An idea: Antifragile cars via situation-aware user interfaces

The car controls system and its interfaces are the major witnesses of the user behaviors that ultimately lead to the emergence of safety. All of the user actions in the primary vehicle platform can be transcoded in an homogeneous XML format and logged, together with their time of occurrence. A number of other data sources can be collected and transcoded in the same format -- for instance automotive imaging, LiDAR, GPS and traffic information, V2V, and V2I data sources. This constitutes a constantly updated stream of contextual information describing the cloud of behaviors taking place within and "around" each car and each user. Said stream represents a very valuable knowledge that may be applied in several ways:

• first, it represents a knowledge base to reason about individual and social driving behaviors. Post-mortem approaches and tools can be used to correlate multiple causes leading to accidents and other safety-related conditions.
• Secondly, said knowledge base can be integrated with Advanced Driver Assistance Systems (ADAS) and used to dynamically adapt / personalize the driving experience with the objective to enhance safety, learn peculiar driving traits, compensate them with corrective adaptations in the ADAS system, and constructing a periodic personalized feedback report highlighting recursive dangerous behaviors and conditions. The result would be that of an antifragile car: a car able to systematically improve safety by learning and evolving after each and every driver.
• Third, by using dynamic profiling and machine learning it is possible to create and constantly update a stereotype of the "official" drivers. By using Hidden Markov Models, Bayesian Intelligence and similar techniques it can be possible to compare reference stereotypes with observed stereotypes. Discrepancies (see also here) imply that the either the driver has changed, which could be a possible indication of theft. Alarms could be instructed so as to automatically inform, e.g., the official drivers through their smartphones, or the nearest police offices.
• Fourth, by comparing the reference and the observed stereotypes it is possible to detect this the driving behavior is drifting away from the reference ones. By coupling this with other ADAS-relayed information, the car could "realize" that the driver is developing fatigues or is under the influence of substances affecting his/her behaviors.

Also by considering my concept from the viewpoint of marketing and advertising, the concept of an "Antifragile Car that learns how to protect You" would most definitely attract the interest of the customers.

I wonder what the automotive industries would think of such an idea.

My little "cybernetic journey" through systems and organizations

At the beginning of my research experience my major focus was software fault-tolerance. The leitmotiv of that period is possibly the synchronous system assumption: although the target architectures I was working on were supposedly “high performance”, in fact those systems were quite simple: dedicated networks, dedicated processors, with predefined and immutable assumptions. Later on I described this class of systems as ataraxies—systems that have a complete “faith” in the validity of the designers’ assumptions. Clearly this is an approach that introduces very much fragility. Such systems could maybe described as sitting ducks with respect to change: they fail as soon as any of their system assumptions is invalidated.

In those days I completed my doctoral studies with a thesis in which I introduced the concept of “recovery language”: a special-purpose programming language that runs next to the conventional programming language and deals with error recovery and reconfiguration. This recovery language comes into play as soon as an error is detected by an underlying error detection layer or when some erroneous condition is signaled by the application processes. Error recovery and reconfiguration are specified as a set of guarded actions that operate on coarse-grained entities of the application (tasks and groups of tasks) and are enacted depending on the current state of those entities. An important aspect was that such “recovery code” is run-time interpreted, which means it can be changed dynamically.

From the point of view of General Systems Theory, this meant that systems built with my approach were more-than-ataraxies: when embedded into a context-aware feedback loop, those systems would achieve teleological (reactive) properties.

Later on I became acquainted with General Systems Theories such as the behavioral classification by Wiener and the system of Kenneth Boulding. I started considering “more-than-reactive” systems: systems able to proactively create models of possible futures and adapt their action with respect to those hypothesized conditions. I initiated, promoted, and supervised the doctoral studies of three students, with whom I explored “advanced” adaptive behaviors. With such behaviors, the adaptation code is assembled dynamically, by composing the adaptation planners best-matching the current contextual conditions. This resulted in filing a patent.

