A review of cooperation in multi-agent learning
Cooperation in multi-agent learning (MAL) is a topic at the intersection of numerous
disciplines, including game theory, economics, social sciences, and evolutionary biology …
disciplines, including game theory, economics, social sciences, and evolutionary biology …
Et-hf: A novel information sharing model to improve multi-agent cooperation
Many real-world multi-agent systems require agents to cooperate with each other. However,
it is challenging to generate optimal cooperative strategies (eg, location coordination or …
it is challenging to generate optimal cooperative strategies (eg, location coordination or …
Resolving social dilemmas with minimal reward transfer
Social dilemmas present a significant challenge in multi-agent cooperation because
individuals are incentivised to behave in ways that undermine socially optimal outcomes …
individuals are incentivised to behave in ways that undermine socially optimal outcomes …
Impact of relational networks in multi-agent learning: A value-based factorization view
Effective coordination and cooperation among agents are crucial for accomplishing
individual or shared objectives in multi-agent systems. In many real-world multiagent …
individual or shared objectives in multi-agent systems. In many real-world multiagent …
Influence of team interactions on multi-robot cooperation: A relational network perspective
Relational networks within a team play a critical role in the performance of many real-world
multi-robot systems. To successfully accomplish tasks that require cooperation and …
multi-robot systems. To successfully accomplish tasks that require cooperation and …
Relational Q-Functionals: Multi-Agent Learning to Recover from Unforeseen Robot Malfunctions in Continuous Action Domains
Cooperative multi-agent learning methods are essential in developing effective cooperation
strategies in multi-agent domains. In robotics, these methods extend beyond multi-robot …
strategies in multi-agent domains. In robotics, these methods extend beyond multi-robot …
[PDF][PDF] Resolving social dilemmas through reward transfer commitments
In file sharing networks, users can either act for personal gain by downloading files, or help
the network by uploading files. Similar scenarios are important in many diverse situations …
the network by uploading files. Similar scenarios are important in many diverse situations …
Graph Attention Inference of Network Topology in Multi-Agent Systems
Accurately identifying the underlying graph structures of multi-agent systems remains a
difficult challenge. Our work introduces a novel machine learning-based solution that …
difficult challenge. Our work introduces a novel machine learning-based solution that …
Advances in Multi-agent Reinforcement Learning: Persistent Autonomy and Robot Learning Lab Report 2024
R Azadeh - arXiv preprint arXiv:2412.21088, 2024 - arxiv.org
Multi-Agent Reinforcement Learning (MARL) approaches have emerged as popular
solutions to address the general challenges of cooperation in multi-agent environments …
solutions to address the general challenges of cooperation in multi-agent environments …
Understanding Agent Competency: Effects of Environment Complexity on Area Coverage Time
F Mazzoni, K Jerath - 2022 IEEE Symposium Series on …, 2022 - ieeexplore.ieee.org
As an increasing number of search-and-rescue (SAR) missions begin to incorporate robotic
agents and algorithms to cover search areas, the task of selecting an appropriate algorithm …
agents and algorithms to cover search areas, the task of selecting an appropriate algorithm …