Towards blockchain-based robonomics: autonomous agents behavior validation
This addresses the need for trustworthy interactions between autonomous agents and people in decentralized markets, though it is incremental as it builds on existing blockchain and reputation models.
The paper tackles the problem of ensuring reliable service execution by autonomous agents in decentralized trading markets by introducing a validation methodology using Model Checking and finite state automata to detect incorrect liability executions, demonstrated in the Duckietown application with an autonomous mobile robot.
The decentralized trading market approach, where both autonomous agents and people can consume and produce services expanding own opportunities to reach goals, looks very promising as a part of the Fourth Industrial revolution. The key component of the approach is a blockchain platform that allows an interaction between agents via liability smart contracts. Reliability of a service provider is usually determined by a reputation model. However, this solution only warns future customers about an extent of trust to the service provider in case it could not execute any previous liabilities correctly. From the other hand a blockchain consensus protocol can additionally include a validation procedure that detects incorrect liability executions in order to suspend payment transactions to questionable service providers. The paper presents the validation methodology of a liability execution for agent-based service providers in a decentralized trading market, using the Model Checking method based on the mathematical model of finite state automata and Temporal Logic properties of interest. To demonstrate this concept, we implemented the methodology in the Duckietown application, moving an autonomous mobile robot to achieve a mission goal with the following behavior validation at the end of a completed scenario.