Disentangling Parallelism and Interference in Game Semantics

Game semantics is a denotational semantics presenting compositionally the behaviour of various kinds of effectful programs . We provide compositional conditions parallel innocenceand sequentiality, respectively banning interference and parallelism, and leading to four full abstraction results . To our knowledge, this is the firstextension of Abramsky’s semantic cube programme beyond the sequentialdeterministic world.…

Deriving Laws for Developing Concurrent Programs in a Rely Guarantee Style

In this paper we present a theory for the refinement of shared-memoryconcurrent algorithms from specifications . Our approach avoids restrictiveatomicity contraints . It provides a range of constructs for specifying concurrent programs and laws for refining these to code . All the above constructs are defined in terms of a simple corelanguage, based on four primitive commands and a handful of operators .…

Competing Adaptive Networks

Adaptive networks have the capability to pursue solutions of global optimization problems by relying only on local interactions within the network . The diffusion of information through repeated interactions allows for globally optimal behavior, without the need for centralcoordination . Most existing strategies are developed for cooperative learningsettings, where the objective of the network is common to all agents .…

FisherMob a bioeconomic model of fishers migrations

FisherMob” is a free Gama tool designed to study the effect of economic andbiological factors on the dynamics of connected fisheries . It incorporates themost important processes involved in fisheries dynamics: fish abundancevariability, price of the fishing effort and ex-vessel fish market price .…

Demonstrating Analog Inference on the BrainScaleS 2 Mobile System

The BrainScaleS-2 mobile system is a compact analog inferenceengine based on the BrainScale S-2 ASIC . We measure a total energy consumption of192uJ for the ASIC and achieve a classification time of 276us perelectrocardiographic patient sample . Patients with atrial fibrillation are correctly identified with a detection rate of 93.7(7)% at 14.0(10)% false positives .…

Self Constructing Neural Networks Through Random Mutation

The search for neural architecture is producing many of the most exciting results in artificial intelligence . This paper presents a simple method for learning neural architecture through random mutation . Starting without any neurons or connections, this method constructsa neural architecture capable of high-performance on several tasks .…

Artificial Neural Network classification of asteroids in the M1 2 mean motion resonance with Mars

Artificial neural networks (ANN) have been successfully used in the last years to identify patterns in astronomical images . The use of ANN in the field of asteroid dynamics has been, however, so far somewhat limited . In this work we used for the first time ANN for the purpose of automatically identifying thebehaviour of asteroid orbits affected by the M1:2 mean-motion resonance withMars .…

Joint User Association and Power Allocation in Heterogeneous Ultra Dense Network via Semi Supervised Representation Learning

Heterogeneous Ultra-Dense Network (HUDN) is one of the vital networkingarchitectures due to its ability to enable higher connectivity density andultra-high data rates . This paper proposes a novel idea for solving the joint user association and power control problem: the optimaluser association and Base Station transmit power can be represented by channel information .…

A simpler encoding of indexed types

In functional programming languages, pattern matching over indexed types is very useful as it can be ruled out by the failure of unification of type arguments . In dependent type systems, this is usually called indexed types . We study a simplified version of indexed types (called simpler indexed types) where we specify the selection process of constructors, and we discuss itsexpressiveness, limitations, and properties .…

Reddit s Self Organized Bull Runs

The influence between users on theWallStreetBets (WSB) subreddit is measured by tracing the probability of a userstarting a fresh discussion on an asset given their previous involvement in adiscussion on the same asset, measured by their comment history . This paper finds that users who comment on one discussion involving a particular asset are approximately four times more likely to start a new discussion about this asset .…

A Systematic Survey on Multi relational Community Detection

Complex networks contain various interactions among similar or differententities . These kinds of networks are called multi-relational networks, inwhich each layer corresponds to a special type of interaction . In this survey, we study communitydetection methods for multilayer networks . The considered models aredivided into two main groups, namely, direct methods and indirect methods .…

A stochastic model for the influence of social distancing on loneliness

The short-term economic consequences of the measures employed to curb the transmission of Covid-19 are all too familiar, but the consequences of isolation and loneliness resulting from those measures on the mental well-being of the population are largely unknown . Here we offer a stochastic agent-based model to investigate socialrestriction measures in a community where the feelings of loneliness of the agents dwindle when they are socializing and grow when they’re alone .…

An Efficient Algorithm for Deep Stochastic Contextual Bandits

In stochastic contextual bandit (SCB) problems, an agent selects an action based on certain observed context to maximize the cumulative reward overiterations . Recently there have been studies using a deep neural network(DNN) to predict the expected reward for an action, and the DNN is trained by astochastic gradient based method .…

Compositional Abstraction Error and a Category of Causal Models

Interventional causal models describe joint distributions over some variables used to describe a system . They provide a recipe for how to move between joint distributions and make predictions about the variables upon intervening on the system . Here, we argue thatcompositionality is a desideratum for model transformations and the associatederrors .…

Federated Learning in Robotic and Autonomous Systems

Autonomous systems are becoming inherently ubiquitous with the advancementsof computing and communication solutions enabling low-latency offloading andreal-time collaboration of distributed devices . Federated learning (FL) is a promising solution toprivacy-preserving DL at the edge, with an inherently distributed nature bylearning on isolated data islands and communicating only model updates .…

Coordinated Motion Planning Through Randomized k Opt

This paper examines the approach taken by team gitastrophe in the CG:SHOP2021 challenge . The challenge was to find a sequence of simultaneous moves ofsquare robots between two given configurations that minimized either totaldistance travelled or makespan (total time) Our winning approach has two main components: an initialization phase that finds a good initial solution, and a$k$-opt local search phase which optimizes this solution .…

Should College Dropout Prediction Models Include Protected Attributes

Early identification of college dropouts can provide tremendous value for improving student success and institutional effectiveness . However, ethical concern has emerged about whether including protected attributes discriminates against underrepresented student groups and exacerbates existing inequities . We examine this issue in the context of a large U.S.research…

Acceptance of COVID 19 Vaccine and Its Determinants in Bangladesh

Bangladesh govt. launched a nationwide vaccination drive against SARS-CoV-2 infection from early February 2021 . 61.16% (370/605) of the respondents were willing to accept/take the COVID-19 vaccine . Only 35.14% showed the willingnessto take the vaccine immediately, while 64.86% would delay thevaccination until they are confirmed about the vaccine’s efficacy and safety or COVID19 become deadlier in Bangladesh .…

Mathematics of Digital Hyperspace

Digital hyperspace is an amorphousflow of data supported by continuous streams that stretch standard concepts of type and dimension . The unstructured data of digital hyperspace can be represented, traversed, and transformed via the mathematics ofhypergraphs, hypersparse matrices, and associative array algebra .…

Euler Meets GPU Practical Graph Algorithms with Theoretical Guarantees

The Euler tour technique is a classical tool for designing parallel graphalgorithms, originally proposed for the PRAM model . We ask whether it can be adapteded to run efficiently on the GPU . We show that the Euler-based algorithms not only fulfill their theoretical promises and outperform practicalheuristics on hard instances, but also perform on par with them on easyinstances.…