[CFP] Neuro-symbolic AI for Agent and Multi-Agent systems [NeSyMAS] Workshop

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Neuro-symbolic AI for Agent and Multi-Agent systems [NeSyMAS] Workshop
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The NeSyMAS workshop forms part of the AAMAS 2023 conference taking place
in London, UK on 29th May-2nd June 2023.

* CfP link: https://easychair.org/cfp/nesymas2023
* Paper submission link: https://easychair.org/conferences/?conf=nesymas2023

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Call for Papers
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AI has vast potential, some of which has been realised by developments in
deep learning methods. However, it has become clear that these approaches
have reached an impasse and that such “sub-symbolic” or “neuro-inspired”
techniques only work well for certain classes of problem and are generally
opaque to both analysis and understanding. “Symbolic” AI techniques, based
on rules, logic and reasoning, while not as efficient as “sub-symbolic”
approaches, have better behaviour in terms of transparency, explainability,
verifiability and, indeed, trustworthiness. A new direction described as
“neuro-symbolic” AI combines the efficiency of “sub-symbolic” AI with the
transparency of “symbolic” AI. This combination potentially provides a new
wave of AI systems that are both interpretable and elaboration tolerant and
can integrate reasoning and learning in a very general way.

Though there is ample work on neuro-symbolic AI for competing with
classical ML models, such as its use of label-free supervision and graph
embeddings, there is much less on the use for agent modelling or
multi-agent systems. Especially in a multi-agent context, the use of
symbolic models for mental state reasoning together with low-level
perception patterns or the formation of reasoning-capable representations
from subsymbolic data, all represent promising areas where MAS offers a
unique perspective. This workshop’s aim is thus to assemble leading-edge
work in which neuro-symbolic AI approaches and MAS interact.

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Relevant Topics
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Topics of interest include, but are not limited to, the following:
- Explicit agency in neuro-symbolic multi-agent systems
- Neuro-symbolic Reinforcement Learning
- Neuro-symbolic robotics and planning
- Mental models and epistemic logics for MAS
- Multiagency flavours
- Symbolic knowledge representations for subsymbolic MAS
- Neural-symbolic multi-agent systems
- Hybrid agent architectures
- Formal analysis of neural-symbolic multi-agent systems

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Submission Information
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We welcome unpublished technical papers of up to 8 pages, and short (2-4
pages) position papers. Papers should be written in English, be prepared
for single-blind reviewing, be submitted as a PDF document, and conform to
the formatting guidelines of AAMAS 2023:
https://aamas2023.soton.ac.uk/wp-content/uploads/sites/443/2022/06/AAMAS-2023-Formatting-Instructions.zip

Papers selected for presentation at the workshop will be included in the
workshop’s proceedings as open access publications, tentatively in CEUR (
https://ceur-ws.org/) or EPTCS (https://www.eptcs.org/).

Please use the following link to submit your paper:
https://easychair.org/conferences/?conf=nesymas2023

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Important dates
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All deadlines are 23:59 AoE.

- Paper submission deadline: 30 January 2023
- Paper acceptance notification: 13 March 2023
- Call for participation and program published: 3 April 2023
- Workshop:   29 or 30 May, 2023

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Organising Committee
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Vaishak Belle, University of Edinburgh, UK
Michael Fisher, University of Manchester, UK
Xiaowei Huang, University of Liverpool, UK
Masoumeh Mansouri, University of Birmingham, UK
Albert Meroño-Peñuela, King’s College London, UK
Sriraam Natarajan, UT Dallas, USA
Efi Tsamoura, Samsung Cambridge, UK

This workshop is organised by the Interest Group in Neuro-Symbolic AI of
The Alan Turing Institute. You can find more information about us and how
to join the IG on our website (
https://www.turing.ac.uk/research/interest-groups/neuro-symbolic-ai).

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Programme Committee [TBC]
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Devendra Singh Dhami (Hessian Center for AI (hessian.AI) and TU DarmstadtI)
Aaron Eberhart (Kansas State University)
Christina Winkler (TU München)
Thomas Kipf (Google Brain)
Robert Peharz (TU Graz)
Kristian Kersting (Hessian Center for AI (hessian.AI), DFKI and TU
DarmstadtI)
Francesca Rossi (IBM Research)
Guy Van den Broeck (UCLA)
Zachary Lipton (CMU)
Ian Horrocks (University of Oxford)
Artur d'Avila Garcez (City, University of London)
Pascal Hitzler (Kansas State University)
Monireh Ebrahimi (lBM Watson San Francisco)
Petar Veličković (DeepMind, University of Cambridge)
Riccardo Tommasini (University of Lyon)
Varun Kanade (University of Oxford)
Bei Peng (University of Liverpool)
Louise Dennis (University of Manchester)