tions, and the ability to create, structure
and ‘rationalize’ the environment to fit
ones expectations and abilities (
leading, for example, to the design of organizations, institutions, and norms).
Following an increasing number of
researchers in both ABM and MAS that
in recent years have come to similar
7, 13, 18, 19 we claim that new
models of preference and belief formation are needed that show how behavior
derives from identities, emotions, motivation, values, and practices.
The endeavor required to construct
such agent models that are socially realistic requires the effort and the capabilities of both the MAS and ABM communities, bringing together formalization
and computational efficiency, and
planning techniques as in MAS, with
the ABM expertise on empirical validation and on adapting and integrating
social sciences theories into a unified
set of assumptions,
1 furthering the
fundamental understanding of social
deliberation processes, and developing techniques to make these accessible for simulation platforms. This
Viewpoint is therefore an appeal to join
the strengths of both communities toward sociality-based agents.
Without claiming a readily available
solution, we propose the concept of
sociality as the leading principle of
agency, as an alternative for rationality. Following the aforementioned
description of rational behavior, the
main characteristics of sociality-based reasoning are:
˲ Ability to hold and deal with inconsistent beliefs for the sake of coherence
with identity and cultural background.
That is, beliefs originate from other
sources than observation, including
ideology or culture.
˲ Ability to fulfill several roles, and
pursue seemingly incompatible
goals concurrently, for example, simultaneously aiming for comfort
and environmental friendliness, or
for riches and philanthropy.
˲ Preferences are not only a cause
for action but also a result of action.
Moreover, preferences change significantly over time and their ordering is
influenced by the different roles being
fulfilled simultaneously, which requires
the need to deal with misalignment and
˲ Action decisions are not only geared
Social abilities are central both in
ABM, where agents represent humans
and their interactions, and in MAS,
that enable game-theoretic analyses of
decision strategies, or provide interac-
tive virtual agents in varied situations.
It is precisely in this area where the
need for integration of ABM and MAS
is undoubtedly the most necessary. In
social simulation, the benefits of com-
bining MAS and ABM have been advo-
cated for many years, and are the focus
of the long-lasting workshop series on
Multi-Agent Based Simulation (MABS).
ABM has increasingly and successfully
been used for social simulations,
it is in the MAS area that fundamental
research on agent architectures imple-
menting psychological traits and social
concepts such as norms, commitments,
emotions, identity, and social order, has
been most prominent.
4, 5 Bridging these
somewhat parallel tracks requires a new
grounding for agent architectures.
Traditionally, one of the most salient
aspects shared by both ABM and MAS
approaches is the premise of rationality. This is derived from the traditional
definition of agents as autonomous,
proactive, and interactive entities where
each agent has bounded (incomplete)
resources to solve a given problem;
there is no global system control; data
is decentralized; and computation is
21 Agent rationality can
be summarized as follows:
˲ Agents hold consistent beliefs;
˲ Agents have preferences, or priorities, on outcomes of actions; and
˲ Agents optimize actions based on
those preferences and beliefs.
This view on rationally entails that
agents are expected, and designed,
to act rationally in the sense that they
choose the best means available to
achieve a given end, and maintain consistency between what is wanted and
what is chosen.
14 Even though multiple alternatives have been proposed,
in both the ABM and MAS approaches,
individual agents are still typically characterized as bounded rational, acting
toward their own perceived interests.
The main difference is that agent be-
haviors in ABM are used to capture the
dynamics of a system for analytical pur-
poses, grounded whenever possible on
existing data about system outcomes,
whereas MAS focuses on solving specif-
ic problems using independent agents,
through the formalization of the com-
plex goal-oriented processes, such as
the Beliefs-Desires and Intentions (BDI)
model proposed by Bratman20 or game-
The main advantages of such ra-
tionality assumptions are their parsi-
mony and applicability to a very broad
range of situations and environments,
and their ability to generate falsifiable,
and sometimes empirically confirmed,
hypotheses about actions in these en-
vironments. This gives conventional
rational choice approaches a combina-
tion of generality and predictive power
not found in other approaches. In fact,
rationality approaches are the basis of
most theoretical models in the social
sciences, including economics, politi-
cal science, or social choice theories.
Unfortunately, from a modeling perspective, real human behavior is neither
simple nor rational, but derives from a
complex mix of mental, physical, emotional, and social aspects. Realistic applications must consider situations in
which not all alternatives, consequences, and event probabilities can be foreseen. This renders rational choice approaches unable to accurately model and
predict a wide range of human behaviors.
Toward Social Agents
Human sociability refers to the nature,
quantity, and quality of interactions
with others, including both pro-social,
or cooperative, behaviors, and conflict,
competitive, or dominating behaviors.
Sociability is also the ability to influence
others, by changing their behaviors,
goals, and beliefs, the emotional reaction to others and to the environment,
and how actions are affected by emo-
from a modeling
real human behavior
is neither simple