Optimization of decision networks in structured task environments

This paper considers the problem of determining the optimal distributed decision strategy for a team of decision-makers (DMs) arranged in an arbitrary acyclic organizational structure and controlling a complex structured process. Each DM has access to uncertain and partial information about the task environment and can control only a portion of it. We present an influence diagram model of the joint task-organization system and formulate the optimal team strategy in terms of a set of coupled hypothesis testing tasks at DMs. Specifically, we show that the scope of a local decision task is determined by the interaction of the task structure (what can be measured) and of the information access structure of the organization (who can measure what); while the control structure (who can influence what event) has an impact on the locally perceived costs associated with the decision options available. Theoretical results are illustrated via a numerical example, and connections to existing decision models are discussed     

Symmetric team problems and multi access wire communication

In this paper we deal with the problem of sharing one communication wire among a (possibly large) number of communication stations. The fact that all communication stations are considered identical and that they share one objective of using the communication wire as efficiently as possible leads to the concept of symmetric team problems. For symmetric team problems we define a symmetric solution by the restriction that all decision makers must have identical decision rules. In the first section of this paper the concepts of symmetric team problems and symmetric solutions are developed and motivated. A theorem is given that relates symmetric solutions to randomized decision rules. An example is given which illustrates that the concept of symmetric solutions explains some everyday phenomena. In the second section the access problem in multi-access wire communication is considered as a symmetric team problem. It is shown that the symmetric solution, which corresponds to randomized access rules, tends to give as good performance as the unrestricted solution when the number of stations becomes large (asymptotic optimality). The solutions are also determined numerically, giving quantitative information on the asymptotic behavior.     

An approach to decentralized control of large scale systems using aggregation methods

A two-level decentralized control structure is formulated for large scale interconnected subsystems controlled byNdecision makers. Chained aggregation is used to decompose the overall team problem with a decentralized information structure into (N + 1) subproblems: one low order team problem with a centralized information structure andNdecentralized optimal control problems. Accordingly, the control of each decision maker is decomposed into three components: a decoupling control which induces aggregation, a local control which controls the subsystem dynamics, and an aggregate control which controls the dynamics of the interconnection variables. The robustness of this composite control with respect to perturbations in the system dynamics and the cost functional is established.     

非部分嵌套信息结构的LQG动态队决策问题的可解性（II）*

本文讨论非嵌套信息结构的递阶队决策问题和控制均享信息结构的LQG分散控制问题,文中首先证明这两类问题的信息结构都是“部分控制嵌入”的,进而给出最优策略(或控制)存在的充要条件和当此条件成立时最优策略(或控制)的表达式。     

The garbling decision maker: A model of bounded rationality

A model is constructed of a garbling decision maker-one who randomizes his decision in response to the quantity of information he uses to make his decision. This model is supposed to capture the effects of bounded rationality on decision making and is imbedded in a team problem to model the organization designer's problem. A few results are derived from the linear-quadratic-Gaussian static team formulation developed here.     

Nonlinear robust control and minimax team problems

The problem of robust stabilization of a linear system leads to the classical ℋ︁_∞ control problem. The same analysis applied to a nonlinear system leads to the problem of ensuring via output feedback that a nonlinear operator be Lipshitz continuous, with a prescribed Lipshitz modulus. We show that, in the same way as the ℋ︁_∞ control problem is equivalent to a minimax control problem, the Lipshitz modulus control problem can be approached via a minimax team decision problem. This motivates us to re-visit a class of the so-called ‘static’ team decision problems for nonlinear dynamical control systems. Because of the ‘static’ character, signaling plays no role in that case, which is important for the equivalence with the Lipshitz modulus control problem. We show that under some conditions, a certainty equivalence principle applies that yields a practical solution to the team problem at hand. To reach that conclusion we must first investigate a ‘partial team’ problem where one of the team members has all the information. Copyright © 1999 John Wiley & Sons, Ltd.     

