BLOCKCHAIN -BASED DECENTRALIZED KNOWLEDGE MARKETPLACE USING ACTIVE INFERENCE Shashank Joshi

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BLOCKCHAIN-BASED DECENTRALIZED KNOWLEDGE

MARKETPLACE USING ACTIVE INFERENCE

Shashank Joshi

Department of Computer Science and Engineering

SRM Institute Of Science And Technology

Kattankulathur, Tamil Nadu – 603203,

sj8559@srmist.edu.in

Arhan Choudhury

Department of Computer Science and Engineering

SRM Institute Of Science And Technology

Kattankulathur, Tamil Nadu – 603203,

ac8365@srmist.edu.in

ABSTRACT

A knowledge market can be described as a type of market where there is a consistent

supply of data to satisfy the demand for information and is responsible for the map-

ping of potential problem solvers with the entities which need these solutions. It is

possible to deﬁne them as value-exchange systems in which the dynamic features of

the creation and exchange of intellectual assets serve as the fundamental drivers of the

frequency, nature, and outcomes of interactions among various stakeholders. Further-

more, the provision of ﬁnancial backing for research is an essential component in the

process of developing a knowledge market that is capable of enduring over time, and

it is also an essential driver of the progression of scientiﬁc investigation. This paper

underlines ﬂaws associated with the conventional knowledge-based market, including

but not limited to excessive ﬁnancing concentration, ineffective information exchange,

a lack of security, mapping of entities, etc. The authors present a decentralized frame-

work for the knowledge marketplace incorporating technologies such as blockchain,

active inference, zero-knowledge proof, etc. The proposed decentralized framework

provides not only an efﬁcient mapping mechanism to map entities in the marketplace

but also a more secure and controlled way to share knowledge and services among

various stakeholders.

Keywords

DAO

Blockchain

Knowledge

Marketplace

Active Inference

Decentralization

Free Energy

1 Introduction

To be successful in today’s extremely competitive and knowledge-based economy, businesses need to be able to

handle huge amounts of information and services effectively. This kind of information and service is extremely

sophisticated, not to mention that it is incredibly diverse, and it is expanding at an ever-increasing rate. Over

the course of time, different knowledge management strategies have emerged [

], and It is apparent that the

preponderance of the studies and developments have been concentrated on the management of knowledge

within organizations, which is where a large number of issues have been resolved [

]. Nevertheless, this opens

up a window of opportunity for organizations or individuals to economically utilize their knowledge assets

arXiv:2210.01688v1 [cs.CR] 4 Oct 2022

[

], and the phenomena of utilizing the crowd’s knowledge assets against commercialization give rise to the

concept of knowledge markets. Nevertheless, the existing knowledge monetizing ecosystem is inefﬁcient and

thus undermines the productivity of the whole knowledge-sharing sector due to its inherent structural and

operational intricacies.

To begin with, research funding is a crucial facet of a sustaining knowledge marketplace, and the structure of

the current knowledge market is inherently characterized by the disparity in research spending [

]. Furthermore,

one of the main causes of this discrepancy is an improper mapping of the parties who would be interested in

a research consignment (which usually culminates in the interchange and commercialization of knowledge

assets). In addition, the fact that prominent players are involved in this sector is another factor that adds to

the problem of excessive funding concentration [

]. Next, the conventional knowledge market framework

is also cluttered with a plethora of intricacies, which, in turn, leads to inefﬁcient information ﬂow between

the stakeholders. Lastly, other problems associated with the conventional knowledge trade include a lack of

information security, privacy, access control, ownership transfer, and transparency.

In order to resolve the aforementioned issues and to streamline the exchange of knowledge assets, this paper

proposes a novel decentralized framework in order to construct a trustworthy and functional knowledge

marketplace, which employs active inference-based free energy analysis for the efﬁcient mapping of the

stakeholders for a research contract along with blockchain’s innate qualities including but not limited to

immutability, secure, distributed, fraud resilience etc. which based on its cutting-edge data cryptographic

techniques, assures both the security of the data as well as the user’s identiﬁcation. To avoid the issues of a

centralized framework in which all information and knowledge is held by a limited number of parties, the

proposed framework makes use of current advancements in computing technology to establish a ﬂexible and

distributed network. To facilitate each party’s contribution, the framework allows for not only the sharing of

information but also the trading of expertise and services.

