Creating and Capturing Artificial Emotions in Autonomous Robots and Software Agents

This paper presents ARTEMIS, a control system for autonomous robots or software agents. ARTEMIS is able to create and capture artificial emotions during interactions with its environment, and we describe the underlying mechanisms for this. The control system also realizes the capturing of knowledge about its past artificial emotions. A specific interpretation of a knowledge graph, called an Agent Knowledge Graph, represents these artificial emotions. For this, we devise a formalism which enriches the traditional factual knowledge in knowledge graphs with the representation of artificial emotions. As proof of concept, we realize a concrete software agent based on the ARTEMIS control system. This software agent acts as a user assistant and executes the user’s orders. The environment of this user assistant consists of autonomous service agents. The execution of user’s orders requires interaction with these autonomous service agents. These interactions lead to artificial emotions within the assistant. The first experiments show that it is possible to realize an autonomous agent with plausible artificial emotions with ARTEMIS and to record these artificial emotions in its Agent Knowledge Graph. In this way, autonomous agents based on ARTEMIS can capture essential knowledge that supports successful planning and decision making in complex dynamic environments and surpass emotionless agents

The IDIP framework for assessing protein function and its application to the prion protein

The quest to determine the function of a protein can represent a profound challenge. Although this task is the mandate of countless research groups, a general framework for how it can be approached is conspicuously lacking. Moreover, even expectations for when the function of a protein can be considered to be ‘known’ are not well defined. In this review, we begin by introducing concepts pertinent to the challenge of protein function assignments. We then propose a framework for inferring a protein's function from four data categories: ‘inheritance’, ‘distribution’, ‘interactions’ and ‘phenotypes’ (IDIP). We document that the functions of proteins emerge at the intersection of inferences drawn from these data categories and emphasise the benefit of considering them in an evolutionary context. We then apply this approach to the cellular prion protein (PrP^{C}), well known for its central role in prion diseases, whose function continues to be considered elusive by many investigators. We document that available data converge on the conclusion that the function of the prion protein is to control a critical post-translational modification of the neural cell adhesion molecule in the context of epithelial-to-mesenchymal transition and related plasticity programmes. Finally, we argue that this proposed function of PrP^{C} has already passed the test of time and is concordant with the IDIP framework in a way that other functions considered for this protein fail to achieve. We anticipate that the IDIP framework and the concepts analysed herein will aid the investigation of other proteins whose primary functional assignments have thus far been intractable

On a Bounded Budget Network Creation Game

We consider a network creation game in which each player (vertex) has a fixed budget to establish links to other players. In our model, each link has unit price and each agent tries to minimize its cost, which is either its local diameter or its total distance to other players in the (undirected) underlying graph of the created network. Two versions of the game are studied: in the MAX version, the cost incurred to a vertex is the maximum distance between the vertex and other vertices, and in the SUM version, the cost incurred to a vertex is the sum of distances between the vertex and other vertices. We prove that in both versions pure Nash equilibria exist, but the problem of finding the best response of a vertex is NP-hard. We take the social cost of the created network to be its diameter, and next we study the maximum possible diameter of an equilibrium graph with n vertices in various cases. When the sum of players' budgets is n-1, the equilibrium graphs are always trees, and we prove that their maximum diameter is Theta(n) and Theta(log n) in MAX and SUM versions, respectively. When each vertex has unit budget (i.e. can establish link to just one vertex), the diameter of any equilibrium graph in either version is Theta(1). We give examples of equilibrium graphs in the MAX version, such that all vertices have positive budgets and yet the diameter is Omega(sqrt(log n)). This interesting (and perhaps counter-intuitive) result shows that increasing the budgets may increase the diameter of equilibrium graphs and hence deteriorate the network structure. Then we prove that every equilibrium graph in the SUM version has diameter 2^O(sqrt(log n)). Finally, we show that if the budget of each player is at least k, then every equilibrium graph in the SUM version is k-connected or has diameter smaller than 4.Comment: 28 pages, 3 figures, preliminary version appeared in SPAA'1

Single crystals of metal solid solutions

The following definitions were sought in the research on single crystals of metal solid solutions: (1) the influence of convection and/or gravity present during crystallization on the substructure of a metal solid solution; (2) the influence of a magnetic field applied during crystallization on the substructure of a metal solid solution; and (3) requirements for a space flight experiment to verify the results. Growth conditions for the selected silver-zinc alloy system are described, along with pertinent technical and experimental details of the project

Application of numerical methods to simulate the unsteady flow of lean liquor solution through a porous medium made up of porous ore particles

Unsaturated flow of liquid in a bed of uniform and spherical ore particles is studied numerically and experimentally. An unsteady and two-dimensional model is developed based on the mass conservation equations of the liquid phase in the bed and in the particles. The model equations are solved using a fully implicit finite difference method giving the distribution of the degree of saturation in the particles and in the bed and the vertical velocity of flow in the bed, as well as, the effect of periodic infiltration on the above distributions. To calibrate the computational model, several column tests are performed using periodic infiltration of water on 40 cm high columns composed of ore having particles smaller than 25 mm. The numerical analysis shows that (a) the results obtained from numerical modelling under the same operating conditions as used for column tests, are in good agreement with those from the experimental procedure, (b) the degree of saturation of the bed and the time required to reach steady state conditions depend on the inflow of water and intrinsic permeability of the bed and (c) the velocity fluctuations and the fluctuations of the degree of saturation in the bed depend on the inflow of water, period of infiltration, height, and intrinsic permeability of the bed

Reconfigurable cooperative control of networked lagrangian systems under actuator saturation constraints

In this paper, a reconfigurable control strategy is proposed for state synchronization and tracking control of networked (electro-) mechanical Euler-Lagrange (EL) systems that are subject to input saturation constraints that may arise due to actuator faults or failures. The reconfigurable controller consists of three main parts. The first part, known as the nominal controller, is a distributed controller that is employed to guarantee global stability of the multiagent networked EL system provided that certain mild connectivity conditions are satisfied in absence or presence of actuator saturation constraints. The second part, known as the reconfigured controller, is a constrained nonlinear smooth distributed controller that has a different structure and gains from the nominal controller. This controller can preserve the overall control objectives in presence of actuator faults and actuator saturation constraints. The third part is a switching strategy between the nominal and the reconfigured controllers. Global stability as well as asymptotic convergence of the synchronization and the tracking errors to origin for switchings under certain conditions between the nominal and the reconfigured controllers with non-vanishing dwell-times for a fixed network topology are shown to be guaranteed. Simulation results are reported to demonstrate and validate the merits of the proposed controllers

Mapping the genetic architecture of gene expression in human liver

Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process. © 2008 Schadt et al

The role of social networks in students’ learning experiences

The aim of this research is to investigate the role of social networks in computer science education. The Internet shows great potential for enhancing collaboration between people and the role of social software has become increasingly relevant in recent years. This research focuses on analyzing the role that social networks play in students’ learning experiences. The construction of students’ social networks, the evolution of these networks, and their effects on the students’ learning experience in a university environment are examined