TL;DR
The paper introduces SASS, a multi-agent system framework designed to enhance cooperation and automation in distributed AI, bridging perception to learning for improved collective decision-making.
Contribution
It proposes a novel self-adaptive framework for multi-agent cooperation that integrates multiple levels of automation in distributed AI systems.
Findings
Framework enables improved coordination among agents
Bridges automation gaps from perception to learning
Enhances collective decision-making capabilities
Abstract
Distributed artificial intelligence (DAI) studies artificial intelligence entities working together to reason, plan, solve problems, organize behaviors and strategies, make collective decisions and learn. This Ph.D. research proposes a principled Multi-Agent Systems (MAS) cooperation framework -- Self-Adaptive Swarm System (SASS) -- to bridge the fourth level automation gap between perception, communication, planning, execution, decision-making, and learning.
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Taxonomy
TopicsAI-based Problem Solving and Planning