, collaboration can be divided into the following categories:
◆ natural collaboration among people in the real world
◆ computer-supported cooperative work (CSCW), which
is collaboration involving people through computers
and related technologies
◆ human-computer interaction (HCI) or human-
machine interaction, which is collaboration that
occurs between people and computers (machines)
◆ distributed systems [including multiagent systems
(MASs)] are collaborations that take place among systems (or agents)
◆ a computer system is a collaboration among system
components.
At the abstract level, collaboration is composed of two
major intersupplementary aspects: task distribution and
coordination, i.e., more attention paid to task distribution
would decrease the effort on coordination or vice versa.
RBC focuses on providing better task distribution to save
the effort of coordination, which is believed to be more
complex than task distribution. Coordination has more
complex problems than does task distribution, where
complex problems cannot be formalized by mathematical
symbols and expressions or can be formalized but solved
in nonpolynomial time.
A computational methodology can be used to discover,
consider, model, understand, and solve the real-world problems with the help of computer-based systems. RBC is such
a methodology, using roles as the primary underlying mechanism to facilitate collaboration activities [58]-[88]. RBC was
proposed in 2003 [58], [67], [68] and has been the subject of
research and investigation for more than a decade. During
this period, many significant challenges have arisen [58]-[88]
(see the "Problems Discovered But Not Yet Fully Solved" section), including the role transfer problem (RTP), the group
role assignment (GRA) problem, and the GRA with conflicting agents (GRACA) problem. Amazingly, these challenges
have interesting parallels to engineering problems in the real
world. Solving such problems satisfies the requirements of
good engineering practice. Previous research has solved typical problems in role assignment and role transfer [58]-[88].
GRA [80] has arisen as an important challenge and has been
revealed as a complex task in the life cycle of RBC (Figure 1),
i.e., agent evaluation, role assignment, and role transfer. GRA
aims at finding an optimal assignment from roles to agents
with the agent evaluation result [71], [84], and it significantly
affects the efficiency of collaboration and the degree of satisfaction among the members involved in RBC.
28

IEEE Systems, Man, & Cybernetics Magazine July 2015

Through continuous effort, RBC-related research has
been developed into a methodology of discovery in the
collaboration-systems research field. The RBC-related
research has been done by taking advantage of formalizations and abstracting system components, at differing
levels, by mathematical expressions. The instances of such
abstractions are easily found in real-world scenarios. The
problems discovered through RBC research have direct
parallels in the real world (see the sections "Problems
Discovered and Solved by RBC" and "Problems Discovered
But Not Yet Fully Solved").
The fundamental model of RBC is E-CARGO. E-CARGO
is highly abstracted from natural and man-made systems,
in particular, collaboration systems. Many researchers
may find that their systems involve components similar to
those in the E-CARGO model.
RBC and the E-CARGO model bring in new visions to
a collaboration system by dividing the system into six different classes of components, i.e., classes, objects, agents,
roles, environments, and groups. Among them, many
relationships can be formalized through mathematical
symbolization. In this way, many problems previously considered to be too complex to solve with computer-based
systems can now be well defined and, finally, solved.
This article intends to provide a brief introduction to the
E-CARGO model and RBC while advocating the need for
further investigation of these topics.
The Components of the E-CARGO Model
With the E-CARGO model [84], a system R can be defined
as a nine-tuple R : : =1 C, O, A, M, R, E, G, s 0, H 2, where
C is a set of classes, O is a set of objects, A is a set of
agents, M is a set of messages, R is a set of roles, E is a
set of environments, G is a set of groups, s 0 is the initial
state of the system, and H is a set of users. In such a system, A and H, and E and G are tightly coupled sets.
A human user and his or her agents may perform a role
together. Every group should work in an environment. An
environment regulates a group. Note that E-CARGO is an
abstract model, and it is developed continuously. Investigations may emphasize different aspects in different ways.
In the following descriptions, c, o, a, , r, e, g, and
h are used to denote an element of C, O, A, M, R, E, G,
and H respectively. If S is a set, S is its cardinality.
If a and b are objects, a.b denotes b of a or a\s b; and
" a, b, f , denotes a set of enumerated elements of a, b,
and others. If a and b are real numbers, 6a, b@ and 6a, b h
denote the set of all the real numbers between a and
b, where the former includes both a and b, but the latter includes a but not b. If Y is a vector, Y6i @ denotes
the element at its i th position. If Y is a matrix, Y 6i, j@
denotes the element at the intersection of row i and column j in Y. N denotes the set of natural numbers or,
more exactly, nonnegative integers, i.e., " 0, 1, 2, 3, f , . In
the following discussions, components instead of concepts are used to emphasize that the elements in the

Table of Contents for the Digital Edition of Systems, Man & Cybernetics - July 2015