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Modelling and verification of reconfigurable multi-agent systems.
Yehia Abd Alrahman1, Nir Piterman1
1University of Gothenburg, Gothenburg, Sweden.
Autonomous Agents and Multi-Agent Systems
|November 15, 2021
Summary
We introduce a new framework for modeling reconfigurable multi-agent systems, enabling agents to dynamically adapt and communicate for complex tasks. This research enhances reasoning about agent intentions and communication protocols in dynamic environments.
Area of Science:
- Artificial Intelligence
- Computer Science
- Robotics
Background:
- Multi-agent systems require formalisms for dynamic reconfiguration and complex interactions.
- Existing models often lack explicit reasoning about agent intentions and adaptive communication.
Purpose of the Study:
- To propose a novel formalism for modeling and reasoning about reconfigurable multi-agent systems.
- To extend temporal logic for explicit reasoning on agent intentions and communication protocols.
Main Methods:
- Representing systems as sets of agents with local states, interacting via message exchange.
- Extending Linear Temporal Logic (LTL) to incorporate agent intentions and communication protocols.
- Analyzing the complexity of satisfiability and model-checking for the extended logic.
Main Results:
- A formalism enabling agents to dynamically synchronize, exchange data, adapt behavior, and reconfigure interfaces.
- An extended LTL capable of explicit reasoning about agent intentions and communication protocols.
- Complexity analysis of satisfiability and model-checking for the proposed formalism.
Conclusions:
- The proposed formalism provides a robust framework for modeling and reasoning about complex, reconfigurable multi-agent systems.
- The extended LTL enhances the ability to analyze agent interactions and communication in dynamic environments.
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