Ultrafuzzy team decisions in a dynamic environment

In this paper, the concept of fuzzy sets of type 2 is introduced and the team decision processes which contain ultrafuzzy states, ultrafuzzy information structures, ultrafuzzy information signals, ultrafuzzy decision rules, and ultrafuzzy actions are formulated. After some definitions of fuzzy relations of type 2, fuzzy sets of type 2 induced by mappings, composition, Cartesian product, ultrafuzzy mappings, and ultrafuzzy functions, a model of ultrafuzzy team decision in a dynamic environment is proposed. The team decision problem under ultrafuzzy constraints is dealt with. Some results on fuzzy sets of type 2 induced by mappings are given.     

Multi-objective optimization and decision making approaches to cricket team selection

Selection of players for a sports team within a finite budget is a complex task which can be viewed as a constrained multi-objective optimization and a multiple criteria decision making problem. The task is specially challenging for the game of cricket where a team requires players who are efficient in multiple roles. In the formation of a good and successful cricket team, batting strength and bowling strength of a team are major factors affecting its performance and an optimum trade-off needs to be reached. We propose a novel gene representation scheme and a multi-objective approach using the NSGA-II algorithm to optimize the overall batting and bowling strength of a team with 11 players as variables. Fielding performance and a number of other cricketing criteria are also used in the optimization and decision-making process. Using the information from the trade-off front obtained, a multi-criteria decision making approach is then proposed for the final selection of team. Case studies using a set of players auctioned in Indian Premier League (IPL) 4th edition are illustrated and players’ current statistical data is used to define performance indicators. The proposed computational techniques are ready to be extended according to individualistic preferences of different franchises and league managers in order to form a preferred team within the budget constraints. It is also shown how such an analysis can help in dynamic auction environments, like selecting a team under player-by-player auction. The methodology is generic and can be easily extended to other sports like American football, baseball and other league games.     

Partially nested information structures with a common past

A team control problem is considered whose information structure is partially nested and is characterized by the existence of a common past information set shared by the team members after a finite delay. Under LQG assumptions, it is shown that the optimal control strategy can take on a time-invariant recursive form based on suitable sufficient statistics.     

The dynamic linear exponential Gaussian team problem

The dynamic team problem for a linear system with Gaussian noise, exponential of a quadratic performance index, and one-step delayed sharing information pattern is considered. It is shown, via dynamic programming, that the multistage problem can be decomposed into a series of static team problems. Moreover, the optimal policy of theith team member at timekis an affine function of both the one-step predicted Kalman filter estimate and theith team member's observation at timek. Efficient algorithms are available for determining the gains of this affine controller. This model and solution are applied to an approximate resource allocation problem associated with a defense network, and a numerical example is discussed.     

On optimal distributed decision architectures in a hypothesistesting environment

The authors consider the distributed detection problem, in which a set of decision makers (DMs) receive observations of the environment and transmit finite-values messages to other DMs according to prespecified communication protocols. A designated primary DM makes the final decision on one out of two alternative hypothesis. All DMs make decisions, in order to maximize a measure of organizational performance. The problem is to find an architecture for the organization which remains optimal for a variety of operating conditions. It is shown that even for very small organizations this problem is quite complex because the optimal architecture depends on variables external to the team, so that global conclusions on optimal organizational structures cannot be drawn. Suboptimal solutions are considered, and bounds on their performance are obtained     

Properties of Nash solutions of a two-stage nonzero-sum game

This paper contains exact expressions for the complete class of uncountably many globally optimal affine Nasb equilibrium strategies for a two-stage two-person nonzero-sum game problem with quadratic objective functionals and with dynamic information for beth players. Existence conditions for each of these Nash equilibrium solutions are derived and it is shown that a recursive Nash solution is not necessarily globally optimal. Cost-uniqueness property of the derived Nash strategies is investigated and it is proven that the game problem under consideration admits a unique Nash cost pair if and only if it can be made equivalent to either a team problem or a zero-sum game. It is also shown that existence conditions of a globally optimal Nash solution will be independent of the parameters characterizing the nonuniques of the Nash strategies only if the game problem can be made equivalent to a team problem.     

