Monthly Archives: March 2015

Evolutionary methods for problem solving and artificial development

One of the principles I follow for problem solving is that many of the best solutions can be found in nature. The basic axiom of all knowledge as self knowledge applies to the study of computer science and artificial intelligence.

By studying nature we are studying ourselves and what we learn from nature can give us initial designs for DApps (decentralized applications).

The SAFE Network example

SAFE Network for example is following these principles by utilizing biomimicry (ant colony algorithm) for the initial design of the SAFE Network. If SAFE Network is designed appropriately then it will have an evolutionary method so that over time by our participation with it can fine tune it. There should be both a symbiosis between human and AI as well as a way to make sure changes are always made according to the preferences of mankind. In essence SAFE Network should be able to optimize it’s design going into the future to meet human defined “fitness” criteria. How they will go about achieving this is unknown at this time but my opinion is that it will require a democratization or collaborative filtering layer. A possible result of SAFE Network’s evolutionary process could be a sort of artificial neuro-network.

The Wikipedia example

Wikipedia is an example of an evolving knowledge resource. It uses an evolutionary method (human based genetic algorithm) to curate, structure and maintain human knowledge. Human beings

One of the main problems with WIkipedia is that it is centralized and that it does not generate any profits. This may be partially due to the fact that the ideal situation is that knowledge should be free to access but it does not factor in that knowledge isn’t free to generate. It also doesn’t factor in that knowledge has to be stored somewhere and that if Wikipedia is centralized then it can be taken down just as the library of Alexandria once was. A decentralized Wikipedia could begin it’s life by mirroring Wikipedia and then use the evolutionary methods to create a Wikipedia which does not contain the same risk profile or model.

Benefits of applying the evolutionary methods to Wikipedia style DApps

One of the benefits is that is that there could be many different DApps which can compete in a market place so that successful design features could result in an incentive to continue to innovate. We can think of the market in this instance as the human based genetic algorithm where all DApps are candidate solutions to solve the problem of optimizing knowledge diffusion. The human beings would be the innovators, the selectors, and the initializers. The token system would represent the incentive layer but also be for signalling so that humans can give an information signal which indicates their preferences to the market.

Wikipedia is not based on nature currently and does not evolve it’s design to adapt to it’s environment. Wikipedia “eats” when humans donate money to a centralized foundation which directs the development of Wikipedia. A decentralized evolutionary model would not have a centralized foundation and Wikipedia would instead adapt it’s survival strategy to it’s environment. This would mean Wikipedia following the evolutionary model would seek to profit in competition with other Wikipedia’s until the best (most fit) adaptation to the environment is evolved. Users would be able to use micropayments to signal through their participation and usage which Wikipedia pages are preferred over others and at the same time you can have pseudo-anonymous academic experts with good reputations rate the accuracy.

In order for the human based genetic algorithm to work, in order for the collaborative filtering to work, the participants should not know the scores of different pages in real time because this could bias the results. Also participants do not need to know what different experts scored different pages because personality cults could skew the results and influence the rating behavior of other experts. Finally it would have to be global and decentralized so that experts cannot easily coordinate and conspire. These problems would not be easy to solve but Wikipedia currently has similar problems in centralized form.

Artificial development as a design process

Quote from artificial development:
Human designs are often limited by their ability to scale, and adapt to chang-ing needs. Our rigid design processes often constrain the design to solving the
immediate problem, with only limited scope for change. Organisms, on the other hand, appear to be able to maintain functionality through all stages of de-
velopment, despite a vast change in the number of cells from the embryo to a mature individual. It would be advantageous to empower human designs with
this on-line adaptability through scaling, whereby a system can change com-plexity depending on conditions.
The quote above summarizes one of the main differences between an evolutionary design model and a human design model. The human designs have limited adaptability to the environment because human beings are not good at trying to predict and account for the possible disruptive environmental changes which can take place in the future. Businesses which take on these static inflexible human designs are easily disrupted by technological changes because human beings have great difficulty making a design which is “future proof”.  It is my own conclusion that Wikipedia in it’s current design iteration suffers from this even though it does have a limited evolutionary design. The limitation of Wikipedia is that the foundation is centralized and it’s built on top of a network which isn’t as resilient to political change as it could be. In order for the designs of DApps to be future proof they have to utilize evolutionary design models. Additionally it would be good if DApps are forced to compete against each other for fitness so that the best evolutionary design models rise to the top of the heap.


