Modelling Behaviour Change using Cognitive Agent Simulations

Behaviour Change Theories (BCTs) play an important role in modelling human goal achievement in adverse environments . Some of the BCTs use concepts that are also used in computational modelling of cognition and affect in AI . Such simulations are useful because they can providenew insights into human behaviour change and improve conceptual precision .…

Physics guided Deep Markov Models for Learning Nonlinear Dynamical Systems with Uncertainty

In this paper, we propose a probabilistic physics-guided framework, termedPhysics-guided Deep Markov Model . The framework is especially targetedto the inference of the characteristics and latent structure of nonlineardynamical systems from measurement data . The proposed framework takes advantage of the expressive power of deep learning, while retaining the driving physics of the dynamical system by imposing physics-driven restrictions on the side of the latent space .…

Physical Side Channel Attacks on Embedded Neural Networks A Survey

Deep Neural Networks (DNN) have progressively beenintegrated on all types of platforms, from data centers to embedded systems including low-power processors and, recently, FPGAs . The underlying hardware securityvulnerabilities of embedded NN implementations remain unaddressed . Inparticular, embedded DNN implementations are vulnerable to Side-ChannelAnalysis (SCA) attacks, which are especially important in the IoT and edgecomputing contexts where an attacker can usually gain physical access to thetargeted device .…

Uplink Power Control in Integrated Access and Backhaul Networks

Integrated access and backhaul (IAB) network is a novel radio access network(RAN) solution, enabling network densification for 5G and beyond . We use power control combined with resource allocation algorithms todevelop efficient IAB networks with high service coverage . We also study the effect of different parameters including minimum data raterequirement, coverage distance and transmit power on the network performance .…

Anomaly Detection in Multi Agent Trajectories for Automated Driving

The spatio-temporal graphauto-encoder for learning normal driving behaviours . The code, simulation and thedataset are publicly available on the project page:https://://://github.com/againerju/maad_highway. We introduce our dataset using adriving simulator for normal and abnormal manoeuvres. Our evaluations show thatour approach learns the relation between different agents and delivers promising results compared to the related works.…

Design Technology Co Optimization for Neuromorphic Computing

We present a design-technology tradeoff analysis in implementing machine-learning inference on the processing cores of a Non-Volatile Memory(NVM)-based many-core neuromorphic hardware . We show that such designand technology characteristics can be incorporated in a design flow to significantly improve the inference lifetime of a coredependends on the resistance state of a core(design) and the voltage variation inside the core that is introduced by the current paths (technology) We show the negative impact ofdesign scaling on read endurance of NVMs, which directly impacts theirinference lifetime .…

Shaping Large Population Agent Behaviors Through Entropy Regularized Mean Field Games

Mean-field games (MFG) were introduced to efficiently analyze approximateNash equilibria in large population settings . We show that entropy regularization provides thenecessary regularity conditions, that are lacking in the standard finite meanfield games . We establish conditions for the existence of a Nashequilibrium in the limiting case as $N$ tends to infinity, and we demonstratethat the Nash equilibrium for the infinite population case is also an$epsilon$-Nash equilibrium .…

Accelerating Genetic Programming using GPUs

Genetic Programming (GP), an evolutionary learning technique, has multiple applications in machine learning such as curve fitting, data modelling, featureselection, classification etc. GP has several inherent parallel steps, making it an ideal candidate for GPU based parallelization . We evaluate our algorithm on synthetic datasets for the PagiePolynomial (ranging in size from $4096$ to $16$ million points) We run performance benchmarks on our algorithmand gplearn, profiling the training time, test accuracy, and loss .…

First Order Modal ξ Calculus

This paper proposes first-order modal $\xi$-calculus as well as genealogicalKripke models . Inspired by modal $\mu$-Calculus, it takes a similar form and extends its inductiveexpressivity onto a different dimension . We elaborate on several vivid examplesthat demonstrate this logic’s profound utility .…

BPPChecker An SMT based Model Checker on Basic Parallel Processes

Basic Parallel Process (BPP), as a subclass of Petri nets, can be used as a model for describing and verifying concurrent programs with lowercomplexity . We propose and implement BPPChecker, the first model checker forverifying CTL on BPP . For EF operator, we reduce the model checking of EF-formulas to the satisfiabilityproblem of existential Presburger formula .…

Multi layer Space Information Networks Access Design and Softwarization

In this paper, we propose an approach for constructing a multi-layermulti-orbit space information network (SIN) to provide high-speed continuousbroadband connectivity for space missions . Space-based Internet providers, such as Starlink,OneWeb, and SES O3b, can be utilized for broadband connectivity directly to/from the nanosatellites, which allows a larger degree of connectivity inspace network topologies .…

New techniques for bounding stabilizer rank

In this work, we present number-theoretic and algebraic-geometric techniques for bounding the stabilizer rank of quantum states . First, we find the first non-trivial examples of quantumstates with multiplicative stabilizer ranks under the tensor product . We also find new bounds on the genericstabilizer rank.…

The Neural MMO Platform for Massively Multiagent Research

Neural MMO is a computationally accessible research platform that combines large agent populations, long time horizons, open-ended tasks, and modular gamesystems . We present Neural MMO as free and opensource software with active support, ongoing development, documentation, and training, logging, and visualization tools to help users adapt to the new setting .…

The Pebble Relation Comonad in Finite Model Theory

The pebbling comonad, introduced by Abramsky, Dawar and Wang, provides acategorical interpretation for k-pebble games from finite model theory . The coKleisli category of the pebble-relation comonads specifies equivalences under different fragments and extensions of infinitary k-variable logic . We prove a new Lov\’asz-type theorem relating pathwidth to therestricted conjunction fragment of k- variable logic with counting quantifiers .…

