Kinesin is a protein-based natural nanomotor that transports molecular cargoes within cells by walking along microtubules. Kinesin nanomotor is considered as a bio-nanoagent which is able to sense the cell through its sensors (i.e. its heads and tail), make the decision internally and perform actions on the cell through its actuator (i.e. its motor domain). The study maps the agent-based architectural model of internal decision-making process of kinesin nanomotor to a machine language using an automata algorithm. The applied automata algorithm receives the internal agent-based architectural model of kinesin nanomotor as a deterministic finite automaton (DFA) model and generates a regular machine language. The generated regular machine language was acceptable by the architectural DFA model of the nanomotor and also in good agreement with its natural behaviour. The internal agent-based architectural model of kinesin nanomotor indicates the degree of autonomy and intelligence of the nanomotor interactions with its cell. Thus, our developed regular machine language can model the degree of autonomy and intelligence of kinesin nanomotor interactions with its cell as a language. Modelling of internal architectures of autonomous and intelligent bio-nanosystems as machine languages can lay the foundation towards the concept of bio-nanoswarms and next phases of the bio-nanorobotic systems development.
Kinesin and muscle myosin are considered as physical bio-nanoagents able to sense their cells through their sensors, make decision internally, and perform actions through their actuators. This paper has investigated and compared the flexible (reactive, pro-active, and interactive) autonomous behaviors of kinesin and muscle myosin bio-nanorobots. Using an automata algorithm, the agent-based deterministic finite automaton models of the internal decision making processes of the bio-nanorobots (as their reactive and pro-active capabilities) were converted to their respective computational regular languages (as their interactive capabilities). The resulted computational languages could represent the flexible autonomous behaviors of the bio-nanorobots. The proposed regular languages also reflected the degree of the autonomy and intelligence of internal decision-making processes of the bio-nanorobots in response to their environments. The comparison of flexible autonomous behaviors of kinesin and muscle myosin bio-nanorobots indicated that both bio-nanorobots employed regular languages to interact with their environments through two sensors and one actuator. Moreover, the results showed that kinesin bio-nanorobot used a more complex regular language to interact with its environment compared with muscle myosin bio-nanorobot. Therefore, our results have revealed that the flexible autonomous behavior of kinesin bio-nanorobot was more complicated than the flexible autonomous behavior of muscle myosin bio-nanorobot.