unlocking global consiousness
Playdao is an avant-garde, exploratory protocol designed to pioneer a world operating on collective consciousness, transcending conventional currency systems. At its core, it harnesses the power of a decentralized directed acyclic graph, the Weighted Action Graph (WAG), engineered to shape dynamic, action-value-centric educational, organizational, and economic infrastructures.
It provides greater transparency, efficiency, and fairness by coupling fundamental concepts from graph theory, artificial intelligence, cryptography, and economics into a single global "substrate" protocol.
People live, work, learn, and grow in a system driven by pure action giving birth to a revolutionary new ontology of interconnected organically organized social and economic zero-currency structures of the future.
The playdao protocol WAG ontology consists of 2 unqiue types of nodes - actions, and values - along with all 4 possible edges that connect them. Action nodes serve as actions, and the edges connecting them to other actions and values are dependencies. Actions are paired wih value nodes which represent the total sum of all connected actions and other value nodes.
Each action in Playdaos action graph has dependency rules - other discreet action prerequisites and value requirements required to either observe or perform different actions. Actions can be things such as "giving a cookie", "reading a book", "taking a specfic class", or any other generic form of attestation.
Actions are also linked to different Values via Value Graphs consisting of Swap Nodes which connect up to form a graph. Each node within the graph acts as a barter comparison formula between different actions (2 - infinity). Swap nodes are rules for weighing different actions against each other. Actions can respect different Swap Nodes within their dependency rules to act as proofs of reputation. Reputation is recycled back into the system when it used as proof upon action completion.
The Value Graph acts as a comparasion algorithom for different actions and value can be thought of as reputation / trust within each interlinked action graph. The value of each action ( its max supply ) can be thought of as its weight or impact as a ratio of the entire the Value Graph to which the acion belongs to. Value is "recycled" back into the system after it used as proof. All actions that are part of the Value Graph are ratios (e.g. 1/3) of the value represented as a single whole (1) with the max supply of each action adding up to the ratio of the action. Value Graphs are free market driven and determined by Action Swap Nodes - nodes that equate actions against each other, Actions can have multiple value ratios rewarded for them.
Privacy is a core feature of the protocol, playdao uses powerful cryptography and zero-knowledge proofs to separate participants' identities (action certificates) & the action graph. Each agent who participates in the action graph fully controls their data.
The protocol is built on top of a distributed & decentralized vector graph database designed to be directly plugged into a neural network for analysis and detection of patterns formed by the connections of different actions and their supply & demand. This enables complex ai-generated Value Graphs and suggestions for action dependencies. This aims to achieve the type of value driven coupling required for A.I and human alignment.
Playdao is accessible to everyone and aims to build tools for small businesses and communities. Its grand vision is to build a new foundation for the triple coupling of A.I, economy, and organization to enable the creation of a more just, sustainable, and conscious future.
Playdao is currently in its early stages and our next step is to build a sandbox engine to simulate this new system and validate its efficiency via ai enabled self-interest driven agents within virtual communities. Testing the system would be done by observing and analysing the action graph and Value Graphs and their evolution. Factors such as fluctuations in supply and demand, competitive dynamics, potential gaming & parasitic behavior, value distribution and its effect on manipulation of the graph. Real-world case studies can also be performed by building 2 initial applications - graph explorer/editor & app/wallet which would enable agents to create actions, explore the action graph(s) and Value Graph(s), and explore available actions & complete/validate actions via the app. We already have a working proof of concept built on top of the blockchain presented at #ETHDevner2022 and are actively exploring other ways of testing this new concept.