A method and system for implementing a population of bio-inspired agents with consistent memories but different behaviors

Abstract

The application discloses a kind of method for realizing memory consistent but different behavior of biological population, creates a definition line behavior transaction and fills transaction content, after signature, it is submitted to blockchain;Process transaction, save behavior after all check through;Carry out a behavior, check the behavior type;According to different type, complete behavior execution.The application also proposes a kind of system for realizing memory consistent but different behavior of biological population, including consensus manager, data manager and behavior manager, so as to realize the effect of individualized behavior under the premise of consistent data, solve the systemic risk problem caused by the consistent behavior due to the requirement of consistent information.

Description

Technical Field

[0001] This invention relates to the field of blockchain technology, and in particular to a method and system for realizing a biosphere-like community with consistent memory but diverse behaviors. Background Technology

[0002] In the future, with the continuous and rapid development of information technology, information barriers will become increasingly weaker until everyone has virtually identical information. Information is the primary driver of human behavior, and when everyone has the same information, it will lead to a convergence of human behavior. In the current environment of highly centralized and monopolized information, these central institutions often use their information monopoly advantage to drive people to perform certain behaviors. If this ability is not properly controlled or is maliciously exploited, it may have negative consequences and even lead to social regression. For example, a central institution may provide one group with one piece of information and another group with completely contradictory information. Through long-term, continuous guidance and information accumulation, this will lead to conflict between the two groups on the aspects desired by the institution. Alternatively, suppose an honest institution strives to promote and disseminate what it truly believes is beneficial to society. Under the long-term accumulation and guidance of this information, society will gradually converge with the institution's desired direction. However, once the overall social environment changes, the risk resistance of a society with convergent behavior will approach zero. This may lead to systemic risks or even collapse, resulting in social regression. However, without these central institutions to centrally control and guide information, information overload can lead to the depletion of social development momentum in internal conflicts, making healthy social development unsustainable. Therefore, how to achieve a unified, orderly, personalized, and sustainable social infrastructure that allows for centralized information guidance without malicious misuse, enables participants to engage in personalized behaviors, and ensures these diverse behaviors do not lead to internal conflicts, has become an urgent problem to solve. Summary of the Invention

[0003] This invention aims to propose a biosphere-like method and system for achieving consistent memory but diverse behaviors. It designs the concept of a "biosphere-like system," the core idea of ​​which is to put the data of all participants on a blockchain, separate consensus data from business data, and have different algorithms for each node on the blockchain, so that each node can perform different behaviors under the same data basis. This realizes the effect of personalized behavior under the premise of consistent data and solves the systemic risk problem caused by the requirement of consistent behavior in order to achieve consistent information.

[0004] A method and system for achieving a biological community with consistent memory but diverse behaviors, the method comprising:

[0005] S1. Create an empty transaction with defined behavior, fill in the behavior content, sign it, and submit it to the blockchain;

[0006] S2. Start processing the transaction. After all checks are passed, save the actions locally.

[0007] S3. Begin performing an action and check the action type;

[0008] S4. Perform actions according to different behavior types.

[0009] Furthermore, the transaction processing procedure described in step S2 includes:

[0010] S21. Extract transaction details;

[0011] S22. Verify the legality of the transaction; discard the transaction if it is invalid.

[0012] S23. Check if the algorithm for this behavior already exists. If it does, discard the transaction.

[0013] S24, parsing algorithm.

[0014] Furthermore, the process of performing the action described in step S4 includes:

[0015] S41. If it is a consensus behavior, extract the behavior algorithm defined by the transaction; if it is a personalized behavior, extract the local personalized behavior algorithm.

[0016] S42. Obtain the input data required by the algorithm;

[0017] S43. Pass the input into the algorithm for execution;

[0018] S44. Obtain the execution result. If it is a consensus action, submit the execution result to the blockchain.

[0019] Building upon the aforementioned method for achieving biogroups with consistent memory but diverse behaviors, this invention further proposes a system for achieving biogroups with consistent memory but diverse behaviors, the system comprising:

[0020] Consensus Manager: Used to manage the consensus mechanism of the current network;

[0021] Data Manager: Used to manage traditional blockchain data, as well as formulaic and personalized data;

[0022] Behavior Manager: Used to manage the behavior of nodes.

[0023] The system creates an empty transaction with a defined behavior through the behavior manager, fills in the transaction content, signs it, and submits it to the blockchain. The transaction is then processed, and after all checks are passed, the algorithm is parsed. The data manager saves the behavior locally, and the behavior manager starts to perform a behavior, checks the behavior type, and executes the behavior by the consensus manager or the behavior manager. The data manager obtains the execution result. The consensus manager, data manager, and behavior manager are interconnected in a cross-network structure and can access each other's data.

