Some questions I seek to answer to understand the current state of research:

1. What are the key principles of game theory, cryptoeconomics, and tokenomics?

• Game theory, the branch of mathematics that studies strategic behaviour, where the outcome for each participant or "player" depends on the actions of all. In other words, it provides a mathematical structure for understanding and analyzing decision-making in situations of interdependence.
  • Nash Equilibrium
  • Mechanism Design (reverse game theory), the study of designing strategic situations, the game (rewards, penalties, actions) so that positive externalities are archived.
• Cryptoeconomics, the field that combines economics, game theory and cryptography to study the design and operation of cryptocurrency systems.
  • Using economic incentives to induce the network participants adhere to the protocol and not deviate and do otherwise.
• Tokenomics, the study of the economic systems that can be modeled using tokens.

2. How can game theory and cryptoeconomics be used to model the behavior of provers in Layer 2 networks? Look for studies and papers that have applied game theory and cryptoeconomics to rollups.

3. What are the existing or proposed incentive structures in Layer 2 networks, specifically zkRollups?

What mechanisms are currently used to incentivize provers in these networks? What are the advantages and disadvantages of these structures? What are the factors that influence the effectiveness of incentive structures in Layer 2 networks?

4. What gaps exist in the current understanding of prover incentives in Layer 2 networks?

5. What are known attack vectors in zkRollups and other Layer 2 solutions?

Understanding potential attack vectors will help design a model and simulation that can account for these risks.

6. What economic models have been proposed or used to analyze prover incentives?

Are there existing models that have been used to understand prover incentives? What were their findings, and what limitations did they have?

7. What simulations or practical implementations have been conducted on Layer 2 networks, and what were their results?

Are there existing simulations you can learn from? What methods did they use, and what did they find? What are the challenges of simulating Layer 2 networks? How can the results of simulation be used to improve the design of incentive structures for Layer 2 networks?

Ethereum Economic Model

radCAD: A Python framework for modelling and simulating dynamical systems.
Mesa: Agent-based modeling in Python.