Research Assistant in Multi-agent Neuro-symbolic
1 week ago
Professor Alessandra Russo has recently won a research grant funded by ARL (US) to develop novel neuro-symbolic reinforcement learning algorithms in the context of cooperative multi-agent systems. This post of Research Assistant is to conduct world-leading research on the formalisation, implementation and experimentation of such a framework, in collaboration with UCLA, Cardiff University and University of Ferrara (Italy).
While based at Imperial College, this post-holder will work in collaboration with a large team composed of postdoc researchers and academics from UCLA, Cardiff University and University of Ferrara as well as researchers from ARL).
**Duties and responsibilities**:
More specifically, the research task concerns the development of a neurosymbolic MARL approach based on the concept of reward machine in RL, that leverages a seamless integration of decentralised RL and symbolic machine learning. The work involved theoretical contributions as well as engineering and experimental work. Problems such as communication among agents, asynchrnonicity of the learning processes and physical constraints (e.g., communication delays) will need to be considered in order to realise a practical MARL system. Evaluation will be performed using a simulation environment of the physical world, provided by the UCLA collaborators, and in the while using Go1 Robots.
**Essential requirements**:
- A Master’s degree (or equivalent) in computer science or a related area.
- Experience in Symbolic machine learning, in particular use of logic-based learning systems.
- Knowledge in Logic, Answer Set Programming and Reinforcement Learning.
- Excellent communication skills and ability to work with others.
- Ability to organise your own work and set priorities to meet deadlines.
Please see job description for full list of requirements.
**Further information**:
- A full CV, with a list of all publications
- A 1-page research statement indicating what you see are interesting research issues relating to the above post and why your expertise is relevant.
**Documents**:
- Research Assistant JD.pdf
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