Self-organisation and self-evolution is evident in physics, chemistry, biology, and human societies. Despite the existing literature on the topic, we believe self-organisation and self-evolution is still missing from the IT tools (whether online or o ine) we are building and using. In the last decade, human interactions have been moving more and more towards social media. The time we spend interacting with others in virtual communities and networks is tremendous. Yet, the tools supporting those interactions remain rigid. This position paper argues the need for self-evolving software-enabled communities, and proposes a roadmap for achieving this required self-evolution. The proposal is based on building normative-based communities, where community interactions are regulated by norms and community members are free to discuss and modify their community's norms. The evolution of communities is then dictated by the evolution of its norms.
The concept of social self-organisation has deep roots in political theory. In the Leviathan, Hobbes expresses the idea that the social structure, the State or res publica, is the result of a social contract or pact. The social contract is an agreement among free individuals in order to surrender power to a central authority in order to get a guarantee of peace. In essence, a social contract is the implicit acceptance of self-limiting individual freedom in order to guarantee self-preservation and a better life. The concept of social contract implies that individuals re ect on the community governance in order to decide on the means to reach commonwealth.
This capacity of individuals to re ect and decide on community governance is missing in the IT tools we are currently building. How individuals interact is decided by groups of engineers that design tools, determine the individuals' privacy levels, hinder some from performing certain tasks, and all this without the individuals having a say. We argue that it is time for us to take control of the evolution of our own virtual communities, which we refer to as softwareenabled communities | examples of such communities are those based on social networks or any other community whose management relies on software, such as customer relationship management systems (CRMs) or conference management systems. To address this issue, we propose normative-based communities, where community interactions are regulated by norms and community members are free to discuss and modify their community's norms (or social contracts), while respecting their free will. The roadmap for self-evolution is then dictaded by the lifecycle of norms, and the research required for supporting this lifecycle is varied and multidisciplinary | from social sciences and legal studies, to learning mechanisms, agreement technologies, natural language processing, formal logics, norm enforcement and regimentation, human computer interaction, and other software engineering techniques.
It is true that the notion of self-organisation is not new. Self-organisation,
in general, refers to how a system reorganises to adapt to changes to its goals
or environment, where the reorganisation is driven from within the system as
opposed to some external control. In many cases, self-organisation is associated
with emergence, where a structure appears at a higher level without it being
represented at a lower level. Self-organisation has been studied in a number
of areas, such as biology, chemistry, geology, sociology, as well as information
technology [
In this paper, however, we do not propose to follow traditional self-organisation AI techniques, but to open a new direction in AI research with a novel method for self-evolving software-enables communities. The proposed research is original in the sense that we do not simply talk about self-organising software that usually imitates existing natural systems, but we study how the human users' evolving needs consciously direct evolution. We essentially propose to provide the human users with learning mechanisms that help them learn the best evolution path, along with agreement technologies that help them discuss, argue, and agree on their preferred path of evolution. The system then takes care of the formalisation, operationalisation, and enforcement of the agreed upon norms. This is a fundamentally di erent approach from existing self-organising systems. 2
In this paper, we argue that it is time for us to take control of the evolution of our own virtual communities. To address this issue, we propose normativebased communities, where community interactions are regulated by norms and community members are free to discuss and modify their community's norms.
Norms are the rules that govern behaviour in groups and societies [
We adopt the idea of using norms to control, or mediate, community behaviour. This is motivated by the fact that software is usually engineered based on some notion of norms in mind; furthermore, the use of norms allows human users to discuss their interactions without the need for any technical knowledge about the software actually mediating their interactions. We note that by specifying a community through its norms, the evolution of the community becomes dictated by the evolution of its norms. As such, the evolution of software-enabled communities may be depicted by the lifecycle of norms, as illustrated by Figure 1. ! coBmimrthunoitfyNmoermmbse:rs collectively decide on their norms
Norms Community Interactions
Automated " Formalisation of Norms: norms are translated from natural language to a formal specification $ EnforcAeumteonmtaotefdNorms: software ensures community interactions follow the norms
Formalised
Norms Software # Operationalisation of Norms:
Automated software is modified to incorporate the norms
We divide the lifecycle of norms in a software-enabled community into four di erent stages. In the rst stage, community members discuss and agree on their community's norms. If community members do agree on a new set of norms, then the norms' lifecycle enters its second stage, where the agreed upon norms are automatically translated into some formal speci cation. Given the formal speci cation of norms, the lifecycle then enters the third stage, where the softwareenabled community interactions are modi ed to operationalise the new norms. Finally, as the software runs to mediate community interactions, norms are enforced by ensuring that community interactions follow the agreed upon norms. The details of these four stages are presented next.
