The Institutional Stance in Agent-based Simulations
Giovanni Sileno, Alexander Boer and Tom Van Engers
Leibniz Center for Law, University of Amsterdam, Amsterdam, The Netherlands
Normative Systems, Story Animation, Institutions, Agent-roles, Agent-based Simulation, Jural Relations,
Legal Knowledge, Non-compliance, Multi-Agent Systems.
This paper presents a multi-agent framework intended to animate scenarios of compliance and non-compliance
in a normative system. With the purpose of describing social human behaviour, we choose to reduce social
complexity by creating models of the involved agents starting from stories, and completing them with back-
ground theories derived from common-sense and expert knowledge. For this reason, we explore how an
institutional perspective can be taken into account in a computational framework. Roles, institutions and
rules become components of the agent architecture. The social intelligence of the agent is distributed to sev-
eral cognitive modules, performing the institutional thinking, whose outcomes are coordinated in the main
decision-making cycle. The institutional logic is analyzed from a general simulation perspective, and a con-
crete possible choice is presented, drawn from fundamental legal concepts. As a concrete result, a preliminary
implementation of the framework has been developed with Jason.
In the last decades, software engineering has been
moving away from machine-oriented views of pro-
gramming towards concepts and abstractions more
closely reflecting the way in which humans conceive
the world. Multi-agent systems have been introduced
to develop complex services, typically strongly char-
acterized by interactions between entities, but, differ-
ently from other distributed systems, they often inte-
grate concepts derived from philosophy or psychol-
ogy, like the Belief-Desire-Intention paradigm. Fur-
thermore, multi-agent systems are successfully used
for simulations in economics, sociology, and biology
(in that case the term ABM - Agent-based modelling
is preferred). However, although since a few years
there has been an active research interest on norma-
tive multi-agent systems, there is no equivalent de-
velopment about ABM simulations from a legal per-
spective. Although there are interesting overlaps with
these studies there is an intrinsic, and important, dif-
ference of perspective. With the first approach, con-
ception, we design and create artefact systems, which
are largely under our control, trusted, and highly pre-
dictable (for example, electronic institutions). With
the second approach, interpretation or discovery, we
interpret the relevant events against a background of
See for example in (Batten, 2000; Duffy, 2006).
systems, in our case mostly of human origin, some
of which we trust to work in certain ways, and some
others we only guess at. The second is the arena
where ABM actually plays a role, and where this
study should be placed.
A (soft) Evolution. In the computational world, all
starts (and ends) with imperative commands in the
form of instructions. Instructions can be grouped in
procedures. Data passes from numeric to string, uni-
fied in arrays, structures, and finally instantiated in
objects, elements of classes defined by data struc-
tures and methods handling that data. Objects do not
perform any action independently, they can only be
. An agent is instead a proactive entity (agere
in Latin means to do, to achieve, to lead). The basic
type of agents is the behavioural agent: it has appar-
ent autonomy, executes a plan composed by actions.
The next step in this evolution is brought by inten-
tional agents, that show autonomy, proactiveness, re-
activeness and social ability. These four character-
A practical definition in object-oriented programming
may be different.
Sileno G., Boer A. and Van Engers T..
The Institutional Stance in Agent-based Simulations.
DOI: 10.5220/0004257602550261
In Proceedings of the 5th International Conference on Agents and Artificial Intelligence (ICAART-2013), pages 255-261
ISBN: 978-989-8565-38-9
2013 SCITEPRESS (Science and Technology Publications, Lda.)
istics are the references of a very important human
capability: mentalization (Fonagy and Target, 1997).
Humans are able to mentalize, i.e. to create an inter-
nal representation of an external agent, in a way that
its behaviour can be predicted and, according to the
intentional approach, explained in terms of attitudes,
for example using concepts like beliefs, desires and
. This is an innate exercise of modelling
for humans, and its importance comes from the fact
of being commonly used as representation of reality.
As a matter of fact, humans tend to mentalize not only
individuals, but also communities, cultures, organiza-
tions, nations.
