School of Computer Science

Agents Lab Celebrates Double AAAI 2019 Success

Agents Lab celebrates double AAAI 2019 Success

With a two fold increase in applications and a paper acceptance rate of 16.2% it is an honour to announce that the Agents Lab has had not one, but two papers accepted into the thirty-third AAAI conference on Artificial Intelligence (AAAI-19) being held in Honolulu, Hawaii.

The first paper is titled Unbound Orchestrations of Transducers for Manufacturing written by Natasha Alechina, Tomas Brazdil, Giuseppe De Giacomo, Paolo Felli, Brian Logan and Moshe Vardi.
There has recently been increasing interest in using reactive synthesis techniques to automate the production of manufacturing process plans. Previous work has assumed that the set of manufacturing resources is known and fixed in advance. In this paper, we consider the more general problem of whether a controller can be synthesised given sufficient resources. In the unbounded setting, only the types of available manufacturing resources are given, and we want to know whether it is possible to manufacture a product using only resources of those type(s), and, if so, how many resources of each type are needed. We model manufacturing processes and facilities as transducers (automata with output), and show that the unbounded orchestration problem is decidable and the (Pareto) optimal set of resources necessary to manufacture a produce is computable for uni-transducers. However, for multi-transducers, the problem is undecidable.

The second paper is titled Qualitative Spatial Logic over 2D Euclidean Spaces is Not Finitely Axiomatisable and was written by Heshan Du, from The University Of Nottingham Ningbo China, and Natasha Alechina from our school here in Nottingham.

Several qualitative spatial logics were introduced in (Du et al. 2013; Du and Alechina 2016) to aid in debugging matches between different geospatial datasets (Du et al. 2015). They are sound and complete for metric spaces.
However, 2D Euclidean spaces are a much more appropriate semantics for geospatial data, as geospatial data is usually represented using geometries or coordinates and visualized as a map. The question was open whether a more precise debugging tool could be developed using the same approach but using reasoning about 2D Euclidean spaces. In other words, is the axiomatisation presented in (Du et al. 2013; Du and Alechina 2016) still complete with respect to 2D Euclidean spaces, and if not, what are the missing axioms? We use recent results from graph theory (Atminas and Zamaraev 2018) to answer this question negatively by showing that the axiomatisations presented in (Du et al. 2013; Du and Alechina 2016) are not complete for 2D Euclidean spaces and, moreover, the logics are not finitely axiomatisable.

The papers will be made available online in the next few months, if you would like to find out more please keep checking

Posted on Monday 5th November 2018

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