Technical

It is possible to realise the project in different ways, best understood as realisations on different levels of complexity. For the purposes of this paper, discussion of potential, yet 'temporary' problems (such as the unavailability of payment via the Etherum service) will be ignored. Furthermore, the following discussion is based mainly on readily available technology.

Lowest level of complexity:

A smart contract on the Etherum Blockchain controls the in- and outputs of the forest. Every six months a programme fetches satellite pictures of the property from a supplier outside of the Blockchain. With the help of self-written image-analysis software, the programme can determine how much wood can be sold without overly-diminishing the tree population. The smart contract has hardly any feedback to rely on, and acts according to contractually invariable rules. A rudimentary function makes it possible for the system to buy additional properties and thus to expand. In this case the programme must be adjusted manually from outside the Blockchain by the project initiators.

This level of complexity realises a project which only fullfilles three of the seven criteria for creation of an autonomous and decentralised agent:

1. The agent is earns enough money to maintain itself, without human intervention (e.g. the agent pays for its own sever space).
2. The agent has an adaptive feedback system.
3. When interacting with humans the agent does so as a peer, not as a tool.

Middle level of complexity:

The smart contract carries out all calculations itself and is no longer depdendent on programmes outside of the Blockchain. Furthermore, the contract can scrape databases in order to dynamically regulate its prices. Because any infrastructure outside of the Blockchain is now unnecessary, the system is simple to reproduce. The contract can optimise itself from cycle to cycle. The contract thus recognises which trees are most profitable, and therefore only sell, or grow, specific types of trees in order to maximise profit. Two further criteria are fulfilled via a realisation of the project on this level of complexity:

1. The agent behaves much like a simple biological organism.
2. The agent can react and adapt to its environment (and furthermore, gather and process information about this environment).

Highest level of complexity:

The smart contract is no longer distinguishable from a completely developed artificial intelligence. Scraping data from forest databases allows the forest to radically optimise itself through logging decisions. Due to this, the wood is now sold at highest possible price. It should be noted that, although these databases are controlled by a wise variety of public, private, and governmental organisations, the political implications of the source of the scraped data is of no immediate concern to the project. After the contract accumulates a certain amount of money, it is able to set up independent versions of itself. These operate in accordance with different parameters, and let the contract optimise. Every new version of the contract thus acts more competitively, in order to optimise its economic value, and can adapt itself dynamically to different zones (according to climate and local vegetation). The last of the proposed criteria are thus fulfilled:

1. The agent can replicate itself.
2. The agent evolves through evolutionary algorithms and can thus discover new survival strategies.