Clune, J., Beckmann, B. E., Pennock, R. T., & Ofria, C. (2011). HybrID: A hybridization of indirect and direct encodings for evolutionary computation. In Advances in Artificial Life. Darwin Meets von Neumann (pp. 134-141). Springer Berlin Heidelberg.

Cussat-Blanc, S., Bredeche, N., Luga, H., Duthen, Y., & Schoenauer, M. Artificial Gene Regulatory Networks and Spatial Computation: A Case Study.

Doursat, R. (2008). Organically grown architectures: Creating decentralized, autonomous systems by embryomorphic engineering. In Organic computing (pp. 167-199). Springer Berlin Heidelberg.

Harding, S., & Banzhaf, W. (2008). Artificial development. In Oganic Computing (pp. 201-219). Springer Berlin Heidelberg.
Ulieru, M., & Doursat, R. (2011). Emergent engineering: a radical paradigm shift. International Journal of Autonomous and Adaptive Communications Systems, 4(1), 39-60.

Decentralized reputation based reward networks and gift economics

What are decentralized reputation based reward networks?

If we look at the reputation system as a sort of human based genetic algorithm in a sort of multi-agent system then it becomes possible to use smart contracts to reward agents which meet a threshold score for certain reputation attributes. These attributes could be for instance how effective an individual agent is at altruism. The agents who are deemed most effective at altruism would receive the highest effectiveness score in the altruistic reputation based network and they could then qualify for conditional discounts, conditional rebates, conditional rewards, from corporations and individuals within that reputation based network.

Is a reputation based reward network?

The Basic Income algorithm which allows for dividend pathways works in a similar fashion where the givers within the personalized safety net become part of the overall Resilience social support network.  The Resilience network accounts for and tracks the altruists who volunteer to pay the tax and at the same time the individuals (individual agents) who pay into the network are given the incentive to shop at businesses which are part of the network. The Resilience network is a sort of reputation network where all who maintain a certain attribute by giving to the community get to remain a part of the community. could be recognized as a reputation based reward network but only in a very limited sense due to the fact that participants may or may not choose to see it that way. If participants choose to build a reputation system on top of then it can become an effective reputation based reward network.

Reputation based reward networks allow for gift economics

In a gift economy nothing is bought or sold. In a gift economy everything given or received is a gift similar to how at Christmas it is a gift economy because everything given or received is gifted. A gift economy can take advantage of reputation so that those who give a lot to others earn a certain reputation which can allow the givers in the network to obtain priority status for rewards. It is also possible to have smart contracts with conditions such that only those who have proven themselves through specified acts of kindness can become eligible for the reward lottery.  In essence in order to enter the lottery you would have to earn lottery tickets which can only be earned by giving donations to certain charities.

Reputation lotteries can leverage greed to encourage effective altruism

  1.  In order to enter the lottery you must be able to prove you did the specified act of altruism. This can easily be shown by a blockchain transaction for example.
  2. For every altruistic interaction you shall receive points which can be traded in for lottery tickets.
  3. The more lottery tickets you have the greater your chance to win the rewards.
  4. All who enter the lottery are guaranteed to receive a permanent badge of honor for having participated whether they win or not. This would encourage the participants to continue playing into the future.
  5. Participants can be human or machine.

References,. ‘Basicincome.Co – Incentive-Based Decentralized Safety Nets’. N.p., 2015. Web. 12 Mar. 2015.

YouTube,. ‘Identity And Reputation’. N.p., 2015. Web. 12 Mar. 2015.

Evolutionary Computation as a Form of Organization

The Free Knowledge Exchange (FKE) project intro-
duces the concept of evolutionary knowledge manage-
ment based on concepts of GA. It used a human-based
genetic algorithm (HBGA) for the task of collabora-
tive solving of problems expressed in natural language
(Kosoruko , 2000a). It was created in 1997 for a small
organization with the goal of promoting success of
each member through new forms of cooperation based
on better knowledge management.

Human genetic based algorithms pave the way for evolutionary self organizing architectures. These architectures can be social, political, economic, or physical.

The idea is that user preferences are tracked in real time by the architecture itself. The architecture then uses this feedback to continuously evolve the organization.

The idea of human interaction came from interac-
tive genetic algorithms (IGA) that introduced hu-
man evaluation interfaces in evolutionary computa-
tion. Human-based genetic algorithm (HBGA) used
in FKE is basically an IGA combined with human-
based innovation interfaces (crossover and mutation).