Instructions, Habits, Rules. Every human individ-
ual or group, having a goal, sets the more adequate
means, or better, those considered as the more ade-
quate means to achieve it. The means/end relation-
ship creates generally an instruction of conduct of that
type: If you want to reach the goal A, you have to
do the action B”. All these instructions could be very
different in aim, content, scope of validity, or subjects
involved. Moreover not all the instructions are estab-
lished in the previous form (to do), but also in a qual-
ification or state discriminant form (to be). If the for-
mer type requires the capability of executing tasks and
in a larger sense of planning, the latter subsumes the
existence of another process: the situation (or state)
recognition. Anyway, all instructions have something
in common: they are propositions that aim to influ-
ence the behaviour of individuals and/or groups, lead-
ing their actions towards certain objectives more than
others. In a social agglomerate, similar instructions
could be part of common knowledge, or cultural con-
ventions, social habits and social rules. Only effective
legal norms become part of the social rules.
Choice of Conduct. Recognition of the present
state, and then planning tasks towards a goal are parts
of a typical problem solving cycle (Breuker, 1994),
that could be seen as the main core of the agent activ-
ity. The choice of conduct is then a sort of preference
order between possible plans of actions, considering
eventually associated economic costs or some poten-
tial side-effects. But how are norms related to the
choice of conduct? (Neumann, 2010) has found in the
normative multi-agent literature two main philosoph-
ical approaches: deontic and consequentialistic. The
first considers norms as cognitive objects. A deontic
conceptualization of norms typically emphasises that
norms are in itself a reason for action. On the other
The intentional stance has been introduced by Dennett
(Dennett, 1987).
brute fact
institutional fact
Figure 1: Institutional perspective.
side, with a consequentialistic approach, agents con-
sider the possibility of breaking the norm as one of
the alternative choices. Stated differently, the latter
treats norms as behaviour regularities, and, for this,
they may be described for example with game theo-
retic models
. The two different perspectives result
in two potential attitudes towards norms; our target
ABM framework should integrate both of them.
Institutions. In (Searle, 1969) an interesting point
is traced about the difference between normative (or
regulative) and constitutive rules. The former regu-
lates existing forms of behaviour. For example, the
rules of polite table behaviour have been introduced
later than the eating activity. Eating existed and ex-
ists anyway, with or without these rules. But, at the
contrary, the rules of playing chess have created the
possibility of playing chess. Searle extended these
examples. “The institutions of marriage, money and
promising are like the institutions of baseball and
chess in that they are systems of such constitutive
rules or conventions.
Generalizing, we can say that an institution is an
intentional social collective entity (Boer, 2009), de-
fined by certain rules and some institutional facts. It
is collective and intentional, simply because a group
of people recognizes and intends its existence. This
concept of institution unifies games, social informal
norms and legal norms
From a game theory point of view, a social rule elim-
inates certain strategies for each of social convention the
agents, and thus induces a sub-game. “For a given agent,
a social law presents a trade-off; he suffers from loss of
freedom, but can benefit from the fact that others lose some
freedom. (Shoham and Leyton-brown, 2009)
According to the institutional perspective, law is an
institution whose purpose is to create normative order via
formalization (MacCormick, 1998). Legal facts are de-
pendent on legal norms and observed through legal norms.
Law’s ‘truth’ is different from reality, psychological or so-
cial truth. “In court proceedings, the ‘truth’ of the facts is
ultimately determined not by criteria employed in empirical
sciences but by those provided by procedural and substan-
A general institutional perspective has been visu-
alized on Fig. 1. Two realities coexist: a brute reality
and an institutional reality. Filtered by the constitu-
tive rules associated to the institution, only few of all
real facts determine an institutional fact. Stated dif-
ferently, these real facts are events triggering a change
in the institutional reality. They will be called consti-
tutive facts, and typically are created through a consti-
tuting act. Institutional rules create new institutional
facts from existing institutional facts. Finally, norma-
tive rules convert institutional facts into instructions
of behaviour, and if the choice of conduct of the agent
goes accordingly, they perform an actual normative
Institution as Agents. As pointed out in (Boer and
Van Engers, 2011) externalization of rules and social
organization is philosophically defensible, and often
an efficient solution from a system engineering point
of view. However, for ABM simulation purposes, this
is not a natural choice. During a theory construction
session with legal experts, it is more natural to think
of the agent as provided with an internalized artefact,
of arbitrary complexity, embedding the social factor.
