Deep Learning Meets Mechanism Design: Key Results and Some Novel Applications

Mechanism design is essentially reverse engineering of games and involves inducing a game among strategic agents in a way that the induced game satisfies a set of desired properties in an equilibrium of the game. Desirable properties for a mechanism include incentive compatibility, individual rationality, welfare maximisation, revenue maximisation (or cost minimisation), fairness of allocation, etc. It is known from mechanism design theory that only certain strict subsets of these properties can be simultaneously satisfied exactly by any given mechanism. Often, the mechanisms required by real-world applications may need a subset of these properties that are theoretically impossible to be simultaneously satisfied. In such cases, a prominent recent approach is to use a deep learning based approach to learn a mechanism that approximately satisfies the required properties by minimizing a suitably defined loss function. In this paper, we present, from relevant literature, technical details of using a deep learning approach for mechanism design and provide an overview of key results in this topic. We demonstrate the power of this approach for three illustrative case studies: (a) efficient energy management in a vehicular network (b) resource allocation in a mobile network (c) designing a volume discount procurement auction for agricultural inputs. Section 6 concludes the paper

Antibacterial Activity of Nigella sativa L. Seed Extracts

Abstract: Most of the bacterial pathogens are resistant to existing synthetic antibacterial agents demanding an increasing effort to seek effective phytochemicals as antibacterial agents against such pathogens. Nigella sativa L. (black cumin) seeds play an important role in folk medicine and some of its major constituents are reported to be pharmacologically active. In this present work, black cumin seed extracts were obtained using supercritical carbon dioxide (SCCO 2 ) and conventional soxtec extraction using various organic solvents. The antibacterial activities of the extracts were investigated by the agar dilution method against Gram-positive bacteria (Bacillus cereus F 4810 and Staphylococcus aureus FRI 722) and Gram-negative bacteria (Escherichia coli MTCC 108 and Yersinia enterocolitica MTCC 859). SCCO 2 -1 (120 bar/40ºC) extract showed effective growth inhibition than conventional solvent extracts against all the tested bacteria. Further the antibacterial principle present in the extract was isolated and characterized found to be thymoquinone

Subchannel allocation and power control in femtocells to provide quality of service

Femtocells are a new concept which improves the coverage and capacity of a cellular system. We consider the problem of channel allocation and power control to different users within a Femtocell. Knowing the channels available, the channel states and the rate requirements of different users the Femtocell base station (FBS), allocates the channels to different users to satisfy their requirements. Also, the Femtocell should use minimal power so as to cause least interference to its neighboring Femtocells and outside users. We develop efficient, low complexity algorithms which can be used online by the Femtocell. The users may want to transmit data or voice. We compare our algorithms with the optimal solutions

QoS provisioning for multiple Femtocells via game theory

We consider a system with multiple Femtocells (FCs) operating in a Macrocell. The transmissions in one Femtocell interfere with its neighboring Femtocells. Each Femtocell has multiple users, each requiring a minimum transmission rate. There is also peak transmit power constraint in each channel to control interference to the BS and the users in the Macrocell. We formulate the problem of channel allocation and power control in each Femtocell as a noncooperative Game. We develop efficient decentralized algorithms to obtain a Nash equilibrium (NE) that satisfies the Quality of Service (QoS) of each user, in an efficient way. We also obtain efficient decentralized algorithms to obtain fair NE when it may not be feasible to satisfy the QoS of all the users in FCs. Finally, we extend our algorithms to the case where there may be voice and data users in the system. (C) 2016 Elsevier B.V. All rights reserved