In this stage, community members propose norm modi cations (including the abandoning and adoption of norms), discuss the di erent proposals amongst themselves, and collectively agree on their community's new (or modi ed) set of norms.
An interdisciplinary research is highly recommended at this stage. For example, social sciences can help understand the emergence of norms, their social function, their impact on behviour, as well as understand the possible deviance from norms. Legal studies can help understand the legal aspects of norms, such as the enforcement of norms, the e ectivity and validity of norms, and the resolve of con icting norms. Learning mechanisms can help learn from a community's past experience, or a similar community's past experience, and suggest norm modi cations accordingly. Finally, to aid the collective agreement on community norms, agreement technologies will be needed.
Concerning learning mechanisms, learning from data has been one of the main
sub elds of arti cial intelligence [
Concerning agreement technologies, we note that this eld is one of the vibrant and active elds in multiagent systems. Agreement technologies aim at helping individuals collaboratively reach a decision, which is crucial when individuals are intelligent and autonomous, having their own goals and agendas to ful l. The eld is based on a number of models and mechanisms, such as argumentation and negotiation mechanisms, social choice theory and voting mechanisms, and trust and reputation models.
Argumentation theory uses logical reasoning to illustrate how conclusions
may be drawn in cases of uncertainty and con ict. Argumentation frameworks
in multiagent systems [
Social choice theory is concerned with the representation and aggregation of
individual preferences. Voting mechanisms and ranking systems are considered
to fall under the social choice category. Social choice theory studies a variety of
aspects, such as the manipulation of a voting rule [
A common issue that arises in building open distributed systems is the issue
of trust and reputation. Trust has become an increasingly important concept in
computer science [
Roadmap: In the context of self-evolving communities, research in the
information and computer Science eld should focus on two main issues. (1) We
should aim at building a system that is capable of automatically suggesting norms
that can help improve the quality of interactions in a community, based on
learning from similar past experiences. Improving the quality of interactions may refer
to a number of issues, such as improving the individual user satisfaction, or
improving the e ciency of the interactions by helping community members achieve
their goals faster and easier. We note that learning mechanisms may also be
combined with other techniques, such as analogical reasoning [
Norms agreed upon by community members need to be formalised in a language that can be understood by the system mediating community interactions. We expect community members to be non-technical people who discuss and specify norms in natural language. An automatic translator is then needed to translate the norms from their natural language speci cation to some formal speci cation that is comprehensible by the system.
The research that should support this stage should focus on natural language processing, which will help perform the automatic translation, and formal logics, which will de ne the formal language used to specify norms.
Concerning natural language processing, machine translation [
Concerning the formal speci cation of norms, existing approaches may be divided into two main categories: declarative approaches and procedural ones. We note that in this paper, we refer to the declarative approaches as norms and the procedural ones as interaction models. Declarative formalisms are concerned with the expressiveness of norms, the formal semantics, and how to resolve con icts arising from an inconsistent set of norms. Declarative approaches are usually based on deontic logic, which is the logic of duties. They deal with concepts like permissions, prohibitions, and obligations, which help specify who can do what, under what conditions, and so on.
Deontic-based policy languages have been used widely in hardware systems
and networks for security reasons, trust negotiation, access control,
authorisation, and so on. [
In multiagent systems, several deontic based formal logics have been proposed
for de ning a normative speci cation of agents interaction, such as [
Roadmap: In the context of self-evolving communities, research should focus on two main issues. (1) We should aim at building an automatic translator that can translate norms speci ed in a natural language into some formal logic. (2) We should select, or design, a logic that ful lls the following three requirements: i) it should be expressive enough to capture the community members' needs; ii) it should be compatible with the natural language processing technique that needs to translate norms speci ed in natural language into the logic; and iii) it should be compatible with the software system that needs to operationalise those norms. The outcome of this research work would be to have the agreed upon norms translated into some formal logic that is ready to be operationalised by the system. 2.3
Given a formal speci cation of norms, the ultimate goal is to enforce those norms. One approach to achieve this is through what is known as norm regimentation. In other words, the system mediating community interactions needs to be modi ed in order to operationalise those norms.
