Flexible Decision Control in an Autonomous Trading Agent

An autonomous trading agent is a complex piece of software that must operate in a competitive economic environment and support a research agenda. We describe the structure of decision processes in the MinneTAC trading agent, focusing on the use of evaluators – configurable, composable modules for data analysis and prediction that are chained together at runtime to support agent decision-making. Through a set of examples, we show how this structure supports sales and procurement decisions, and how those decision processes can be modified in useful ways by changing evaluator configurations. To put this work in context, we also report on results of an informal survey of agent design approaches among the competitors in the Trading Agent Competition for Supply Chain Management (TAC SCM).autonomous trading agent;decision processes

Investigating the Effectiveness of Antiretroviral Therapy in sub-Saharan Africa

Antiretroviral therapy (ART) has revolutionised outcomes of HIV infection among people living with HIV (PLWH). But despite these great strides, ongoing concerns of drug-drug interactions, widespread use of herbal medication while using ART, safety in pregnancy and breastfeeding are challenges of HIV treatment in PLWH. Potent new ART are not widely used in most low and middle income countries (LMIC) due to insufficient safety data and fear of adverse events. This Thesis aimed at evaluating the pharmacokinetic (PK) safety of DTG in pregnant and breastfeeding women, drug drug interaction of DTG and Artemisinin Combination Therapy (ACT), and evaluate the factors that affect ART in PLWH such as use of herbal medication among PLWH. Therefore the thesis evaluated the following: Chapter 2 reviewed the clinical PK and pharmacogenetic, drug-drug interactions and safety of DTG in diverse populations from different studies, and concluded that DTG has a variable PK influenced by factors such as food, research conditions and population variability. Chapter 4 evaluated the PK of DTG in 3rd trimester of pregnancy and postpartum women and found no clinically significant difference in DTG PK between pregnancy and postpartum period in women. Safety and efficiency of HIV control was also evaluated and concluded that DTG efficiently control viral load within a short period of time even when women present late in pregnancy. xx Chapter 5 evaluated the drug-drug interaction of DTG and ACT, and concluded that DTG can be co-administered with ACT in treatment of malaria among PLWH on DTG. Chapter 6 evaluated the impact of pharmacogenetics and pregnancy on tenofovir and emtricitabine Pharmacokinetics. An estimated 1-2-fold increase in FTC blood concentration was observed in pregnant and postpartum women with ABCC2 12:g.154962860T>C T allele allele compared to women with CT and CC allele. Sample size was small and was recognise as a limitation. Therefore require verification with larger clinical studies and result should be interpreted with caution. Chapter 7 evaluated the widespread use of herbal medicines amongst PLWH and contamination of herbal medicines with ART in Nigeria as a recognised challenge of ART in sub-Saharan Africa. In conclusion, approximately 2-4% of maternal plasma DTG concentration was excreted in BM, and DTG PK changes were not clinically significant in both pregnancy and postpartum period. DTG Ctrough decreased by 37%, when DTG was administered with AL, 42% when administered with AS-AQ and 24% decrease in AUC0-24 when administered with AS-AQ, but were all above the protein adjusted IC90 for the Ctrough and does not warrant dose adjustment. An estimated 41.8% use of herbal medication was recorded amongst 742 PLWH attending HIV clinics. Herbal use preceded HIV therapy in 38.4% while 14.5% were yet to commence ART. A total of 3 (2%) out of 138 herbal samples evaluated, were contaminated with detectable levels of tenofovir and emtricitabine which is a concern, though implication is unknown

Spatial & Temporal Characteristics of Ha flares during the period 1975-2002 (comparison with SXR flares)

Although the energetic phenomena of the Sun (flares, coronal mass injections etc.) exhibit intermittent stochastic behavior in their rate of occurrence, they are well correlated to the variations of the solar cycle. In this work we study the spatial and temporal characteristics of transient solar activity in an attempt to statistically interpret the evolution of these phenomena through the solar cycle, in terms of the self-organized criticality theory.Comment: Recent Advances in Astronomy and Astrophysics: 7th International Conference of the Hellenic Astronomical Society. AIP Conference Proceedings, Volume 848, pp. 194-198 (2006

Real-time Tactical and Strategic Sales Management for Intelligent Agents Guided By Economic Regimes

Many enterprises that participate in dynamic markets need to make product pricing and inventory resource utilization decisions in real-time. We describe a family of statistical models that address these needs by combining characterization of the economic environment with the ability to predict future economic conditions to make tactical (short-term) decisions, such as product pricing, and strategic (long-term) decisions, such as level of finished goods inventories. Our models characterize economic conditions, called economic regimes, in the form of recurrent statistical patterns that have clear qualitative interpretations. We show how these models can be used to predict prices, price trends, and the probability of receiving a customer order at a given price. These “regime†models are developed using statistical analysis of historical data, and are used in real-time to characterize observed market conditions and predict the evolution of market conditions over multiple time scales. We evaluate our models using a testbed derived from the Trading Agent Competition for Supply Chain Management (TAC SCM), a supply chain environment characterized by competitive procurement and sales markets, and dynamic pricing. We show how regime models can be used to inform both short-term pricing decisions and longterm resource allocation decisions. Results show that our method outperforms more traditional shortand long-term predictive modeling approaches.dynamic pricing;trading agent competition;agent-mediated electronic commerce;dynamic markets;economic regimes;enabling technologies;price forecasting;supply-chain