The paper addresses four foundational facets of the knowledge marketplace. First, it veriﬁes and assesses

whether or not the researchers and the investors are a good ﬁt for one another. Second, the proposed framework

guarantees equitable monetization, meaning that both the investor and the knowledge seller should beneﬁt from

the knowledge monetization, and the knowledge buyer should obtain the knowledge after payment has been

received. Third, ensure that the information is not divulged to any other parties until the process of knowledge

monetization has been fully completed, thus ensuring the conﬁdentiality of intellectual assets. Finally, the

proposed architecture also streamlines all the interactions and processes among various stakeholders of the

network.

The remaining sections of this paper are structured as follows: Section 2 provides some context or preliminary

information on this work. Next, Section 3 provides a summary of the current attempts to digitize the

knowledge economy, including a review of the relevant research and associated works. The working of

the knowledge marketplace is outlined in section 4. Section 5 of the paper then describes the conventional

knowledge exchange system along with its ﬂaws. Then, Section 6 elaborates on the proposed framework for

the knowledge marketplace and its potential outcome on the knowledge monetization sector. Finally, The

paper is concluded in section 7, along with some recommendations for further research.

2 Background

2.1 Blockchain

A decentralized distributed ledger that can only be appended to and has a synchronization mechanism

constitutes a blockchain network. It logs every transaction and veriﬁes the origin of any assets involved

in those transactions in chronological order using cryptographic links between each block. Blockchain

technology, in contrast to centralized apps found on the internet, does not have a single controlling authority.

The distributed ledger system (blockchain) consists of a network of nodes, each of which copies the ledger. It

is seen in a public capacity by every user that is connected to the network [

]. Because only the wallet address

may be matched to a transaction, all of the transactions are open to public scrutiny while maintaining a veneer

of anonymity [

]. The ﬁrst practical implementation of blockchain technology was the "cryptocurrency"

Figure 1: Architecture Of Blockchain Network

Bitcoin [

], which is also known as a "decentralized digital currency" that is veriﬁed by encryption. After that,

a plethora of brand-new currencies, each with their own set of distinctive characteristics, such as Ethereum [

emerged. The basic architecture of a blockchain network is illustrated in Figure 1.

2.2 Active Inference

Active inference is a theory that describes perception, planning, and action in terms of probabilistic inference.

It is a way of describing sentient activity [

]. Active inference, which theoretical neuroscientist Karl Friston

created during years of ground-breaking research, offers an integrated viewpoint on the brain, cognition, and

behaviour that is increasingly employed in various ﬁelds, including neuroscience, psychology, and philosophy.

Active inference translates observation into action. Active inference’s theory, applications, and cognitive

domains simulate various complex systems.

By framing behaviour and the brain in terms of a single drive to reduce free energy, active inference is a

"ﬁrst principles" approach to understanding behaviour and the brain. In order to comprehend how the brain

functions, there is a strong emphasis on the implications of the free energy principle. In order to contextualize

active inference within the most recent theories of cognition, it is ﬁrst introduced theoretically and formally. It

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BLOCKCHAIN-BASEDDECENTRALIZEDKNOWLEDGEMARKETPLACEUSINGACTIVEINFERENCEShashankJoshiDepartmentofComputerScienceandEngineeringSRMInstituteOfScienceAndTechnologyKattankulathur,TamilNadu603203,sj8559@srmist.edu.inArhanChoudhuryDepartmentofComputerScienceandEngineeringSRMInstituteOfScienceAndTechnologyKa...

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BLOCKCHAIN -BASED DECENTRALIZED KNOWLEDGE MARKETPLACE USING ACTIVE INFERENCE Shashank Joshi

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