Following the terminology used in (Chu, 2011), we
consider that there is no institution an sich in the
brute reality. It exists only in the form of conceptual-
ization, internal to each agent. The collective flavour
of this type of entity is given by a similar represen-
tation in each individual of the community, or, better,
may be regarded as an instance of emergence. At a
macro-level, institutions arise, evolve and function as
patterns of social self-organization, which goes be-
yond the conscious intentions of the individual hu-
mans involved, but still, it is generated by a micro-
level, individual behaviour.
From the agent’s point of view, to be comply-
ing with an institution means to have a representa-
tion of the present institutional state (rules and facts)
and behave accordingly with the normative rules gen-
erated by reasoning with it. This is a specific form
of the equation T hinking = Knowledge + Reasoning
(Kowalski, 2010). This kind of modularization un-
veils an architectural possibility: to consider the insti-
tution itself as a cognitive agent, dividing the model
in separate but interconnected sub-models.
Scenarios and Roles. Humans continuously learn
about the social institutions around them. The law
tells us that a sale involves a buyer and a seller, that it
deploys an offer and an acceptance, and that it leads
tive legal norms” (Tuori, 2006). This observation could be
extended also to informal institutions.
rule 1
institution A
role X
role Y
role Z
rule 2
rule 3
institution B
institution C
Figure 2: Architectural components.
to an obligation on the buyer to pay, and an obligation
on the seller to deliver. It does not entail that the seller
and buyer feel harmed if the other party does not meet
their obligations, it does not tell what they will do if
that happens, it does not tell when an offer will be
acceptable, but we do have expectations about these
things. In fact, analyzing a certain context, we pro-
vide a plausible (at least, according to us) intentional
model of the involved agents, using our knowledge of
the domain, analogies with other experiences and our
mentalization capability.
In doing this, we use prototypes of normal be-
haviours (on which we will plausibly base our own
behaviour, at the place of that agent), and also pro-
totypes of the behaviours of non complying, faulty
agents. Almost without noticing, we are not talk-
ing any more about individual agents. Identifying the
contextual common patterns between individual cases
(and their rationality), we are writing down typical
scenarios (as patterns of social interaction) with the
typical (social) roles that agents play in them. Such
roles are associated to certain beliefs, plans (result-
ing in actual actions) and goals. Nothing forbids an
agent to play simultaneously several roles (Fig. 2)
and viceversa.
Constitutive and institutional rules could be expressed
in the form of normative conditionals (Sartor, 2006):
i f CONDIT IONS then
CONCLUSION. Conditions
are constitutive and institutional facts. The conclu-
sion is a new institutional fact. Institutional facts con-
cern institutional entities or jural relations. Every new
institutional fact typically draws a new configuration
of the jural relations between the agent entities exist-
ing in that institution. This new configuration is a re-
sult of the modus ponens or forward reasoning applied
through some deontic rules. We have taken as a start-
ing point the fundamental legal concepts elaborated in
(Hohfeld, 1917), completed and further developed in
(Sartor, 2006), but another choice could be possible
as well.
no-right privilege
disability immunity
Figure 3: The two Hohfeldian squares: directed obligations
and power concepts.
Directed Obligations and Permissions. Simplify-
ing, the first Hohfeldian square defines the directed
obligations between two actors, and it introduces four
different deontic concepts: obligative-right, obliga-
tion, privilege and no-right (Fig. 3). An obligative-
right, strictly defined, is one’s enforceable claim
against another (progressive form). Privilege is one’s
freedom from the claim of another one (regressive
form). Like the cited author, we added to these
concepts the permissive-right, different to obligative-
right. This is in fact not completely reducible to the
idea of a directed obligation.
Power. The second Hohfeldian square refers to the
concept of power, with four new concepts: action-
power, subjection, disability, immunity (Fig. 3).
Action-power consists in the agent’s power to deter-
mine a normative position involving a certain agent
performing a certain action. On the contrary, disabil-
ity defines the impossibility (no-power) to achieve a
certain normative position.
Following the analysis found in (Vatiero, 2010),
we extend their use also to not strictly legal aspects.
