Synthesis of Communication Policies for Multi-Agent Systems Robust to Communication Restrictions
Authors: Saleh Soudijani, Rayna Dimitrova
IJCAI 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate our approach experimentally on a range of benchmarks and demonstrate that it is capable of computing pairs of action and communication policies that satisfy the communication restrictions, if such exist. 5 Experimental Evaluation We evaluated our approach on four multi-robot navigation scenarios. |
| Researcher Affiliation | Academia | Saleh Soudijani , Rayna Dimitrova CISPA Helmholtz Center for Information Security, Germany EMAIL |
| Pseudocode | No | The paper presents mathematical formulations and an optimization problem, but it does not include explicitly labeled pseudocode blocks or algorithms. |
| Open Source Code | No | The paper references an extended version on arXiv (https://arxiv.org/abs/2505.13311), but this is a link to a paper, not specifically to source code for the methodology described. |
| Open Datasets | No | The paper describes |
| Dataset Splits | No | The paper describes |
| Hardware Specification | Yes | All experiments were performed on a Macbook Pro with an Apple M2 chip and 32GB memory. |
| Software Dependencies | Yes | The two optimization problems are solved using GLPK [Makhorin, 2000] and SNOPT [Gill et al., 2018], respectively. The reference for SNOPT specifies 'User s guide for snopt 7.7'. |
| Experiment Setup | Yes | In each scenario, we consider a MAS with three agents and K = 2. The possible actions are moving in one of the four cardinal directions or remaining in place. Moves succeed with probability 0.9 and fail, resulting in remaining in the current cell, with probability 0.1. Here, however, the move actions lead to the desired cell with probability 0.9, and the remaining 0.1 probability is redistributed across the current cell and all other neighboring cells. |