Bridging the Gap: Exploring the Intersection of Blockchain and Reinforcement Learning


Hatched by Glasp

Sep 08, 2023

3 min read


Bridging the Gap: Exploring the Intersection of Blockchain and Reinforcement Learning


The world of technology is constantly evolving, with new advancements reshaping industries and challenging traditional norms. Two areas that have garnered significant attention in recent years are blockchain technology and reinforcement learning (RL). While these fields may seem unrelated at first glance, a closer examination reveals intriguing connections and potential for collaboration.

The Token Disconnect:

Blockchain technology has been met with skepticism by many, who question its practicality and relevance. Some argue that blockchains are a solution in search of a problem, with limited use cases and niche applications. The fundamental question of "For what?" remains unanswered, leaving many hesitant to invest in tokens. This perception of a disconnect between blockchain technology and real-world applications has fueled the debate surrounding its true value.

The Venture Capitalist Perspective:

In contrast to the skepticism surrounding blockchain, venture capitalists perceive crypto as an exciting financial tool. Their primary goal is to generate returns for their limited partners (LPs), and cryptocurrencies offer a unique opportunity to arbitrage securities regulation. The accreditation divide has been a driving force behind the venture capitalist class's fascination with crypto tokens and the ICO mania of 2017.

The allure lies in the fact that these tokens resemble securities but are not regulated as such. This lack of regulation allows for immediate liquidity and the ability to cash out without the need for an initial public offering. The financial engineering aspect of crypto assets is where the true innovation lies, rather than in software engineering. It is a new form of financial product that offers flexibility and potential gains, albeit with regulatory concerns.

Accelerating Reinforcement Learning:

On the other end of the technology spectrum, reinforcement learning (RL) has gained traction as a promising field for training intelligent agents. Researchers have explored various methods to improve RL algorithms, and one intriguing avenue involves integrating human intelligence through implicit feedback.

A recent study focused on capturing human reactions through EEG-based implicit feedback, specifically error-related potentials (ErrP). By incorporating these natural and direct signals from human participants, researchers aim to accelerate RL agent learning. This innovative approach opens up possibilities for human-AI collaboration and the optimization of RL algorithms.

Finding Common Ground:

While seemingly disparate, the worlds of blockchain technology and reinforcement learning share common themes. Both fields have sparked excitement and debate, with proponents envisioning transformative potential. Additionally, they both face challenges in terms of regulation and perception.

One commonality lies in the concept of innovation. Blockchain technology has revolutionized financial engineering, offering new ways to transact and invest. Similarly, RL is pushing the boundaries of AI and machine learning, seeking to create more intelligent and adaptable agents. By recognizing these shared goals, stakeholders in both fields can find opportunities for collaboration and mutual growth.

Actionable Advice:

  • 1. Foster Interdisciplinary Collaboration: Encourage experts from the fields of blockchain technology and reinforcement learning to collaborate and share insights. By bringing together diverse perspectives, new ideas and applications can emerge.
  • 2. Bridge the Gap: Educate stakeholders about the potential synergies between blockchain technology and RL. Highlight the benefits of integrating human intelligence through implicit feedback, showcasing how this can enhance both fields.
  • 3. Embrace Responsible Innovation: While the regulatory landscape for blockchain technology and cryptocurrencies may still be evolving, it is crucial to prioritize responsible practices. Promote transparency, ethical conduct, and compliance to ensure the long-term viability and acceptance of these technologies.


The convergence of blockchain technology and reinforcement learning presents a unique opportunity for innovation and collaboration. By recognizing the shared challenges and potential benefits, stakeholders can work together to bridge the gap and unlock new possibilities. Through interdisciplinary collaboration, responsible innovation, and a focus on shared goals, we can harness the true potential of these transformative technologies.

Hatch New Ideas with Glasp AI 🐣

Glasp AI allows you to hatch new ideas based on your curated content. Let's curate and create with Glasp AI :)