In the case of the buyer and seller, if the buyer is com-
pletely dependent to the seller because he is the only
one in possession of the good he wishes, he is actu-
ally in a subjection position towards the seller for his
pricing choices. On the other hand, the seller is in a
power position and can eventually raise the price. For
the buyer, the only way to avoid this subjection is to
stop wishing that good (which is not always possible),
or finding another seller with a better price.
Generalizing this example, an action (in the form
of an investment) of the agent may bring about a
change of his institutional position. At the same time,
contextual factors may determine an endogenous en-
forcement of power: the fact that the buyer needs that
good and that the seller is the only one to sell deter-
mines the power positions between the two agents,
and this is not influenced by the agents’ consciousness
of these positions. However, renewing the Bacon’s
knowledge is power, an agent that is able to recognize
the contextual state, and knows how to change it ac-
cordingly to his own interests, has the action-power to
modify the power positions in the institution.
Coordination and Competition Dimensions. The
agent behaviour associated to an institution could be
generally ascribed along two main axis: (social) co-
ordination and (economic) competition. Simplifying,
the first covers the rules of the “game”, the second the
knowledge about how to “play the game” within the
rules. The rules of fair competition are particularly
meaningful. They are introduced in order to avoid
that one player attains a position too strong compared
to the others, limiting or blocking de facto their pos-
sibilities of action and resulting in a failure or degen-
eration of the institution.
Practical Normative Indications. In order to have
a successful normative action, the jural relations re-
sulting from the institution should have some con-
sequence on the agent’s behaviour. Focusing on the
decision-making cycle, only four practical normative
indications are important for the agent: you can
you can not *, you must *, you do not have to *.
In general, * may be related to actions (to do),
or states (to be), or results (to bring about). The
state subsumes a state recognition, i.e. the possibil-
ity that a certain group of perceived/believed condi-
tions counts as a certain state. For this reason, defin-
ing a fact as a reified statement about something, a
state/situation is a second order fact, requiring a qual-
ification. The bring about requires a plan toward the
objective/result, and a result can be both a fact or a
constitutive facts
practical indications
you can *
you can not *
you must *
you do not have to *
constitutive facts
to be brought about
request for change
how to be allowed to *
how to be allowed not to *
how to be obliged to *
how to be obliged not to *
Figure 4: Forward and backward reasoning in institution.
Institutional Backward Reasoning. The process
analyzed until now, from constitutive facts to practical
indications, is a forward-chaining procedure (condi-
tion to conclusions). It is interesting to consider also
the other way around, the backward-chaining (con-
clusion, if condition): which conditions have to be
brought about to reach a different institutional config-
uration? More answers might be possible to the same
question, in the form of alternative sub-goals aiming
to the same objective (Fig. 4).
If the logic describing rules and jural relations
is consistent, forward and backward chaining rela-
tions can be automatically inferred one from the other.
However, here we emphasize the possibility to sim-
ulate in such a framework also a wrong conceptu-
alization of the institution, conflicting rules, faulty
logic, using for example a non-monotonic approach
and handling separately the forward and backward re-
Normative Plans. Put in a simple form, in order to
be complying, an agent should: (a) check, before per-
forming an action, if he has the permission to do that,
and if not, evaluate to drop the plan involving that ac-
tion, (b) add as goal the performance of any new obli-
gation. On the other side, in order to be socially reac-
tive in a context in which non-complying behaviours
are possible, an agent should: (c) be able to recognize
not complying events or situations
, (d) have a main-
tenance plan with a monitoring purpose, (e) react to
the occurrence of not complying events.
In this context can has only the meaning of being al-
lowed to (and not, for example, of being able to).
Here we are considering * defined always in a positive
form, but it is easy to demonstrate that the negative forms
can be reduced to one of these. Furthermore, all four po-
sitions could actually be expressed using only one functor,
nevertheless we prefer to use the proposed expressions, as
they are more pertinent to focus on behaviour.
Starting from the famous Wason’s selection task, sev-
eral studies have been conducted in behavioural psychology
with the purpose of assessing the heuristics involved in hu-
man reasoning. Part of these results, relevant for our scopes,
are described in (Cosmides and Tooby, 2008).
Using the terms previously defined, an event is a fact,
observed or acknowledged by the agent, and a situation is a
state, in the sense of fact of facts.
