[month] [year]

PRICAI-2022

November 2022

Shaily Mishra and Manisha Padala working under the supervision of Dr. Sujit Gujar presented a paper on EEF1-NN: Efficient and EF1 allocations through Neural Networks at the proceedings of the 19th Pacific Rim International Conference on Artificial Intelligence. (PRICAI-22)   held in a hybrid mode in Shanghai, China from 10 to 13 November.

Research work as explained by the authors:

Neural networks have shown state-of-the-art performance in designing auctions, where the network learns the optimal allocations and payment rule to ensure desirable properties. Motivated by the same, we focus on learning fair division of resources, with no payments involved. Our goal is to allocate the items, goods and/or chores efficiently among the fair allocations. By fair, we mean an allocation that is Envy-free (EF). However, such an allocation may not always exist for indivisible resources. Therefore, we consider the relaxed notion, Envy-freeness up to one item (EF1) that is guaranteed to exist. However, it is not enough to guarantee EF1 since the allocation of empty bundles is also EF1. Hence, we add the further constraint of efficiency, maximum utilitarian social welfare (USW). In general finding, USW allocations among EF1 is an NP-Hard problem even when valuations are additive. In this work, we design a network for this task which we refer to as EEF1-NN. We propose an UNet inspired architecture, Lagrangian loss function, and training procedure to obtain desired results. We show that EEF1-NN finds allocation close to optimal USW allocation and ensures EF1 with a high probability for different distributions over input valuations. Compared to existing approaches EEF1-NN empirically guarantees higher USW. Moreover, EEF1-NN is scalable and determines the allocations much faster than solving it as a constrained optimization problem.

The Pacific Rim International Conference on Artificial Intelligence (PRICAI) is a biennial international event which concentrates on AI theories, technologies and their applications in the areas of social and economic importance for countries in the Pacific Rim. In the past, the conferences have been held in Nagoya (1990), Seoul (1992), Beijing (1994), Cairns (1996), Singapore (1998), Melbourne (2000), Tokyo (2002), Auckland (2004), Guilin (2006), Hanoi (2008), Daegu (2010), Kuching (2012), Gold Coast (2014), Phuket (2016), Nanjing (2018), Fiji (2019), Yokohama (2020, online) and Hanoi (2021, online). PRICAI-2022 aims to bring together researchers, practitioners, educators and users in AI and related communities for in-depth intellectual exchanges, research cooperation and professional development.

Conference page: https://pricai.org/2022/