A comparative study of game theoretic and evolutionary models for software agents

Most of the existing work in the study of bargaining behaviour uses techniques from game theory. Game theoretic models for bargaining assume that players are perfectly rational and that this rationality in common knowledge. However, the perfect rationality assumption does not hold for real-life bargaining scenarios with humans as players, since results from experimental economics show that humans find their way to the best strategy through trial and error, and not typically by means of rational deliberation. Such players are said to be boundedly rational. In playing a game against an opponent with bounded rationality, the most effective strategy of a player is not the equilibrium strategy but the one that is the best reply to the opponent's strategy. The evolutionary model provides a means for studying the bargaining behaviour of boundedly rational players. This paper provides a comprehensive comparison of the game theoretic and evolutionary approaches to bargaining by examining their assumptions, goals, and limitations. We then study the implications of these differences from the perspective of the software agent developer

An anytime approximation method for the inverse Shapley value problem

Coalition formation is the process of bringing together two or more agents so as to achieve goals that individuals on their own cannot, or to achieve them more efficiently. Typically, in such situations, the agents have conflicting preferences over the set of possible joint goals. Thus, before the agents realize the benefits of cooperation, they must find a way of resolving these conflicts and reaching a consensus. In this context, cooperative game theory offers the voting game as a mechanism for agents to reach a consensus. It also offers the Shapley value as a way of measuring the influence or power a player has in determining the outcome of a voting game. Given this, the designer of a voting game wants to construct a game such that a players Shapley value is equal to some desired value. This is called the inverse Shapley value problem. Solving this problem is necessary, for instance, to ensure fairness in the players voting powers. However, from a computational perspective, finding a players Shapley value for a given game is #p-complete. Consequently, the problem of verifying that a voting game does indeed yield the required powers to the agents is also #P-complete. Therefore, in order to overcome this problem we present a computationally efficient approximation algorithm for solving the inverse problem. This method is based on the technique of successive approximations; it starts with some initial approximate solution and iteratively updates it such that after each iteration, the approximate gets closer to the required solution. This is an anytime algorithm and has time complexity polynomial in the number of players. We also analyze the performance of this method in terms of its approximation error and the rate of convergence of an initial solution to the required one. Specifically, we show that the former decreases after each iteration, and that the latter increases with the number of players and also with the initial approximation error. Copyright © 2008, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaarnas.org). All rights reserved

On the Identification of Agents in the Design of Production Control Systems

This paper describes a methodology that is being developed for designing and building agent-based systems for the domain of production control. In particular, this paper deals with the steps that are involved in identifying the agents and in specifying their responsibilities. The methodology aims to be usable by engineers who have a background in production control but who have no prior experience in agent technology. For this reason, the methodology needs to be very prescriptive with respect to the agent-related aspects of design

Mass extinctions past and present: a unifying hypothesis

International audienceEnzymes are often referred to as the "agents of life" ? a very apt term, since essentially all life processes are controlled by them. Typically, these enzymes only function across a narrow band of environmental conditions, particularly temperature and pH. Ambient conditions that challenge these operating conspecifics trigger enzyme dysfunction. Here, it is proposed that the pH-dependent inactivation of a single enzyme, urease, provides a unifying kill-mechanism for at least four of the "big five" mass extinctions of the past 560 million years. The triggering of this kill-mechanism is suggested to be sensitive to both gradualistic and catastrophic environmental disturbances that cause the operating pH of urease-dependent organisms to cross enzymatic "dead zones", one of which is suggested to exist at ~pH 7.9. For a wide range of oceanic and terrestrial ecosystems, this pH threshold coincides with an atmospheric CO2 partial pressure (pCO2) of ~560 ppmv ? a level that at current CO2 emission trajectories may be exceeded as early as 2050. The urease hypothesis thus predicts an impending Anthropocene extinction event of equivalence to the "big five" unless future atmospheric pCO2 levels can be stabilised well below 560 ppmv. Immediate scientific discussion and testing is required to confirm the validity of the urease hypothesis

Regional-scale hydrological modelling using multiple-parameter landscape zones and a quasi-distributed water balance model