In my little “cybernetic journey” I then came to the realization that a significant limitation of my approaches was what I call the genotypical feedback. The systems I was devising were adaptive rather than evolving systems. The lessons learned while facing the environments and adapting to them had no influence on the identity of those systems. The systems were merely resilient (at-work to-stay-the-same [Sachs, 1995]). This persistence of the system identity was a guarantee of trustworthiness; and yet, it came also as a limitation to the ability to evolve. Therefore I started to consider systems that are at-work to-get-better—thus they are able to evolve beyond what initially prescribed by the “designer”. Inspired by the work and the terminology introduced by Nassim N. Taleb, I called such systems antifragile, and came to the idea of studying the properties and the engineering of such systems. I launched a workshop on computational antifragility and antifragile engineering, called ANTIFRAGILE. Professor Taleb himself kindly participated in the second edition with a keynote speech (in teleconference). Dr. Kennie Jones from NASA Langley gave keynote speeches sharing with the attendees his lessons learned in antifragile engineering at NASA. Furthermore, I launched a LinkedIn group on computational antifragility, which has attracted the interest of more than 150 people.

In parallel to the above mentioned explorations, several years ago I started to realize that a second major limitation in my approaches was in the social dimension. Although I was able to manipulate system components, my approaches were basically treating systems as individual entities, thus neglecting their inherently social nature. I understood that this was a major mistake: paraphrasing Margaret Thatcher,

there is no such thing as an individual system.

Every system is collective—every system is a social system. This new perspective allowed me to “see” problems from a new and wider angle. Concepts such as a system’s organization became central and provided me with a new research path to focus my attention on. Preliminary explorations were carried out: I wrote a paper on quality indicators for collective systems resilience, in which I began considering the match between the “social persona” of the Whole and that of the Parts. I discussed centrifugal and centripetal social forces, which were able to weaken or strengthen the resilience of the Whole. The link with the philosophies of Aristotle and Leibniz became very much apparent and ignited an ancillary line of exploration. I began realizing that several of the problems and concepts I had encountered in science had an established “philosophical counterpart”—for instance the Leibnizian concepts of compossibles and substantiata; genotypical and phenotypical conservation of modularity as a foundation to evolvability; and a resorce-constrained world evolving its substances to ever increasing quality and complexity; all mapped to supposedly “modern” concepts such as emergence, evolution, cellular automata, artificial life, and many others.
All the above led me to several new realizations. For instance, I came to realize that many of our “societal systems” (such as healthcare, civil defense, and crisis management organization) are built with “fragility assumptions” quite similar to those of the “sitting ducks” I mentioned earlier—which possibly explains why those systems are so inefficient and incapable to deal with our turbulent, overpopulated, and resource-scarce new world. In fact, the problem is quite the same: I tried to express this in the following sentence from paper “How Resilient Are Our Societies? Analyses, Models, and Preliminary Results”:

“Regardless of its nature, any system is affected by its design assumptions. Our societies are no exception. The emergence of sought properties such as economic and social welfare for all; sustainability with respect to natural ecosystems; and especially manageability and resilience, highly depends on the way social organizations are designed.”

Social organization is obviously the major gestalt in the above quote. Social organization—“a set of roles tied together with channels of communication” [Boulding, 1956]—is the invariant that captures the essence of collective systems as different in scale and behavior as a colony of bacteria in comparison to one of our cities.

In my next post I will focus my attention on two social organization "templates" that I defined a few years ago: the service-oriented community and the fractal social organization.

References

[Sachs, 1995] Joe Sachs, "Aristotle's Physics: A Guided Study". Rutgers University Press. ISBN 0-8135-2192-0.
[Boulding, 1956] Kenneth Boulding, "General Systems Theory—The Skeleton of Science". Management Science 2(3), April 1956, pp. 197-208.

Resilience as concurrent interplays of opponents: preliminary ideas and call for collaborations

In my previous work “A behavioural model for the discussion of resilience, elasticity, and antifragility” I discussed resilience as the emerging result of the dynamic interplay between the behaviors exercised by a system and those of the environment it is set to operate in. Then, in my latest work “On ambients as systemic exoskeletons: Crosscutting optimizers and antifragility enablers” I introduced a “horizontal” and a “vertical classification” of systems. The idea in this second paper is that any system may be considered at the same time a “whole”, a set of “parts”, and a nested compositional hierarchy of functional nodes.