A Broad Spectrum Diffractive Network via Ensemble Learning

A broad-spectrum diffractive deep neural network (BS-D2NN) incorporates multi-wavelength channels of input lightfields and performs a parallel phase-only modulation . A complementary multi-channel base learner cluster is formed in ahomogeneous ensemble framework based on the diffractive dispersion duringlightwave modulation . The BS-D1NN can be trained usingdeep learning algorithms so as to perform a kind of wavelength-insensitivehigh-accuracy object classification .…

Dynamics of Cross Platform Attention to Retracted Papers Pervasiveness Audience Skepticism and Timing of Retractions

Retracted papers often circulate widely on social media, online news outlets and other websites before their official retraction . The spread of potentiallyinaccurate or misleading results from retracted papers can harm the scientific community and the public . This finding indicates that untrustworthyresearch penetrates even curated platforms and is often shared uncritically,plplifying the negative impact on the public, say the authors .…

Simulation of emergence in artificial societies a practical model based approach with the EB DEVS formalism

EB-DEVS is a novel formalism tailored for the modelling, simulation and liveidentification of emergent properties . This work provides case study-driven evidence for theneatness and compactness of the approach to modelling communication structuresthat can be explicit or implicit, static or dynamic, with or without multilevelinteractions, and with weak or strong emergent behaviour .…

StreaMulT Streaming Multimodal Transformer for Heterogeneous and Arbitrary Long Sequential Data

This paper tackles the problem of processing and combining efficientlyarbitrary long data streams . Common applications can be, for instance, long-timeindustrial or real-life systems monitoring from multimodal heterogeneous data . To tackle this problem, we propose StreaMulT, a Streaming Multimodal Transformer, relying on cross-modalattention and an augmented memory bank to process arbitrary long inputsequences at training time and run in a streaming way at inference .…

Design Technology Co Optimization for Neuromorphic Computing

We present a design-technology tradeoff analysis in implementing machine-learning inference on the processing cores of a Non-Volatile Memory(NVM)-based many-core neuromorphic hardware . We show that such designand technology characteristics can be incorporated in a design flow to significantly improve the inference lifetime of a coredependends on the resistance state of a core(design) and the voltage variation inside the core that is introduced by the current paths (technology) We show the negative impact ofdesign scaling on read endurance of NVMs, which directly impacts theirinference lifetime .…

On Extending Amdahl s law to Learn Computer Performance

The problem of learning parallel computer performance is investigated in thecontext of multicore processors . Given a fixed workload, the effect of varyingsystem configuration on performance is sought . Conventionally, the performancespeedup due to a single resource enhancement is formulated using Amdahl’s law .…

BPPChecker An SMT based Model Checker on Basic Parallel Processes

Basic Parallel Process (BPP), as a subclass of Petri nets, can be used as a model for describing and verifying concurrent programs with lowercomplexity . We propose and implement BPPChecker, the first model checker forverifying CTL on BPP . For EF operator, we reduce the model checking of EF-formulas to the satisfiabilityproblem of existential Presburger formula .…

HTTPA HTTPS Attestable Protocol

Hypertext Transfer Protocol Secure (HTTPS) protocol has become integral part of the modern internet technology . It is currently the primary protocol for commercialized web applications . However, HTTPS cannot provide securityassurances on the request data in compute, so the computing environment remainsuncertain risks and vulnerabilities .…

The Power of Many A Physarum Swarm Steiner Tree Algorithm

We create a novel Physarum Steiner algorithm designed to solve the Euclidean Steiner tree problem . The algorithm is of particular interest due to its rectilinear properties, and ability to run on varying shapes and topological surfaces . It is also highly capable of solving theobstacle avoidance problem and is a strong alternative to the current leading algorithm .…

Zipping Strategies and Attribute Grammars

Zippers provide a simple, but generic tree-walk mechanism that is the building blocktechnique we use to express the purely-functional embedding of both techniques . The combined embedding is easier to maintain and extend since it is written in a concise and uniformsetting .…

Channel Eigenvalues and Effective Degrees of Freedom of Reconfigurable Intelligent Surfaces

reconfigurable intelligent surface (RIS) has gained tremendous interest in both the academia and industry in recent years . Only limited knowledge has been obtained about channel eigenvlauecharacteristics and degrees of freedom (DoF) of systems containing RISs . In this paper, we focus on a wireless communication system where both themitter and receiver are respectively equipped with an RIS .…

Spoken ObjectNet A Bias Controlled Spoken Caption Dataset

Modern audio-visual datasets contain biases that undermine the real-world performance of models trained on that data . We introduce Spoken ObjectNet to remove some of these biases . This dataset expands upon ObjectNet, which is a bias-controlled image dataset . We detail our datacollection pipeline, which features several methods to improve caption quality, including automated language model checks .…

Effects of Different Optimization Formulations in Evolutionary Reinforcement Learning on Diverse Behavior Generation

An evolutionary reinforcement learning framework whichexploits multi-objective optimization as a way to obtain policies that succeed at behavior-related tasks as well as completing the main goal . To better understand how one guides multiplepolicies toward distinct strategies and benefit from diversity, we need to examine further the influence of the reward signal modulation and otherevolutionary mechanisms on the obtained behaviors .…

Return migration of German affiliated researchers Analyzing departure and return by gender cohort and discipline using Scopus bibliometric data 1996 2020

The international migration of researchers is a highly prized dimension of scientific mobility and motivates considerable policy debate . In this study, we use Scopus bibliometric data on 8 million publications from 1.1 million researchers who have published at least once with an affiliation address from Germany in 1996-2020 .…