Regional-scale catchments are characterised typically by natural variability in climatic and land-surface features. This paper addresses the important question regarding the appropriate level of spatial disaggregation necessary to guarantee a hydrologically sound consideration of this variability. Using a simple hydrologic model along with physical catchment data, the problem is reconsidered as a model parameter identification problem. With this manner of thinking the subjective nature as to what to include in the disaggregation scheme is removed and the problem reconsidered in terms of what can be supported by the available data. With such an approach the relative merit of different catchment disaggregation schemes is viewed in terms of their ability to provide constrained parameterisations that can be explained in terms of the physical processes deemed active within a catchment. The outlined methodology was tested for a regional-scale catchment, located in eastern Australia, and involved using the quasi-distributed VIC catchment model to recover the characteristic responses resulting from the disaggregation of the catchment into combinations of climate, soil and vegetation characteristics. A land-surface classification based on a combination of soil depth and land cover type was found to provide the most accurate streamflow predictions during a 10-year validation period. Investigation of the uncertainty associated with the predictions due to weakly identified parameters however, revealed that a simpler classification based solely on land cover actually provided a more robust parameterisation of streamflow response. The result alludes to the hydrological importance of distinguishing between forested and non-forested land cover types at the regional-scale, and suggests that given additional information soil-depth / storage considerations may also have proved significant. Improvements to the outlined method are discussed in terms of increasing the informative content available to differentiate between competing catchment responses.</p> <p style='line-height: 20px;'><b>Keywords:</b> regional-scale, spatial variability, disaggregation, hydrotype, quasi-distributed, parameterisation, uncertaint

Regional-scale hydrological modelling using multiple-parameter landscape zones and a quasi-distributed water balance model

International audienceRegional-scale catchments are characterised typically by natural variability in climatic and land-surface features. This paper addresses the important question regarding the appropriate level of spatial disaggregation necessary to guarantee a hydrologically sound consideration of this variability. Using a simple hydrologic model along with physical catchment data, the problem is reconsidered as a model parameter identification problem. With this manner of thinking the subjective nature as to what to include in the disaggregation scheme is removed and the problem reconsidered in terms of what can be supported by the available data. With such an approach the relative merit of different catchment disaggregation schemes is viewed in terms of their ability to provide constrained parameterisations that can be explained in terms of the physical processes deemed active within a catchment. The outlined methodology was tested for a regional-scale catchment, located in eastern Australia, and involved using the quasi-distributed VIC catchment model to recover the characteristic responses resulting from the disaggregation of the catchment into combinations of climate, soil and vegetation characteristics. A land-surface classification based on a combination of soil depth and land cover type was found to provide the most accurate streamflow predictions during a 10-year validation period. Investigation of the uncertainty associated with the predictions due to weakly identified parameters however, revealed that a simpler classification based solely on land cover actually provided a more robust parameterisation of streamflow response. The result alludes to the hydrological importance of distinguishing between forested and non-forested land cover types at the regional-scale, and suggests that given additional information soil-depth / storage considerations may also have proved significant. Improvements to the outlined method are discussed in terms of increasing the informative content available to differentiate between competing catchment responses. Keywords: regional-scale, spatial variability, disaggregation, hydrotype, quasi-distributed, parameterisation, uncertaint

Towards service-oriented ontology-based coordination

Coordination is a central problem in distributed computing. The aim is towards flexible coordination, managed at run-time, in open, dynamic environments. This approach would benefit from an explicit common vocabulary for coordination and hence, in a previous paper, we modelled coordination in an ontology, describing the activities carried out and the interdependencies among these activities. The purpose of this paper is to show how such an ontology can be used alongside a set of rules to perform coordination by managing the interdependencies among activities. The ontology and rules can then be used to provide a general purpose coordination tool in the form of a Web servic

Doubly Robust Estimation of Local Average Treatment Effects Using Inverse Probability Weighted Regression Adjustment

We revisit the problem of estimating the local average treatment effect (LATE) and the local average treatment effect on the treated (LATT) when control variables are available, either to render the instrumental variable (IV) suitably exogenous or to improve precision. Unlike previous approaches, our doubly robust (DR) estimation procedures use quasi-likelihood methods weighted by the inverse of the IV propensity score - so-called inverse probability weighted regression adjustment (IPWRA) estimators. By properly choosing models for the propensity score and outcome models, fitted values are ensured to be in the logical range determined by the response variable, producing DR estimators of LATE and LATT with appealing small sample properties. Inference is relatively straightforward both analytically and using the nonparametric bootstrap. Our DR LATE and DR LATT estimators work well in simulations. We also propose a DR version of the Hausman test that compares different estimates of the average treatment effect on the treated (ATT) under one-sided noncompliance