# Comprehensive Multi-Agent Epistemic Planning

arXiv: https://arxiv.org/abs/2109.08301 · HTML: https://mlsanity.com/paper/2109.08301/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 30 references that are in the map.
- First posted on arXiv 17 Sep 2021.

## Builds on (most cited first, 8 of 8)

- [The LAMA Planner: Guiding Cost-Based Anytime Planning with Landmarks](https://mlsanity.com/paper/1401.3839/) (2014)
- [Thinking Fast and Slow in AI](https://mlsanity.com/paper/2010.06002/) (2020)
- [A General Multi-agent Epistemic Planner Based on Higher-order Belief Change](https://mlsanity.com/paper/1806.11298/) (2018)
- [Cooperative Epistemic Multi-Agent Planning for Implicit Coordination](https://mlsanity.com/paper/1703.02196/) (2017)
- [An Action Language for Multi-Agent Domains: Foundations](https://mlsanity.com/paper/1511.01960/) (2015)
- [Modelling Multi-Agent Epistemic Planning in ASP](https://mlsanity.com/paper/2008.03007/) (2020)
- [Design of a Solver for Multi-Agent Epistemic Planning](https://mlsanity.com/paper/1909.08259/) (2019)
- [E-PDDL: A Standardized Way of Defining Epistemic Planning Problems](https://mlsanity.com/paper/2107.08739/) (2021)

## Built on by (most cited first, 1 of 1)

- [Architecting Trust in Artificial Epistemic Agents](https://mlsanity.com/paper/2603.02960/) (2026)

## Abstract (arXiv)

Over the last few years, the concept of Artificial Intelligence has become central in different tasks concerning both our daily life and several working scenarios. Among these tasks automated planning has always been central in the AI research community. In particular, this manuscript is focused on a specialized kind of planning known as Multi-agent Epistemic Planning (MEP). Epistemic Planning (EP) refers to an automated planning setting where the agent reasons in the space of knowledge/beliefs states and tries to find a plan to reach a desirable state from a starting one. Its general form, the MEP problem, involves multiple agents who need to reason about both the state of the world and the information flows between agents. To tackle the MEP problem several tools have been developed and, while the diversity of approaches has led to a deeper understanding of the problem space, each proposed tool lacks some abilities and does not allow for a comprehensive investigation of the information flows. That is why, the objective of our work is to formalize an environment where a complete characterization of the agents' knowledge/beliefs interaction and update is possible. In particular, we aim to achieve such goal by defining 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 reason on different domains, e.g., economy, security, justice and politics, where considering others' knowledge/beliefs could lead to winning strategies.