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

Competition-induced stress does not explain deceptive alarm calling in tufted capuchin monkeys

Tactical deception has long attracted interest because it is often assumed to entail complex cognitive mechanisms. However, systematic evidence of tactical deception is rare and no study has attempted to determine whether such behaviours may be underpinned by relatively simple mechanisms. This study examined whether deceptive alarm calling among wild tufted capuchin monkeys, Cebus apella nigritus, feeding on contestable food resources can be potentially explained by a physiological mechanism, namely increased activation in the adrenocortex and the resulting production of glucocorticoids (GCs; ‘stress hormones’). This was tested experimentally in Iguazu? National Park, Argentina, by manipulating the potential for contest competition over food and noninvasively monitoring GC production through analysis of faecal hormone metabolites. If deceptive false alarms are indeed associated with adreno- cortical activity, it was predicted that the patterns of production of these calls would match the patterns of GC output, generally being higher in callers than noncallers in cases in which food is most contestable, and specifically being higher in callers on those occasions when a deceptive false alarm was produced. This hypothesis was not supported, as (1) GC output was significantly lower in association with the experimental introduction of contestable resources than in natural contexts wherein the potential for contest is lower, (2) within experimental contexts, there was a nonsignificant tendency for noncallers to show higher GC output than callers when food was most contestable, and (3) individuals did not show higher GC levels in cases in which they produced deceptive alarms relative to cases in which they did not. A learned association between the production of alarms and increased access to food may be the most likely cognitive explanation for this case of tactical deception, although unexplored physiological mechanisms also remain possible

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

Decisional Fit under Turbulent Circumstances

The purpose of this communication is to study the effect of a recent networking decision support system (called Link 16) on decision performance, within the specific context of military operations. Based on a new decision model - the Decisional Fit Model ? we demonstrate that Link 16 fits with task characteristics and decision maker internal representations of the problem domain. However, improvements could be considered in order to increase the level of fit.Systèmes d'aide à la décision, Modèle d'adéquation, prise de décision en situation, conscience de la situation, performance décisionnelle

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 339)

This bibliography lists 105 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during July 1990. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

The modern military leader as sensemaker on the battlefield

The study on which this article reports, addressed the problem with which modern military leaders on the battlefield are faced in assisting the soldier at basic level to make sense of what is happening. In this study, the term ‘sensemaker’ implied a process of individual and group sensemaking that forms the basis for meaning-making in the volatile, unpredictable, complex and ambiguous (VUCA) world within which soldiers are functioning. The authors postulate a best-fit world view for military leaders in this military leadership sensemaking and meaning-making nexus. They coined ‘social constructivism in complexity’ where the military leader acts as a guide for soldiers through a sensemaking process. This process is graphically represented, and requires a toolkit to assist military leaders in working as sensemakers on the battlefield. The article concludes with recommendations to military psychologists and military educators who have to make policy changes to develop and implement such a toolkit for sensemaking on the battlefield