Design of a Solver for Multi-Agent Epistemic Planning
This work addresses the need for automated reasoning tools in multi-agent systems, offering a novel approach to epistemic planning that could enhance strategies in domains such as politics and justice, though it appears incremental in building on existing epistemic logic concepts.
The paper tackles the problem of formalizing and implementing a solver for multi-agent epistemic planning, which involves reasoning about agents' knowledge and beliefs in dynamic domains, resulting in a new action-based language and an epistemic planner designed for flexibility across various domains like economy and security.
As the interest in Artificial Intelligence continues to grow it is becoming more and more important to investigate formalization and tools that allow us to exploit logic to reason about the world. In particular, given the increasing number of multi-agents systems that could benefit from techniques of automated reasoning, exploring new ways to define not only the world's status but also the agents' information is constantly growing in importance. This type of reasoning, i.e., about agents' perception of the world and also about agents' knowledge of her and others' knowledge, is referred to as epistemic reasoning. In our work we will try to formalize this concept, expressed through epistemic logic, for dynamic domains. In particular we will attempt to define a new action-based language for multi-agent epistemic planning and to implement an epistemic planner based on it. This solver should provide a tool flexible enough to be able to reason on different domains, e.g., economy, security, justice and politics, where reasoning about others' beliefs could lead to winning strategies or help in changing a group of agents' view of the world.