The Humboldt-Universität zu Berlin invites applications for a PhD position for the Cluster of Excellence “Science of Intelligence”.

What are the principles of intelligence, shared by all forms of intelligence, no matter whether artificial or biological, whether robot, computer program, human, or animal? And how can we apply these principles to create intelligent technology?

Answering these questions – in an ethically responsible way – is the central scientific objective of the new Cluster of Excellence Science of Intelligence (www.scienceofintelligence.de), where researchers from a large number of analytic and synthetic disciplines – artificial intelligence, machine learning, control, robotics, computer vision, behavioural biology, psychology, educational science, neuroscience, and philosophy – join forces to create a multi-disciplinary research program across universities and research institutes in Berlin. Interdisciplinary research projects have been defined (https://www.scienceofintelligence.de/research/projects), which combine analytic and synthetic research and which address key aspects of individual, social, and collective intelligence.

Weighing personal and social information in cooperative problem solving

A fundamental challenge in collective decision making is the integration of personal and social information. Relying too heavily on personal information prevents the spread of information among group members, whereas relying too heavily on social information may hamper profitable personal exploration. This project investigates this key process by studying how collectives of different complexities dynamically balance personal and social information use across different levels of environmental complexity to achieve collective intelligence. This is a joint research project in which we will study these processes in human groups and robotic swarms simultaneously using similar experimental paradigms: collective spatial search tasks. In human groups, we plan to use immersive reality: humans will control avatars in the virtual work and collectively search for resources. This approach allows full experimental control, providing an ideal testbed for studying cooperative problem solving in human groups. For robotic groups, we plan to use swarms of Thymio II robots, performing collective spatial search tasks. Both systems will be probed with collective search tasks of increasing complexity, starting with simple binary resources, and working towards more complex probabilistic resource environments (e.g. spatial multi-armed bandits). Human and robotic experimentation will continuously interact aided by agent-based modeling and robotic simulators.

Doctoral project “Collective spatial search in robot swarms: taming uncertainty together”

This PhD project focuses on the swarm robotics experiments of this project. These experiments will investigate how robotic swarms can successfully search spatial landscapes collectively. We are interested both in the performance of fixed strategies across different environments, as well as how robots can learn to balance exploration/exploitation tradeoffs when facing dynamic and probabilistic environments. We will make use of mobile robots (e.g. Thymio II robot). Robots will be equipped with light sensors and have to collectively search for light beams in arenas, communicating with each other over infrared. To generalize derived insights from robotic experimentation, we plan to use agent-based modeling. Core tasks of the candidate constitute programing, conducting and analyzing the robotic swarm experiments, and performing agent-based simulations. The PhD student will work closely together with a postdoc who, in parallel, will investigate similar processes in human groups.

Applicants must hold a MSc (or be close to completion) in Computer Science, Robotics, Information Science or related disciplines and should have proven skills/affinity with the following topics:

• conducting experiments with mobile robots
• programming skills in the context of robotics (e.g., Python, C/C++)
• programming skills in the context of agent-based modelling (e.g., Matlab, R)
• preference for candidate with experience in evolutionary computation, and/or models of collective behaviour
• experience in working in collaborative research activities including multidisciplinary teams

 Candidates should upload their application preferably via the portal www.scienceofintelligence.de/jobs in order to receive full consideration.

Applications should include: motivation letter, curriculum vitae, transcripts of records (for both BSc and MSc), copies of degree certificates (BSc, MSc), abstracts of Bachelor-, Master -thesis, list of publications and one selected manuscript (if applicable), two names of qualified persons who are willing to provide references, and any documents candidates feel may help us assess their competence.