The literature provides a variety of solutions that deal with specifying and
regulating interactions in multiagent systems based on the concept of following
social norms [
Two speci cally interesting approaches are electronic institutions [
The lightweight coordination calculus (LCC) [
In the context of self-evolution, it is important to build a system whose
interaction models can operationalise norms requested by its uers. We note,
however, that not all norms are capable of being operationalised. For example, in
an e-commerece context, the system can operationalise the norm that states that
a buyer cannot rate the seller more than once, as the system can actually prevent
the buyer from doing so. However, the system cannot operationalise a norm
that states that only people with su cient credit can bid, as credit is private
information that cannot be accessed and assessed by the system. To deal with
norms that cannot be operationalised, alternative norm enforcement methods
will need to be applied, such as applying sanctions (punishments and rewards).12
In this case, the system will need to ensure the enforcement of un-operationalised
norms by checking the members' abidance to those norms and enforcing the
appropriate sanctions accordingly. To achieve this, it is important to design a
lightweight computational norm enforcement model that allows for the detection
of norm violations and the application of remedial actions. This work may build
upon existing work, as the literature is rich with norm engines that may be used
for resolving con icting norms and applying appropriate sanctions [
Roadmap: In summary, in the context of self-evolution, research should focus on two main issues: (1) building a mechanism that allows the system to operationalise the norms agreed upon by the community members; and (2) building a norm enforcement model that can check members' abidance to unoperationalised norms and enforce appropriate sanctions accordingly. The outcome of this research work would be to have a system that is capable of enforcing the norms agreed upon by the community members. 2.4
Finally, running the software that mediates community interactions will allow members of the community to interact, while ensuring the enforcement of the norms. The research that will support this stage will need to focus on human computer interaction techniques that are required to ensure an intuitive, user friendly interaction for non-technical community members. Research will also need to focus on software engineering techniques to ensure e cient community interactions. However, the context of self-evolution imposes an additional and critical challenge: how can the system be modi ed at runtime when di erent members may still be interacting together? Indeed, it is very unrealistic to assume that all members will need to complete their current interactions successfully and pause any future interactions for the system to get modi ed (as future interactions will need to follow the new norms). As such, research will need to address the issue of seamlessly adapting the system at runtime, and it may take inspiration from existing software compatibility models that allow di erent versions of an application to continue to communicate and collaborate.
Roadmap: In summary, in the context of self-evolution, research should focus on two main issues: (1) building a user friendly interface that would allow 1 The literature usually refers to the operationalisation of norms as `norm regimentation', and alternative norm enforcement methods (such as the application of sanctions) as `norm enforcement'. In this paper, however, we overload the word `enforce' as we use it to describe both approaches. 2 It may be argued that punishment and reward is not always the right approach for motivating the abidance to norms. Furthermore, what may be considered a punishment for one may be viewed as a reward for another. In this paper, although we talk about punishments and rewards, we concur that sanctions may be labeled more generally as the post-conditions of abiding with or breaking a norm. community member to interact, following the norms, without any knowledge of their interactions and their complexity, and in cases when users need to discuss norms, norms and norm violations will need to be visualised in a user friendly and comprehensible manner; and (2) engineering the system in such a way that ensures e cient interactions and permits evolution at runtime in a seamless manner that does not interrupt community interactions. The outcome of this research work would be to have the system run and manage evolving normativebased community interactions in an e cient, userfriendly, and seamless manner. 3
We argue that just like human communities, e-communities (or virtual communities) also need to self-evolve. Instead of creating numerous rigid systems, which is very common in online social systems, what we should aim at instead is providing tools for creating self-evolving systems that adapt to the community's needs. We believe di erent communities should be governed by di erent rules. These rules should be an ever evolving set resulting from the aspirations of its members, and not a rigid set de ned by a corporation (or a system designer) that does not take the community members' interests at heart. Furthermore, for the community's rules to be e ective, they need to be tailored to the speci c community, such as considering the character traits of the community's members.
We believe that the notion of self-evolving communities will revolutionise the way how software is build, as well as how we interact with software. We say that in the context of social interactions, software does not need to be rigid, nor customised for the individual, but adaptable to the group. Software engineers will need to design intelligent software that is capable of evolving according to the needs of the community as a whole, and users (or community members) should become more active in shaping their community by discussing and agreeing on their community rules.
In summary, the proposal is based on the traditional notion of mediating social interactions via norms. The roadmap for self-evolution is then dictaded by the lifecycle of norms, which we divide into four di erent stages (see Figure 1): (1) the birth of norms, (2) the automated formalisation of norms, (3) the automated operationalisation of norms, and (4) the automated enforcement of norms. Varied, and even interdisciplinary, research will be required for supporting these four stages, from social sciences and legal studies, to learning mechanisms, agreement technologies, natural language processing, formal logics, norm enforcement and regimentation, human computer interaction, and other software engineering techniques.