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Aston University researchers have developed an artificial intelligence system to manage traffic more efficiently at intersections.

The Belief-Desire-Intention (BDI) architecture is a widely-used model for developing multi-agent systems. BDI agents pursue their goals over time using a collection of plan recipes that are programmed by the developers. Thus, traditional BDI agents are limited in dealing with dynamic environments where uncertainties are not known beforehand, such as those introduced by adversarial forces. In this paper, we present the BDI-Dojo framework for developing robust BDI agents by training them using reinforcement learning against similarly learning-equipped adversarial agents. This adversarial trainin...

Multi-agent learning has been widely used to enable multiple agents to autonomously find solutions for complex tasks such as robotic swarm control, social order maintenance, and transportation management. To date, various multi-agent learning approaches have been developed with various capabilities such as having teaching skills and utilising collective intelligence. Despite the progress, there are still various research challenges to be addressed to advance the usage of multi-agent learning. Specifically, this thesis tries to address three challenges, which are: 1. to accelerate multi-agent l...