Dynamic Coalition Formation Under Uncertainty

Coalition formation algorithms are generally not applicable to real-world robotic collectives since they lack mechanisms to handle uncertainty. Those mechanisms that do address uncertainty either deflect it by soliciting information from others or apply reinforcement learning to select an agent type from within a set. This paper presents a coalition formation mechanism that directly addresses uncertainty while allowing the agent types to fall outside of a known set. The agent types are captured through a novel agent modeling technique that handles uncertainty through a belief-based evaluation mechanism. This technique allows for uncertainty in environmental data, agent type, coalition value, and agent cost. An investigation of both the effects of adding agents on processing time and of model quality on the convergence rate of initial agent models (and thereby coalition quality) is provided. This approach handles uncertainty on a larger scale than previous work and provides a mechanism readily applied to a dynamic collective of real-world robots. Abstract © IEEE

Determining Solution Space Characteristics for Real-Time Strategy Games and Characterizing Winning Strategies

The underlying goal of a competing agent in a discrete real-time strategy (RTS) game is to defeat an adversary. Strategic agents or participants must define an a priori plan to maneuver their resources in order to destroy the adversary and the adversary\u27s resources as well as secure physical regions of the environment. This a priori plan can be generated by leveraging collected historical knowledge about the environment. This knowledge is then employed in the generation of a classification model for real-time decision-making in the RTS domain. The best way to generate a classification model for a complex problem domain depends on the characteristics of the solution space. An experimental method to determine solution space (search landscape) characteristics is through analysis of historical algorithm performance for solving the specific problem. We select a deterministic search technique and a stochastic search method for a priori classification model generation. These approaches are designed, implemented, and tested for a specific complex RTS game, Bos Wars. Their performance allows us to draw various conclusions about applying a competing agent in complex search landscapes associated with RTS games

Differential Diagnosis and Clinical Management of a Case of COVID-19 in a Patient With Stage III Lung Cancer Treated With Radio-chemotherapy and Durvalumab

none14nononeGuerini A.E.; Borghetti P.; Filippi A.R.; Bonu M.L.; Tomasini D.; Greco D.; Imbrescia J.; Volpi G.; Triggiani L.; Borghesi A.; Maroldi R.; Pasinetti N.; Buglione M.; Magrini S.M.Guerini, A. E.; Borghetti, P.; Filippi, A. R.; Bonu, M. L.; Tomasini, D.; Greco, D.; Imbrescia, J.; Volpi, G.; Triggiani, L.; Borghesi, A.; Maroldi, R.; Pasinetti, N.; Buglione, M.; Magrini, S. M

Risk-shifting Through Issuer Liability and Corporate Monitoring

This article explores how issuer liability re-allocates fraud risk and how risk allocation may reduce the incidence of fraud. In the US, the apparent absence of individual liability of officeholders and insufficient monitoring by insurers under-mine the potential deterrent effect of securities litigation. The underlying reasons why both mechanisms remain ineffective are collective action problems under the prevailing dispersed ownership structure, which eliminates the incentives to moni-tor set by issuer liability. This article suggests that issuer liability could potentially have a stronger deterrent effect when it shifts risk to individuals or entities holding a larger financial stake. Thus, it would enlist large shareholders in monitoring in much of Europe. The same risk-shifting effect also has implications for the debate about the relationship between securities litigation and creditor interests. Credi-tors’ claims should not be given precedence over claims of defrauded investors (e.g., because of the capital maintenance principle), since bearing some of the fraud risk will more strongly incentivise large creditors, such as banks, to monitor the firm in jurisdictions where corporate debt is relatively concentrated

Computers from plants we never made. Speculations

We discuss possible designs and prototypes of computing systems that could be based on morphological development of roots, interaction of roots, and analog electrical computation with plants, and plant-derived electronic components. In morphological plant processors data are represented by initial configuration of roots and configurations of sources of attractants and repellents; results of computation are represented by topology of the roots' network. Computation is implemented by the roots following gradients of attractants and repellents, as well as interacting with each other. Problems solvable by plant roots, in principle, include shortest-path, minimum spanning tree, Voronoi diagram, $\alpha$-shapes, convex subdivision of concave polygons. Electrical properties of plants can be modified by loading the plants with functional nanoparticles or coating parts of plants of conductive polymers. Thus, we are in position to make living variable resistors, capacitors, operational amplifiers, multipliers, potentiometers and fixed-function generators. The electrically modified plants can implement summation, integration with respect to time, inversion, multiplication, exponentiation, logarithm, division. Mathematical and engineering problems to be solved can be represented in plant root networks of resistive or reaction elements. Developments in plant-based computing architectures will trigger emergence of a unique community of biologists, electronic engineering and computer scientists working together to produce living electronic devices which future green computers will be made of.Comment: The chapter will be published in "Inspired by Nature. Computing inspired by physics, chemistry and biology. Essays presented to Julian Miller on the occasion of his 60th birthday", Editors: Susan Stepney and Andrew Adamatzky (Springer, 2017

Hormone replacement therapy enhances IGF-1 signaling in skeletal muscle by diminishing miR-182 and miR-223 expressions: a study on postmenopausal monozygotic twin pairs

MiRNAs are fine-tuning modifiers of skeletal muscle regulation, but knowledge of their hormonal control is lacking. We used a co-twin case-control study design, that is, monozygotic postmenopausal twin pairs discordant for estrogen-based hormone replacement therapy (HRT) to explore estrogen-dependent skeletal muscle regulation via miRNAs. MiRNA profiles were determined from vastus lateralis muscle of nine healthy 54-62-years-old monozygotic female twin pairs discordant for HRT (median 7 years). MCF-7 cells, human myoblast cultures and mouse muscle experiments were used to confirm estrogen's causal role on the expression of specific miRNAs, their target mRNAs and proteins and finally the activation of related signaling pathway. Of the 230 miRNAs expressed at detectable levels in muscle samples, qPCR confirmed significantly lower miR-182, miR-223 and miR-142-3p expressions in HRT using than in their nonusing co-twins. Insulin/IGF-1 signaling emerged one common pathway targeted by these miRNAs. IGF-1R and FOXO3A mRNA and protein were more abundantly expressed in muscle samples of HRT users than nonusers. In vitro assays confirmed effective targeting of miR-182 and miR-223 on IGF-1R and FOXO3A mRNA as well as a dose-dependent miR-182 and miR-223 down-regulations concomitantly with up-regulation of FOXO3A and IGF-1R expression. Novel finding is the postmenopausal HRT-reduced miRs-182, miR-223 and miR-142-3p expression in female skeletal muscle. The observed miRNA-mediated enhancement of the target genes' IGF-1R and FOXO3A expression as well as the activation of insulin/IGF-1 pathway signaling via phosphorylation of AKT and mTOR is an important mechanism for positive estrogen impact on skeletal muscle of postmenopausal women