Problem Solving Cycle of the Agent. From the
point of view of the modeller, it is worth to con-
sider the possibility to associate different attitudes
towards norm to each institutional component. Fol-
lowing the consequentialistic approach the agent will
consider plans containing violations of norms. Fol-
lowing the deontic approach he will abolish any plan
that includes non-complying actions or results. In
both cases, some kind of meta-reasoning about plans
has to be implemented. For this reason, this inves-
tigation would be part of the more general conflict
resolution problem for norm vs desire conflicts, to be
analyzed altogether with plan vs plan (when multiple
alternative plans are possible to reach the same goal),
desire vs desire conflicts (caused for example by con-
flicting goals between simultaneous roles), norm vs
norm (between institutions) and rule vs rule conflicts
(for an internal institutional conflict)
. From a gen-
eral point of view, we are not aiming for autonomous
agents that create their own plans from first princi-
ples, but that evaluate and choose between existing
plans according a given rationality.
An implementation of the framework has been devel-
oped for Jason, a MAS platform based on an exten-
sion of the AgentSpeak(L) programming language
(Bordini et al., 2007). The source code is available on
our site
and consists in different modules handling
the creation of institutions, the institutional logic, the
institutional communication and a coordination so-
lution that follows a deontic approach towards nor-
mative indications. At the moment, two examples
are included, not presented here in details for space
constraints. The first one describes a mythological
story of non-compliance (Achilles avoiding the Tro-
jan war): an example of how a story could be ani-
mated, starting from a narrative, interpreting it, and
adding background theories derived from common-
sense knowledge. The second one is an institutional
model of the sale process, as described in common
Many of these conflicts are consequence of the distribu-
tion of the the institutional thinking to multiple entities, thus
requiring adequate coordination functions. However, this is
also a good representation of our daily experience about the
choice of conduct, when we have to take choices between
our social roles expectations (for example as members of a
family, researchers, citizens, etc.).
Jason is based on logic programming and implements
a BDI architecture for cognitive autonomous agents.
12 jason
law/the Dutch civil code, backing several buyer/seller
The intent underlying our research is to (re)connect
normative (including legal) reasoning with other
forms of reasoning. Particularly, we are interested in
the role that (legal) norms play in social structures and
how norms influence human behavior in those struc-
In the current approach, typical strategy decision
problems for a given game do not take explicitly into
account the possibility of the player to behave avoid-
ing a rule, or forcing the interpretation of the rule to-
ward its interest, if the regulator (consciously or not)
left some ambiguity. The second case is not so com-
mon in games, but in the case of legal order, lacunae
of law are practically unavoidable and within limits,
desirable. This is part in fact of the human collec-
tive adaptation and social reasoning capabilities. In
that way, humans question rules, both directly or in
an involuntary way (for example, in the case of lack
of knowledge or misunderstanding of the rule) and de-
termine with their actions if social rules are successful
or not in their normative intentions. Furthermore, hu-
mans do not play ever a single game at once. In a
broader sense, humans are always players of several
games simultaneously, or to put it differently, they are
agents concerned in the same moment by many dif-
ferent institutions, sometimes conflicting, created by
habits, social rules and legal order.
In the present paper we propose a framework that
aims to take explicitly all of this into account. Our ob-
jective is a partial alignment of the representations of
law with actual social structures and existing imple-
mentations of law. Descriptions of those are present
for example in legal narratives, in the form of court
decisions or anecdotes by legal experts, where a con-
structed theory, at least partially, is explicitly stated.
Thus, using our framework, models of agents or roles
involved in a social scenario could be animated, out-
lined from a story, enriched with knowledge from
experts and/or referring to the sources of regulation,
with the possibility of integrating game-theoretic be-
havioural theories. As operative result, such a sim-
ulation would furnish a support to understand the so-
cial (institutional) dynamics: validating the domain of
conceptualization of the experts, making predictions,
suggesting improvements to regulations.
Along with this paper, a preliminary implementa-
tion has been developed, using an existing multi-agent
system platform. Although successful, this experi-
ence showed the necessity of creating (or extending)
a platform with an explicit ABM approach in order
to attain a full computational deployment of the pro-
posed framework. This is one of the directions of our
future research.
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