[0024] Furthermore, the consensus manager includes:

[0025] Rule Management Module: Used to define and manage the consensus rules currently supported by the network;

[0026] Consensus Execution Module: Used to execute according to the formula rules defined in the rule management module;

[0027] Extended Consensus Module: Used to bring the extended features and transactions defined in the extension manager into the consensus scope when the current network uses the extension manager.

[0028] Furthermore, the data manager includes:

[0029] Data storage module: Used to store consensus data and personalized data in the current network environment, and to provide a basis for subsequent queries;

[0030] Data query module: Used to provide data based on specific conditions;

[0031] Data interface module: Used to connect to external services.

[0032] Furthermore, the behavior manager includes:

[0033] Behavior definition module: Used to define the types of various behaviors, as well as the algorithms for those behaviors;

[0034] Behavior Execution Module: This module executes the algorithm behind the behavior according to the definition of the behavior type, provides data input for the execution of the algorithm, and collects feedback on the execution results after the execution is completed.

[0035] Compared with the prior art, the present invention has the following advantages:

[0036] (1) This invention achieves the function of personalized behavior while ensuring consistent data, so that information can be guided in a centralized manner and will not be maliciously used.

[0037] (2) This invention solves the systemic risk problem caused by the need for consistent behavior in order to require consistent information, and enhances the ability of society to resist risks;

[0038] (3) The personalized behavior in this invention can be modified or upgraded even during the actual operation of the blockchain, thereby making up for the problem of business development lag caused by the immutability of the consensus mechanism of the blockchain in practical applications. Attached Figure Description

[0039] Figure 1 This is a flowchart illustrating the method for achieving a biological community with consistent memory but different behaviors, as mentioned in this invention.

[0040] Figure 2 This is a flowchart illustrating the transaction processing procedure mentioned in this invention;

[0041] Figure 3 This is a flowchart illustrating the execution process mentioned in this invention;

[0042] Figure 4 This is a schematic diagram of the composition of the biological group system mentioned in this invention, which achieves consistent memory but different behaviors;

[0043] Figure 5 This is a schematic diagram illustrating the composition of the consensus manager mentioned in this invention;

[0044] Figure 6 This is a schematic diagram illustrating the composition of the data manager mentioned in this invention;

[0045] Figure 7 This is a schematic diagram illustrating the composition of the behavior manager mentioned in this invention;

[0046] The module consists of: 100 Consensus Manager; 200 Data Manager; 300 Behavior Manager; 101 Rule Management Module; 102 Consensus Execution Module; 103 Extended Consensus Module; 201 Data Storage Module; 202 Data Query Module; 203 Data Interface Module; 301 Behavior Definition Module; and 302 Behavior Execution Module. Detailed Implementation

[0047] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments. It should be noted that the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0048] In today's highly centralized information environment, central institutions often leverage their information monopoly to guide certain behaviors. However, in a society where behaviors tend to be uniform, the ability to withstand risks is greatly weakened. Conversely, without a central institution to centrally monopolize information for guidance, information overload can hinder societal development. Therefore, to achieve personalized behavior while ensuring consistent data, this invention proposes a method for creating biospheres with consistent memories but diverse behaviors. This method includes the following technical steps:

[0049] This method consists of two main steps. The first is defining a behavior: creating an empty transaction to define the behavior and filling in its details; after all checks are passed, saving it locally. The second is executing the behavior: checking the behavior type and executing the behavior based on the type, obtaining the execution result, such as... Figure 1 As shown:

[0050] S1. Create an empty transaction with defined behavior and fill in the behavior content, including the behavior name and behavior algorithm, sign it and submit it to the blockchain;

[0051] S2. Start processing the transaction. After all checks are passed, save the actions locally.

[0052] S3. Begin performing an action and check the action type;

[0053] S4. Perform actions according to different behavior types.

[0054] like Figure 2 As shown, in this embodiment, the transaction processing procedure in step S2 includes:

[0055] S21. Extract transaction details;

[0056] S22. Verify the legality of the transaction; discard the transaction if it is invalid.

[0057] S23. Check if the algorithm for this behavior already exists. If it does, discard the transaction.

[0058] S24, parsing algorithm.