By applying the idea of the first paper to this second idea of a system’s horizontal and vertical classifications, I thought of resilience / antifragility as the emergent result of concurrent behavioral interplays taking place across the involved systems’ [ wholes / sets of parts / hierarchies of nodes ].

Let me clarify this through two examples:

1. A bullet is shot and passes through the body of a living being. Such a traumatic event directly affects a number of organs and systems of that being. Interdependence among organs and systems is likely to lead to cascading effects that may in turn lead to severe injuries or the loss of life.
2. A hurricane hitting a region. Catastrophic events such as this one typically ripple across the involved hierarchies of nodes triggering the concurrent reactions of multiple crisis management organizations.

In both cases, resilience may be modeled as the result of the effects of an external event on a system’s horizontal and vertical organization. The external event manifests itself at all systems and networks levels and activates a response that is both individual and social.

Now, I believe a good way to model such response could be in terms of Game Theory. The idea is to consider:

• GT players as the involved whole / parts / nodes (let me call them “opponents”).
• Behavior classes as the strategic choices available to the opponents.
• GT strategies as the behaviors planned and enacted by the opponents.

• Moreover, I propose to assign energy budgets specific of the involved opponents. Said energy budgets serve as global constraints shared by all of the nodes of the GT players across their horizontal and vertical organizations.

• Finally, I propose to associate GT payoffs to the possible behavioral responses, with costs (in terms of consumed energy budget resources) proportional to the complexity of the chosen behavior.

(↦ A simple purposeful behavior only requires sensory / actuator parts, thus calls for less energy than a complex proactive behavior, which requires analytical / planning parts; in turn, that behavior would cost less energy than a complex antifragile behavior, which requires in addition complex knowledge/wisdom management parts.)

The idea I would like to develop is that to define nested compositional hierarchies of payoff matrices: sort of interconnected and mutually influencing payoff “spreadsheets”. Overall resilience may be expressed, maybe in some analytical form, as the solution of those payoff spreadsheets taking into account the outcomes of all the concurrent interplays and the consequences of those outcomes on physically or logically neighboring parts / nodes.

(↦ Think once more of the case of the bullet passing through a living body and of the cascading effects of the many concurrent “confrontations” between the involved organs and the bullet.)

The payoff spreadsheets would also model the local and global costs in terms of the shared energy budgets. Adopting the most expensive behaviors at all levels could result in too high an energy consumption, while being able to “keep control”, and proportion one’s response hierarchies, may translate in the ability to survive longer.  Two very eloquent examples of this fact were provided by Dr. Jeff Washburn here).

I would be happy to discuss the basic ideas and possible “implementations” of the just sketched model. In particular I would welcome discussing with experts in game theory and evolutionary game theory willing to co-write a paper on the above idea for ANTIFRAGILE’16.

ANTIFRAGILE 2016

I'm very glad to announce the launch of ANTIFRAGILE'16, the 3rd Int.l Workshop on Computational Antifragility and Antifragile Engineering. Madrid, Spain, May 23-26, 2016

More information will be made available through the ANTIFRAGILE homepage,   https://sites.google.com/site/antifragile2016/

For any information, do not hesitate to contact me!

Special issue of the Springer Journal of Reliable Intelligent Environments: "Resilient and Antifragile Ambient Systems"

News: NEW DEADLINE: AUGUST 14!

Dear Readers,

 

this is to announce a special issue of the Springer Journal of Reliable Intelligent Environments devoted to Resilient and Antifragile Ambient Systems. The special issue CfP shall soon be announced on the official web pages of the journal, though you may find herein a preview copy. Should you require further information, please do not hesitate to contact me!

Kind regards,
Vincenzo.

