Research on Division of Labor Decision and System Stability of Swarm Robots Based on Mutual Information
Abstract
:1. Introduction
- A mutual information model is built to measure the disparity of information interaction within swarm robot systems. The exponential function is leveraged to convert the mutual information value into a probability. Leveraging this probability value, the assessment of information interaction among diverse robots is conducted to unveil the strategic choices made by individual robots across the disparity of mutual information.
- The division of labor decision-making behavior of swarm robots under different mutual information levels is modeled as a game-theoretic model, exploring the complex dynamical behaviors exhibited by robots during the game process. Based on this, the stability and bifurcation characteristics of the established dynamic game model are analyzed. The impact of system parameter on the dynamic behavior of the model is investigated, leading to the determination of equilibrium stability conditions and complex features.
- The conclusions derived and simulated are as follows: ① When the decision parameter of the game model varies within a certain range, the Nash equilibrium point loses stability and enters a chaotic state. ② As the level of information exchange between robots increases (i.e., increases), the decision-making pattern of robots transitions gradually from the Cournot game to the Stackelberg game. Concurrently, the sensitivity of swarm robotics systems to changes in decision parameter decreases, reducing the likelihood of the system entering a chaotic state.
2. Related Work
2.1. Research Related to Division of Labor and Decision-Making in Swarm Robotic Systems
2.2. Research Related to the Stability of Swarm Robotic Systems
3. Model
- “ (State)” signifies information pertaining to the current condition of the robot, encompassing aspects such as strategy, position, etc.
- “ (Behavior)” embodies the robot’s behavior or decision-making, governing its adaptations and adjustments.
- “ (Network)” is defined as a complete graph that delineates the information links existing between a robot and its neighboring counterparts.
- “ (Utility)” describes the utility of the robot, and each individual robot adapts its strategies aiming to maximize utility.
- “ (Information)” represents the mutual information among robots, reflecting the disparity of information interaction and sharing among them.
3.1. Network Topology
3.2. Mutual Information Model
3.3. Game Model
4. Model Analysis
4.1. Stability Analysis of the System When
4.2. Stability Analysis of the System When
4.3. Stability Analysis of the System When
5. Simulation Analysis
5.1. Parameter Settings
5.2. Simulation
5.2.1. Simulation Analysis When
5.2.2. Simulation Analysis When
5.2.3. Simulation Analysis When
5.2.4. Fractal Phenomenon Simulation Analysis
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Feng, Z.; Sun, Y. Research on Division of Labor Decision and System Stability of Swarm Robots Based on Mutual Information. Sensors 2024, 24, 5029. https://doi.org/10.3390/s24155029
Feng Z, Sun Y. Research on Division of Labor Decision and System Stability of Swarm Robots Based on Mutual Information. Sensors. 2024; 24(15):5029. https://doi.org/10.3390/s24155029
Chicago/Turabian StyleFeng, Zhongyuan, and Yi Sun. 2024. "Research on Division of Labor Decision and System Stability of Swarm Robots Based on Mutual Information" Sensors 24, no. 15: 5029. https://doi.org/10.3390/s24155029