ChaosEngine - Exploring Chaotic Entities

Overview

The ChaosEngine contract introduces the concept of chaotic entities, where entropy and chaotic logic play a key role in determining outcomes. The contract allows for the creation of chaos entities with an initial state and executes chaotic logic based on a logistic map function. Below, we explore the various features of the Chaos Engine, including the advantages and disadvantages of these novel concepts.

1. Creating Chaos Entities

The contract defines a structure to create chaos entities:

struct ChaosEntity {
    uint256 entityId;
    address creator;
    bytes32 initialState;
    uint256 entropy;
    uint256 creationTime;
}

mapping(uint256 => ChaosEntity) public chaosEntities;
uint256 public nextEntityId;

Advantages

Unique Entities: Each entity is unique, with its own initial state and entropy, representing a chaotic system.
Entropy Factor: Each entity's entropy is generated from the initial state, creator address, and the block timestamp, simulating real-world chaotic systems.

Disadvantages

Entropy is Predictable: The entropy generation is pseudo-random and deterministic based on the initial state, so it may not be ideal for highly secure applications.
Execution Complexity: Handling chaotic systems introduces complexity in execution, which can lead to difficulty in debugging or gas inefficiencies.

2. Chaotic Logic Execution

The chaotic logic is based on deterministic chaos using a logistic map function:

function chaoticLogic(bytes32 state, uint256 entropy)
    internal
    pure
    returns (bytes32)
{
    uint256 chaoticValue = (uint256(state) * entropy) % 1000000000;
    uint256 r = 4; // Chosen for maximal chaos in the logistic map
    uint256 nextState = (r * chaoticValue * (1000000000 - chaoticValue)) / 1000000000;

    return keccak256(abi.encodePacked(nextState));
}

Advantages

Chaotic Outcome: The use of chaotic logic introduces an element of unpredictability in the contract's behavior, making it suitable for applications like unpredictable NFTs.
Mathematically Complex: The use of the logistic map introduces real-world chaotic systems into the blockchain, creating a new paradigm for decentralized applications.

Disadvantages

Computationally Expensive: Chaotic systems, especially those modeled mathematically, can introduce higher gas costs.
Deterministic Chaos: Despite its chaotic appearance, the system is still deterministic based on the initial entropy and state, which could be exploited if predictable.

3. Governance and Chaos Execution

The contract introduces decentralized governance over chaos entities, allowing users to vote on chaos execution:

mapping(uint256 => uint256) public votesForChaosExecution;
mapping(uint256 => mapping(address => bool)) public hasVoted;

function voteForChaosExecution(uint256 entityId) public {
    require(!hasVoted[entityId][msg.sender], "Already voted");
    votesForChaosExecution[entityId]++;
    hasVoted[entityId][msg.sender] = true;
}

function getChaosExecutionStatus(uint256 entityId) public view returns (string memory) {
    uint256 votes = votesForChaosExecution[entityId];
    if (votes > 100) {
        return "Chaos execution imminent!";
    } else {
        return "Chaos in deliberation.";
    }
}

Advantages

Decentralized Governance: Allows users to have control over the execution of chaotic entities, adding a community-driven aspect to chaotic decision-making.
Social Entropy: The more votes an entity receives, the higher its chance of execution, simulating social entropy in decision-making.

Disadvantages

Requires Active Participation: The success of governance-based chaos execution requires active participation from users, which could be difficult to maintain over time.
Threshold Dependency: If the voting threshold is not reached, chaotic entities may remain in a limbo state, never being executed.

Full Contract Code


// SPDX-License-Identifier: MIT
pragma solidity ^0.8.21;

contract ChaosEngine {
    struct ChaosEntity {
        uint256 entityId;
        address creator;
        bytes32 initialState;
        uint256 entropy;
        uint256 creationTime;
    }

    mapping(uint256 => ChaosEntity) public chaosEntities;
    uint256 public nextEntityId;

    event ChaosCreated(
        uint256 entityId,
        address creator,
        uint256 entropy,
        uint256 creationTime
    );
    event ChaosExecuted(uint256 entityId, bytes32 result);

    function createChaosEntity(bytes32 initialState) public {
        uint256 entityId = nextEntityId++;
        uint256 entropy = uint256(
            keccak256(
                abi.encodePacked(initialState, block.timestamp, msg.sender)
            )
        ) % 1000000000;

        chaosEntities[entityId] = ChaosEntity({
            entityId: entityId,
            creator: msg.sender,
            initialState: initialState,
            entropy: entropy,
            creationTime: block.timestamp
        });

        emit ChaosCreated(entityId, msg.sender, entropy, block.timestamp);
    }

    function executeChaos(uint256 entityId) public returns (bytes32) {
        ChaosEntity storage entity = chaosEntities[entityId];
        require(entity.creator == msg.sender, "Not the creator");

        bytes32 result = chaoticLogic(entity.initialState, entity.entropy);
        emit ChaosExecuted(entityId, result);
        return result;
    }

    function chaoticLogic(bytes32 state, uint256 entropy)
        internal
        pure
        returns (bytes32)
    {
        uint256 chaoticValue = (uint256(state) * entropy) % 1000000000;

        uint256 r = 4; 
        uint256 nextState = (r * chaoticValue * (1000000000 - chaoticValue)) /
            1000000000;

        return keccak256(abi.encodePacked(nextState));
    }

    mapping(uint256 => uint256) public votesForChaosExecution;
    mapping(uint256 => mapping(address => bool)) public hasVoted;

    function voteForChaosExecution(uint256 entityId) public {
        require(!hasVoted[entityId][msg.sender], "Already voted");
        votesForChaosExecution[entityId]++;
        hasVoted[entityId][msg.sender] = true;
    }

    function getChaosExecutionStatus(uint256 entityId)
        public
        view
        returns (string memory)
    {
        uint256 votes = votesForChaosExecution[entityId];
        if (votes > 100) {
            return "Chaos execution imminent!";
        } else {
            return "Chaos in deliberation.";
        }
    }

    function autoExecuteChaos(uint256 entityId) public returns (bytes32) {
        ChaosEntity storage entity = chaosEntities[entityId];
        uint256 votes = votesForChaosExecution[entityId];
        require(
            block.timestamp > entity.creationTime + 1 days,
            "Too early to auto-execute"
        );
        require(votes > 100, "Insufficient votes");

        bytes32 result = chaoticLogic(entity.initialState, entity.entropy);
        emit ChaosExecuted(entityId, result);
        return result;
    }

    function entropyDecay(uint256 entityId) public view returns (uint256) {
        ChaosEntity storage entity = chaosEntities[entityId];
        uint256 timeElapsed = block.timestamp - entity.creationTime;
        uint256 decayFactor = timeElapsed / 1 hours;

        return entity.entropy / (1 + decayFactor);
    }
}