The concept of Evolutionary Computation as a Form of Organization will be discussed in future postings within the context of how a distributed autonomous virtual state can utilize evolutionary computation to become a self optimizing system.


Coello, C. A. C. (2010). List of references on constraint-handling techniques used with evolutionary algorithms. Power, 80(10), 1286-1292.
Kosorukoff, A., & Goldberg, D. E. (2002, July). Evolutionary Computation As A Form Of Organization. In GECCO (Vol. 2002, pp. 965-972).


Virtual mutual aid societies can supplement and eventually replace national welfare services

Virtual mutual aid societies can be formed by any group of people who have access to the Internet. To achieve this we must achieve a state of affairs where Internet access is perceived as a human right rather than a privilege.  Virtual mutual aid societies could be fully programmable, based around decentralized digital reputation, decentralized trust, and distributed authority.

Virtual mutual aid societies may start out on social networking sites such as Facebook where individuals can join Facebook groups. Virtual mutual aid societies may also start out in Second Life, in gaming universes, or anywhere that a group of people can meet. The criteria for entry can act as a programmable filter and the ability to vote may also be built in.

Virtual mutual aid societies can provide for their members by offering membership rewards, membership dividends, or if these virtual mutual aid societies are self governing then citizen’s dividends, discounts, etc. Decentralized reputation will allow people to know far more people than the limits of Dunbar’s number and due to the fact that it is programmable the logic of the mutual aid society can be continuously improved and updated.

I will have more posts to offer insight on the subject of virtual mutual aid societies in the future.


In the United States the Democrats are attached to old ideas. One of these old ideas is the Robin Hood protocol. The Robin Hood protocol requires that voters elect Democrats and in exchange for party loyalty the Democrats will tax the rich and give to the poor. Since a lot of or perhaps the majority of voters are poor and since a majority of Democrats are also probably poor this amounts to a kind of mass bribe or in less provocative terms a method of buying votes. At the same time this creates a “lifeline” dependency on the Democratic party and it’s politicians while giving the politicians the power to cut that “lifeline” dependency off if they have a change of mood.

This state of affairs may have worked in the past because the threat of revolution, civil unrest, organized crime, all but required that the government placate the have nots through social programs aka “hand outs”. I will state for sake of clarity that I have no issue with “hand outs” because corporations receive these “hand outs” as well in the form of government contracts. The problem arises from the fact that due to technological advances leading to “total transparency” or “total surveillance” there eventually will no longer be a fear of revolution, unrest, organized crime, etc. Once this delicate balance of power is broken the Robin Hood protocol which encompassed the strategy of the Democrats for decades going back to FDR will also be broken. The social contract breaks down under a state of total surveillance & total transparency and after the fear of social unrest is gone is there any reason for politicians to continue with the social programs aka “hand outs” to keep the majority of the population placated?

I believe we cannot predict the outcome or future political events. I also don’t believe that people who are in a position to do something today should put their fate and their future into the hands of political authority, religious authority, Jesus, aliens, or anyone else. I take the opinion that we make our fate and no entity from up above will come down to save those down below.

How did communities do social programs prior to there being a government? Prior to nationalist governments providing social programs there were mutual aid societies/benefit societies which provided the social welfare services. These mutual aid societies/benefit societies were based on the value of community service and the Freemasons are an example of this. To get accepted into a mutual aid society a person had to be of good character and other members had to vouch for their character.

Fast foward to 2015 and we now have the blockchain which allows for programmable distributed autonomous societies. These new global societies could take on similar functions that mutual aid societies took on during times when there were no government social programs. By building these sorts of distributed autonomous societies now we can reduce the risk of chaos and social upheaval in the future. By building these sorts of societies now we might be able to prevent a rise in organized crime, terrorism, resource wars, which could come about if we stay on the current course.

One of the first implementations of a programmable distributed autonomous society will be the digital autonomous virtual state (DAVS) project. More information will be available about this in future postings. This post and future postings on the subject can be seen as a historical documentation of my thoughts and intentions going forward.


Beito, David. ‘From Mutual Aid To Welfare State: How Fraternal Societies Fought Poverty And Taught Character’. The Heritage Foundation. N.p., 2000. Web. 1 Mar. 2015.

Scandlen, Greg, and Greg Scandlen. ‘Mutual Aid Societies: It’S Amazing What People Can Do Together’. The Federalist. N.p., 2015. Web. 1 Mar. 2015.

Wikipedia,. ‘Mutual Aid (Organization Theory)’. N.p., 2015. Web. 1 Mar. 2015.