[0059] like Figure 3 As shown, in this embodiment, the process of performing the action described in step S4 includes:

[0060] S41. If it is a consensus behavior, extract the behavior algorithm defined by the transaction; if it is a personalized behavior, extract the local personalized behavior algorithm.

[0061] S42. Obtain the input data required by the algorithm;

[0062] S43. Pass the input into the algorithm for execution;

[0063] S44. Obtain the execution result. If it is a consensus action, submit the execution result to the blockchain.

[0064] like Figure 4 As shown, this invention also proposes a biosphere system that achieves consistent memory but diverse behaviors. The system includes the following components and their functions:

[0065] Consensus Manager 100: This manages the consensus mechanism of the current network. It is the foundation for nodes to join the entire network and the most basic behavioral basis for nodes to participate in the network. In this invention, the consensus manager adds support for consistency extensions regarding external behavioral constraints on top of the traditional blockchain consensus manager. When certain external behaviors require unanimity from all participants, these requirements are added to the consensus through this mechanism. If individual participation from each participant is required, these requirements are removed from this mechanism. The specific additions and removals are implemented by the upper-layer application. The specific consensus rules here are also predefined by the provider of the upper-layer application.

[0066] Data Manager 200: This manages traditional blockchain data, as well as consensus data and personalized data. Consensus data is the foundation for consensus protocols and, in some cases, is part of the traditional blockchain data. In consensus expansion, it is processed and stored as separate consensus data. Personalized data is often generated by node behavior. This data is often unrelated to the consensus mechanism but is the basis for driving node behavior and serves as the input to node behavior algorithms. The scale of data managed here varies depending on the upper-layer application and the level of intelligence required. For logical processing that can be completed by ordinary checking algorithms, the amount of data here will be much smaller than the amount of data in the blockchain itself. However, when artificial intelligence-level data is required, it will involve much larger-scale data storage.

[0067] Behavior Manager 300: Manages node behavior, including consensus behavior and personalized behavior. Consensus behavior drives the consensus manager to join the network and reach data agreement. Personalized behavior involves performing customized calculations based on data provided by the data manager to derive its own behavior, while still adhering to the basic requirements of the consensus mechanism. Because personalized behavior is not part of the consensus mechanism, it can be randomly upgraded or modified even during actual blockchain operation. This allows for mitigation of the problem of business development lagging behind due to the immutability of the consensus mechanism in practical applications.

[0068] The specific workflow of the system includes:

[0069] The system creates an empty transaction defining a behavior through the behavior manager 300, fills in the transaction content, signs it, and submits it to the blockchain. After the transaction is processed and all checks are passed, the algorithm is parsed. The data manager 200 saves the behavior locally, and the behavior manager 300 starts to perform a behavior, checks the behavior type, and executes the behavior by the consensus manager 100 or the behavior manager 300. The data manager 200 obtains the execution result. The consensus manager 100, data manager 200, and behavior manager 300 are interconnected in a cross-network mesh and can access each other's data.

[0070] like Figure 5 As shown, preferably, the consensus manager 100 includes:

[0071] Rule Management Module 101: Used to define and manage the consensus rules currently supported by the network. To support the implementation in this invention, at least one rule needs to be provided here. This rule is defined in code before the network goes live.

[0072] Consensus Execution Module 102: Used to execute according to the consensus rules defined in the rule management module. Depending on the upper-layer business, this may be defined as a formula or an immutable rule initially written in code.

[0073] Extended Consistency Module 103: When the current network uses an extension manager, it incorporates the extended functions and transactions defined in the extension manager into the consensus scope. In this case, the consensus no longer cares about the specific extended functions and services, but only whether the inputs and outputs of the extension are consistent with other nodes. It also supports constraining behaviors requiring unanimous agreement in the behavior manager through consensus.

[0074] like Figure 6 As shown, preferably, the data manager 200 includes:

[0075] Data storage module 201: Used to store consensus data and personalized data in the current network environment, providing a basis for subsequent queries. When the data volume is small, the same storage method as blockchain data is used; when the data reaches a large storage scale, external storage can be connected.

[0076] Data Query Module 202: This module is used to provide data based on specific conditions. The data here includes both blockchain-related data and node-specific data. When a node provides personalized data, it also needs to provide methods for querying this data.

[0077] Data Interface Module 203: Used to connect to external services. When external services need to provide data, they submit requests through the interface module. The data query module organizes and extracts the data and returns it to the data requester. The data interface module is the entry point for other modules to use data.

[0078] like Figure 7 As shown, preferably, the behavior manager 300 includes:

[0079] Behavior definition module 301: Used to define the types of various behaviors and the algorithms for those behaviors. These algorithms are provided by the developers initially, and behaviors that are not based on consensus can be dynamically defined later.