“Resilient and Antifragile Ambient Systems”

Resilience (from Latin resilire, “to spring back, start back, rebound, recoil, retreat”) plays a central role in several disciplines. Definitions of resilience can be found in ecology, business, psychology, industrial safety, microeconomics, computer networks, security, management science, cybernetics, control theory, as well as crisis and disaster management and recovery. A general interpretation of resilience may be considered that of  “the ability of a system subjected to faults and changes 1) to continue distributing its services 2) without losing its peculiar traits.

Antifragility goes one step further and suggests that certain ambient systems  could systematically improve their system-environment fit, when subjected to faults and changes. Thus an antifragile system would not “stay the same”; rather, it would “get better” with each new experience.

The engineering of antifragile computer-based ambient systems is a challenge that, once met, would allow ambient systems to self-evolve and self-improve by learning from accidents and mistakes in a way not dissimilar to that human beings are capable of. Learning how to design and craft antifragile systems is thus an extraordinary challenge whose tackling is likely to reverberate on many a computer engineering field. New methods, programming languages, even custom platforms will have to be designed. The expected returns are extraordinary as well: Antifragile computer engineering promises to enable the realization of truly autonomic ambient systems able to

- meta-adapt to unprecedented conditions and circumstances;
- self-adjust to dynamically changing environments;
- self-organize so as to converge to proactively optimal strategies to sustain scalability, high-performance, and energy efficiency;
- personalize their aspects and behaviors after each and every user.

And to learn how to get better while doing it!

As a design aspect cross-cutting through all system and communication layers, antifragile engineering will require multidisciplinary visions and approaches able to bridge the gaps between “distant” research communities so as to propose novel solutions to design and develop antifragile ambient systems ;
devise conceptual models and paradigms for antifragility ;
provide analytical and simulation models and tools to measure a system’s ability to withstand faults, adjust to new environments, and enhance their resilience in the process.

The main topics of this special issue of the Springer Journal of Reliable Intelligent Environments include, though are not limited to:

- Conceptual frameworks for antifragile systems, ambients, and behaviours;
- Dependability, resilience, and antifragile requirements and open issues;
- Design principles, models, and techniques for realizing self-resilient and antifragile systems and behaviours;
- Frameworks and techniques enabling the definition of resilient and antifragile ambients;
- Methods and approaches coupling ambient intelligence with antifragility;
- Antifragile human-machine interaction;
- End-to-end approaches towards antifragile services;
- Autonomic resilient behaviours;
- Middleware architectures and mechanisms for resilience and antifragility;
- Theoretical foundation of resilient and antifragile behaviours;
- Formal modeling of resilience and antifragility;
- Software engineering for resilience and antifragility;
- Architectures and design patterns;
- Machine learning as a foundation for resilient and antifragile architectures;
- Antifragility and resilience against malicious attacks;
- Antifragility and the Cloud;
- Service Level Agreements for resilience and antifragility;
- Verification and validation of resilience and antifragility;
- Antifragile and resilient services and components.

Important dates:
Submission deadline: AUGUST 14, 2015
First feedback: October 2, 2015
Final decisions: Noember 13, 2015.

For inquiries please do not hesitate to contact the Guest Editor, Vincenzo De Florio (vincenzo dot deflorio at uantwerpen dot be).

"Write an abstract of your research plan in Layman's terms"

A leitmotiv in our societies is inflexibility. We have great technology, though our supposedly smart phones are not that smart, solutions are one-size-fits-all, devices are not yet appliances, and so on and so forth. And of course we have organizations, which work of course, and are supposed to serve us; but in fact they do so in a very inflexible way, through rigid hierarchies that lead to inefficiency, long service times, and yes very high costs! In fact they look like aqueducts that lose much water along their pipes.