Detecting and Forecasting Economic Regimes in Multi-Agent Automated Exchanges

We show how an autonomous agent can use observable market conditions to characterize the microeconomic situation of the market and predict future market trends. The agent can use this information to make both tactical decisions, such as pricing, and strategic decisions, such as product mix and production planning. We develop methods to learn dominant market conditions, such as over-supply or scarcity, from historical data using Gaussian mixture models to construct price density functions. We discuss how this model can be combined with real-time observable information to identify the current dominant market condition and to forecast market changes over a planning horizon. We forecast market changes via both a Markov correction-prediction process and an exponential smoother. Empirical analysis shows that the exponential smoother yields more accurate predictions for the current and the next day (supporting tactical decisions), while the Markov correction-prediction process is better for longer term predictions (supporting strategic decisions). Our approach offers more flexibility than traditional regression based approaches, since it does not assume a fixed functional relationship between dependent and independent variables. We validate our methods by presenting experimental results in a case study, the Trading Agent Competition for Supply Chain Management.dynamic pricing;machine learning;market forecasting;Trading agents

Flexible Decision Support in Dynamic Interorganizational Networks

An effective Decision Support System (DSS) should help its users improve decision-making in complex, information-rich, environments. We present a feature gap analysis that shows that current decision support technologies lack important qualities for a new generation of agile business models that require easy, temporary integration across organisational boundaries. We enumerate these qualities as DSS Desiderata, properties that can contribute both effectiveness and flexibility to users in such environments. To address this gap, we describe a new design approach that enables users to compose decision behaviours from separate, configurable components, and allows dynamic construction of analysis and modelling tools from small, single-purpose evaluator services. The result is what we call an “evaluator service network” that can easily be configured to test hypotheses and analyse the impact of various choices for elements of decision processes. We have implemented and tested this design in an interactive version of the MinneTAC trading agent, an agent designed for the Trading Agent Competition for Supply Chain Management

Very fast motion planning for highly dexterous-articulated robots

Due to the inherent danger of space exploration, the need for greater use of teleoperated and autonomous robotic systems in space-based applications has long been apparent. Autonomous and semi-autonomous robotic devices have been proposed for carrying out routine functions associated with scientific experiments aboard the shuttle and space station. Finally, research into the use of such devices for planetary exploration continues. To accomplish their assigned tasks, all such autonomous and semi-autonomous devices will require the ability to move themselves through space without hitting themselves or the objects which surround them. In space it is important to execute the necessary motions correctly when they are first attempted because repositioning is expensive in terms of both time and resources (e.g., fuel). Finally, such devices will have to function in a variety of different environments. Given these constraints, a means for fast motion planning to insure the correct movement of robotic devices would be ideal. Unfortunately, motion planning algorithms are rarely used in practice because of their computational complexity. Fast methods have been developed for detecting imminent collisions, but the more general problem of motion planning remains computationally intractable. However, in this paper we show how the use of multicomputers and appropriate parallel algorithms can substantially reduce the time required to synthesize paths for dexterous articulated robots with a large number of joints. We have developed a parallel formulation of the Randomized Path Planner proposed by Barraquand and Latombe. We have shown that our parallel formulation is capable of formulating plans in a few seconds or less on various parallel architectures including: the nCUBE2 multicomputer with up to 1024 processors (nCUBE2 is a registered trademark of the nCUBE corporation), and a network of workstations

Flexible Decision Control in an Autonomous Trading Agent

An autonomous trading agent is a complex piece of software that must operate in a competitive economic environment and support a research agenda. We describe the structure of decision processes in the MinneTAC trading agent, focusing on the use of evaluators – configurable, composable modules for data analysis and prediction that are chained together at runtime to support agent decision-making. Through a set of examples, we show how this structure supports sales and procurement decisions, and how those decision processes can be modified in useful ways by changing evaluator configurations. To put this work in context, we also report on results of an informal survey of agent design approaches among the competitors in the Trading Agent Competition for Supply Chain Management (TAC SCM)

Neuromyths About Neurodevelopmental Disorders: Misconceptions by Educators and the General Public

Neuromyths are commonly held misconceptions about the brain believed by both the general public and educators. While much research has investigated the prevalence of myths about the typically developing brain, less attention has been devoted to the pervasiveness of neuromyths about neurodevelopmental disorders, which have the potential to exacerbate stigma. This preregistered study investigated to what extent neuromyths about neurodevelopmental disorders (namely dyslexia, attention deficit hyperactivity disorder, autism spectrum disorders, and syndrome) are endorsed by two groups: the general public and those working in education. In an online survey, 366 members of the general public and 203 individuals working in education rated similar numbers of myths to be true, but more about neurodevelopmental disorders than general neuromyths. As the frequency of access to brain information emerged as a protective factor against endorsing myths in both populations, we argue that this problem may be addressed via provision of neuroeducational resources