[0080] Behavior execution module 302: is used to execute the algorithm behind the behavior according to the definition of the behavior type, provide data input for the execution of the algorithm, and collect feedback execution results after the execution is completed.

[0081] Compared to existing information monopoly methods using centralized institutions, this invention designs a "biosphere-like" concept, placing all participants' data on a blockchain as the basis for participant memory. It separates consensus data from business data, allowing each node on the blockchain to exhibit different behaviors under the same data foundation. This solves the systemic risk problem caused by consistent behavior due to information consistency, while eliminating additional internal friction. It's important to note that although this invention is described specifically for a blockchain scenario, the same method can be applied to any scenario requiring the preservation of participant individuality. Some of its ideas can also be applied to other business scenarios based on the same principles.

[0082] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the technical scope of the present invention. Therefore, any changes or modifications made in accordance with the claims and description of the present invention should fall within the scope of the patent of the present invention.

Claims

1. A method for achieving a biological swarm with consistent memory but diverse behaviors, characterized in that, The method of placing all participants' data on a blockchain, enabling each node to perform different actions on the same data basis, includes: S1. Create an empty transaction with defined behavior, fill in the behavior content, sign it, and submit it to the blockchain; S2. Start processing the transaction. After all checks are passed, save the actions locally. S3. Begin performing an action and check the action type; S4. Perform actions according to different behavior types; The process of performing the action described in step S4 includes: S41. If it is a consensus behavior, extract the behavior algorithm defined by the transaction; if it is a personalized behavior, extract the local personalized behavior algorithm. S42. Obtain the input data required by the algorithm; S43. Pass the input into the algorithm for execution; S44. Obtain the execution result. If it is a consensus action, submit the execution result to the blockchain.

2. The method for achieving a biological community with consistent memory but diverse behaviors according to claim 1, characterized in that, The transaction processing procedure described in step S2 includes: S21. Extract transaction details; S22. Verify the legality of the transaction; discard the transaction if it is invalid. S23. Check if the algorithm for this behavior already exists. If it does, discard the transaction. S24, parsing algorithm.

3. A biological swarm system that achieves consistent memory but diverse behaviors, characterized in that, By placing all participants' data on the blockchain, each node can perform different actions based on the same data foundation. The process of executing actions according to different action types includes: S41. If it is a consensus behavior, extract the behavior algorithm defined by the transaction; if it is a personalized behavior, extract the local personalized behavior algorithm. S42. Obtain the input data required by the algorithm; S43. Pass the input into the algorithm for execution; S44. Obtain the execution result. If it is a consensus action, submit the execution result to the blockchain. The system includes: Consensus Manager: Used to manage the consensus mechanism of the current network; Data Manager: Used to manage traditional blockchain data, as well as consensus data and personalized data; Behavior Manager: Used to manage the behavior of nodes; The system creates an empty transaction with a defined behavior through the behavior manager, fills in the transaction content, signs it, and submits it to the blockchain. The transaction is then processed, and after all checks are passed, the algorithm is parsed. The data manager saves the behavior locally, and the behavior manager starts to perform a behavior, checks the behavior type, and executes the behavior by the consensus manager or the behavior manager. The data manager obtains the execution result. The consensus manager, data manager, and behavior manager are interconnected in a cross-network structure and can access each other's data.

4. A biological swarm system that achieves consistent memory but diverse behaviors according to claim 3, characterized in that, The consensus manager includes: Rule Management Module: Used to define and manage the consensus rules currently supported by the network; Consensus Execution Module: Used to execute according to the formula rules defined in the rule management module; Extended Consensus Module: Used to bring the extended features and transactions defined in the extension manager into the consensus scope when the current network uses the extension manager.

5. A biological swarm system according to claim 3 that achieves consistent memory but diverse behaviors, characterized in that, The data manager includes: Data storage module: Used to store consensus data and personalized data in the current network environment, and to provide a basis for subsequent queries; Data query module: Used to provide data based on specific conditions; Data interface module: Used to connect to external services.

6. A biological swarm system according to claim 3 that achieves consistent memory but diverse behaviors, characterized in that, The behavior manager includes: Behavior definition module: Used to define the types of various behaviors, as well as the algorithms for those behaviors; Behavior Execution Module: This module executes the algorithm behind the behavior according to the definition of the behavior type, provides data input for the execution of the algorithm, and collects feedback on the execution results after the execution is completed.

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