This seems to be two different things, but in fact I think it is the result of a same mistake: looking at things as individual rater than social systems. If you have to design an individual system, you only consider its relationship with the environment it will be placed into. As resources are limited and constraints are many, you need to face trade-offs: for instance, costs versus functionality, comfort vs. energy efficiency, etc. The net result is systems that are systematically unflexible and systematically fragile. If there is turbulence, meaning that things change rapidly, technology reveals its nature of a sitting duck for change. Now, if you look at social organizations, they are the same: they are the result of trade-offs operated while considering them as individual entities. Thus for instance we have organizations such as the civil defence, the police, and the fire fighters; but they are systems incapable of any interaction, of any cooperation. They can't even share their knowledge, let alone work together! As they are "necessary", constraints mean less to organizations. In the end, we "pump" lots of money in them, in the hope of making them "better", readier, smarter. Unfortunately we get so few in return. This becomes apparent especially in times of crisis (Sometimes one even asks where the organizations are! See for instance “Where in the hell is the cavalry on this one?”).

What is missing across the scales is the social and the "ecological" dimensions. "One man is no man", as they say, though it is also true that one device is no device, and one organization is no organization. Systems, men, organizations-they are all the same: complex Wholes that constitute greater Wholes. Dimensioning of resources while designing an embedded system or a novel social organization should be a social rather than an individual-oriented process. Systems, services, organizations—they should be designed with interoperability in mind. They should be regarded as Wholes and at the same time they should be realized as Parts of greater Wholes—on, on towards an ever greater degree of emergence; of quality, of adaptability, of resilience, of flexibility. This is what my Fractal Social Organizations aim to achieve. This is where I'm directed in my research action for the coming years.

"Write an abstract of your research plan in Layman's terms" by Vincenzo De Florio is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Permissions beyond the scope of this license may be available at mailto:vincenzo.deflorio@gmail.com.

How Resilient Are Our Societies?

Regardless of its nature, any system is affected by its design assumptions. Our societies are no exception. The emergence of sought properties such as economic and social welfare for all; sustainability with respect to natural ecosystems; and especially manageability and resilience, highly depends on the way social organizations are designed. A typical case in point is given by traditional organizations operating in domains such as healthcare and crisis management. A common assumption characterizing those organizations is the adoption of a strict client-server model. This produces at least the following major consequences:

• Stigmatization. Users are permanently classified into service providers and service receivers. Traditional healthcare organizations for instance typically classify users into two disjoint categories: the active users, namely professional and informal carers, and the patients and the elderly, who are considered as users incapable of any active behavior [1]. Likewise, in disaster management organizations, predefined active roles are assigned to institutional responders while the citizens are confined to a passive role [2, 3].
• Fragility. The artificial distinction in an active and a passive side of society severely affects quality-of-emergence [3, 4]. In particular, it introduces a systemic performance penalty in that only a subset of the social actors is available to serve the whole set. As well known, the fast growth and the progressive aging of the human population are introducing a new context—one in which the “service subset” is quickly decreasing in proportion. The problem is no more the ever increasing social costs; rather, it is the fact that the spectre of unmanageability—namely the vision of a fragile society unable to serve its citizens—is just around the corner.
• Absence of a referral service. Despite having an only partial view on the capability and current state of the available servers, it is the responsibility of the client to identify which server to bind to. It is the user that needs to know, e.g., which emergency service to invoke, which hospital to call first, which civil organization to refer to, and so on. Referral services do exist, but they mainly cover a single domain (i.e., healthcare) and very specific cases (typically, the seamless transfer of patient information from a primary to a secondary practitioner [5]). Because of this specialization such services mostly possess an incomplete view of the available resources.
• Lack of unitary responses to complex requests. To the best of our knowledge, no referral service provides a composite response to complex requests such that the action, knowledge, and assets of multiple servers are automatically or semi-automatically combined and orchestrated. Even electronic referral systems in use today are mostly limited [6] and only provide predefined services in specific domains. As a consequence, in the face of complex servicing requests calling for the joint action of multiple servers, the client is basically left on its own. Societal organizations do not provide unitary responses nor assist the client in composing and managing them. Reasons for this may be found in lack of awareness and also in the “convenient” shift of responsibility for failures from the server to the client.

