[robotics-worldwide] [jobs] multiple jobs on Multi-agent and collaborative AI/Human-like artificial intelligence at VUB
Bram.Vanderborght at vub.be
Tue Jul 16 00:32:03 PDT 2019
Jobs for AI/Robotics in Flanders project
The Vrije Universiteit Brussels has several jobs available as part of a larger project to stimulate AI/Robotics in Flanders. These jobs are on the PhD and on the Postdoc level, are fully funded and have a small budget for travel and equipment. More details of each job can be found by clicking on the links below. More information can be found here https://urldefense.proofpoint.com/v2/url?u=https-3A__ai.vub.ac.be_node_1687&d=DwIGaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=p6wkHBd6_oSPOtMXVFOYth2873EBEskz7buq--c1Zaw&s=FfwTP7kTJfEyJTd6Yr2rtBK95hay8r3lqlMvosbIgG8&e=
The AI Flanders project is an overarching project involving all Flemish universities and several research institutes, aiming to stimulate AI research in Flanders, both on the academic and industrial level. The project consists of four grand challenges, of which the VUB is involved in two, namely multi-agent and collaborative AI and human-like artificial intelligence.
Multi-agent and collaborative AI
The goal of this grand challenge is to research how multiple AI agents, each with their own goals can collaborate to reach a joint desired state. The overall long-term goal of this challenge is to develop multi-agent AI systems that are able to cope with open-ended problems, where new (kinds of) agents enter the system, with new capabilities and goals, and to integrate them seamlessly, keeping the system viable. Aspects that are investigated in this challenge include joint multi-agent online learning (how to learn efficiently or transfer knowledge, while respecting constraints and privacy), robustness in dynamic multi-agent systems (how to update the system when agents join or leave; how to avoid agents gaming the system), strategic decision making (how to recognize, reason and anticipate on the decision making of other agents), collaborative decentralized query execution (how to cooperatively solve queries in privacy-sensitive environments), and information gathering and sharing (how to learn and share new information in a MAS without compromising privacy). There are several proofs of concept foreseen for the research in this challenge: machine fleet control, assembly, and healthcare.
Human-like artificial intelligence
The goal of this Challenge is to design and build autonomous, intelligent, trustworthy entities that communicate and collaborate seamlessly with humans in natural and complex environments. This entails communication in ways that are natural for humans, such as natural language, but also the ability to provide multi-step human-like reasoning by perceiving and understanding the complex environment. This will allow to enhance society and workplace with artificial entities that can clearly understand the environment they are interacting with, feature the same level of adaptivity to unseen tasks as humans, while appropriately interpreting the social and physical environment, and involving, informing and supporting human colleagues.
This focus on complex reasoning in an interaction between man, machine and its environment, as human intelligence and physical capabilities work in harmony with machines via intuitive and social interaction, has strong potential in domains such as industry, mobility & society. Increasing the reasoning and understanding capabilities of AI systems and facilitating seamless interaction with intelligent technology has both short term application domains in more predictable environments and allows – in the long term – to achieve human-like intelligence.
List of available jobs
Multi-agent and distributed AI
· Distributed data intelligence preferably filled by a PhD student, but good PostDocs will also be considered
· Hybrid MAS: A PhD position and a short-term visiting postdoc position
· Fleet Control: A PhD position and a short-term visiting postdoc position
· Co-operating agents and robots: A PhD position and a postdoc position
· Formal verification of Multi-agent systems: A PhD position and a short-term visiting postdoc position Human-like Artificial Intelligence
· Acquiring domain knowledge through natural language dialogue PhD position
· Sequential Hierarchical Learning Systems A PhD position and a postdoc position
· Explainable constraint solving PhD position or post-doc
How to apply
Pls check: https://urldefense.proofpoint.com/v2/url?u=https-3A__ai.vub.ac.be_node_1687&d=DwIGaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=p6wkHBd6_oSPOtMXVFOYth2873EBEskz7buq--c1Zaw&s=FfwTP7kTJfEyJTd6Yr2rtBK95hay8r3lqlMvosbIgG8&e=
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