Conditional Max-Sum for Asynchronous Multiagent Decision Making
Dimitrios Troullinos, Georgios Chalkiadakis, Ioannis Papamichail,, Markos Papageorgiou

TL;DR
This paper introduces Conditional Max-Sum, a novel message-passing algorithm for asynchronous multiagent decision making in dynamic environments like lane-free traffic, improving coordination among automated vehicles.
Contribution
The paper proposes a new asynchronous message-passing algorithm, Conditional Max-Sum, and a realistic communication framework for Factor Graphs in multiagent systems.
Findings
Enhanced coordination in lane-free traffic scenarios.
Conditional Max-Sum outperforms standard Max-Sum in asynchronous settings.
Effective decision-making in complex multiagent environments.
Abstract
In this paper we present a novel approach for multiagent decision making in dynamic environments based on Factor Graphs and the Max-Sum algorithm, considering asynchronous variable reassignments and distributed message-passing among agents. Motivated by the challenging domain of lane-free traffic where automated vehicles can communicate and coordinate as agents, we propose a more realistic communication framework for Factor Graph formulations that satisfies the above-mentioned restrictions, along with Conditional Max-Sum: an extension of Max-Sum with a revised message-passing process that is better suited for asynchronous settings. The overall application in lane-free traffic can be viewed as a hybrid system where the Factor Graph formulation undertakes the strategic decision making of vehicles, that of desired lateral alignment in a coordinated manner; and acts on top of a rule-based…
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Taxonomy
TopicsMetaheuristic Optimization Algorithms Research · Neural Networks and Applications · Fuzzy Logic and Control Systems