A logic consequence of the above situation is the urgent need to mutate our organizational paradigms and assumptions. Simply stated, we cannot afford anymore not to use the full potential of our societies. This means that the artificial distinction between an active and a passive subset should be removed—or at least significantly reduced. Moreover, the increasing complexity of modern times require that societal organizations assume responsibility for becoming the enablers of collectively intelligent responses. New organizational design assumptions are called for, able to provide us with new servicing paradigms—in other words, new ways to perceive and manage the status quo. The vision of the organization as a system restricting the freedom to play roles should be changed into that of an enabler and a provider. Instead of preventing participation, the organization should allow roles to be filled by whomever is able and willing to participate. More than this, the organization should function as a catalyst of mutualistic cooperation among the role players at all levels, from the citizens to the governing institutions. By means of the organization, knowledge should flow among the players highlighting needs, assets, requirements, and opportunities. The organization should assist in the process of self-orchestrating a response, making it easier for all parties involved to coordinate themselves, exchange information, take the right and timely decisions.

Two key challenges of our societies are, one the one hand, being able to define one such organizational model. At the same time, fundamental aspects of the identity of the organization must be preserved. A second challenge is thus learning how to guarantee the resilience of our “evolved” organizations. Organizational fidelity [10, 11] (bounds to identity drifting) therefore becomes a new design requirement for our future organizational models.

In previous posts I presented an organizational model called Fractal Social Organizations (FSO). FSO takes the responsibility as a generalized referral service for the orchestration of complex social services. In FSO, the rigid client-server scheme of traditional organizations is replaced by service orientation, while bottleneck-prone hierarchies are replaced by communities of peer-level members. Role appointment is not static and directed by the organization, but rather voluntary and context-driven. It is my conjecture that the just stated new design assumptions allow for the creation of smarter societal organizations able to match the complexity of our new complex world.

References

1. Sun, H., De Florio, V., Gui, N., Blondia, C.: The missing ones: Key ingredients towards effective ambient assisted living systems. Journal of Ambient Intelligence and Smart Environments 2(2) (2010)
2. Colten, C.E., Kates, R.W., Laska, S.B.: Community resilience: Lessons from new orleans and hurricane katrina. Technical Report 3, Community and Regional Re- silience Institute (CARRI) (2008)
3. De Florio, V., Sun, H., Blondia, C.: Community resilience engineering: Reflections and preliminary contributions. In Majzik, I., Vieira, M., eds.: Software Engineering for Resilient Systems. Volume 8785 of Lecture Notes in Computer Science. Springer International Publishing (2014) 1–8
4. De Florio, V.: Communication and control: Tools, systems, and new dimensions. Lexington (2015)
5. Kim, Y., Chen, A., Keith, E., Yee, HalF., J., Kushel, M.: Not perfect, but better: Primary care providers’ experiences with electronic referrals in a safety net health system. Journal of General Internal Medicine 24(5) (2009) 614–619
6. Shaw, L., de Berker, D.: Strengths and weaknesses of electronic referral: comparison of data content and clinical value of electronic and paper referrals in dermatology. British Journal of General Practitioners 57 (2007) 223–224
7. Anonymous: Secured health information network and exchange (SHINE) (2012)
8. Anonymous: SHINE OS+. Available online at http://www.shine.ph (2015)
9. Verhulst, E.: Zen and the art of safety engineering. Available online at http://www.slideshare.net/ericverhulst1/zen-and-the-art-of-safety- engineering (2012)
10. De Florio, V.: Antifragility = elasticity + resilience + machine learning. models and algorithms for open system fidelity. Procedia Computer Science 32 (2014) 834– 841 1st ANTIFRAGILE workshop (ANTIFRAGILE-2015), the 5th International Conference on Ambient Systems, Networks and Technologies (ANT-2014).
11. De Florio, V., Primiero, G.: A method for trustworthiness assessment based on fidelity in cyber and physical domains. CoRR abs/1502.01899 (2015)

How Resilient Are Our Societies? by Vincenzo De Florio is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Permissions beyond the scope of this license may be available at mailto:vincenzo.deflorio@gmail.com.