A multimodel approach to stochastic team problems

This paper develops decentralized team strategies for decision makers using different models of the same large-scale system. Multiparameter singular perturbations are employed to capture the multimodel nature of the fast dynamic subsystems interconnected through slow dynamic variables. The small parameters are appropriately scaled so that the variables in both time scales are well defined. The system considered is linear and the cost criterion is quadratic. First, a multimodel solution is obtained when the decision makers make different noisy linear observations of the random initial state only. Then the solution to this static team problem is utilized to obtain a multimodel solution to the dynamic team problem with sampled observations under the one-step-delay observation sharing pattern. In both cases, the well-posedness of the multimodel solution is demonstrated.     

Decomposition of dynamic team decision problems

This paper considers the question "when can a dynamic team problem be decomposed into several smaller dynamic team problems?" A team is partitioned into several groups of members. Precedence relation a nd nestedness relation of information among these groups are defined. Then the concepts of independent partition and sequential partition of a team are introduced, which are partitions satisfying some conditions on their precedence relation, nestedness relation, and cost function. It is shown that if a team has an independent (sequential) partition, the problem can be decomposed into several independent (related) subproblems. It is also shown that the finest independent (sequential) partition is unique. In addition, decomposition of decentralized control problems is discussed.     

基于multi-agent的地震信息资源决策平台设计

针对传统决策系统的局限性,设计一个基于agent的地震信息决策支持平台。介绍该平台的流程和组织结构,并着重阐述分布式问题的协同控制策略,最后设计了平台中通信和语言机制,为地震信息资源的决策问题提供了一种思路和借鉴。     

Distributed robust finite-time nonlinear consensus protocols for multi-agent systems

This paper investigates the robust finite-time consensus problem of multi-agent systems in networks with undirected topology. Global nonlinear consensus protocols augmented with a variable structure are constructed with the aid of Lyapunov functions for each single-integrator agent dynamics in the presence of external disturbances. In particular, it is shown that the finite settling time of the proposed general framework for robust consensus design is upper bounded for any initial condition. This makes it possible for network consensus problems to design and estimate the convergence time offline for a multi-agent team with a given undirected information flow. Finally, simulation results are presented to demonstrate the performance and effectiveness of our finite-time protocols.     

Production planning and control I. The decision problem

The application of the linear-quadratic-gaussian (LQG) tracking problem to production planning and control systems is discussed. Decision concepts are developed from an examination of the structure of a generalized production control system. The decision problem is modelled as a LQG tracking problem operating in the presence of persistent disturbances—the disturbances representing the demand for finished goods. The development of a solution leads to a linear, time-invariant decision policy which is a decomposition of the decision input into separate and nearly independent decision tasks. Sufficient conditions for the existence of a solution are presented. An open-loop, closed-loop decision system is presented to show how the decision model can be used to analyse relationships among system structure, performance, and information requirements.     

Individual Creativity and Team Climate in Software Development Projects: The Mediating Role of Team Decision Processes

This study investigates how individual creativity is related to the quality of team decision processes and team climate, and the mediating role of team decision processes between individual creativity and team climate. A multi‐level theoretical model was proposed and partial least squares structural equation modelling (PLS‐SEM) was conducted on a sample of 139 software development projects. The results suggest that: (i) individual creativity improves the quality of team decision processes, (ii) team decision processes are positively associated with four dimensions of team climate (organizational support, innovation orientation, goal orientation and informal structure), and (iii) team decision processes partially mediate between individual creativity and team climate. In particular, the obtained results stress the role of individual creativity in the formation and evolution of a positive climate by means of team decision processes. The study implies that managers should recognize the value of creative individuals as the basic source of competitive advantage and success. It further discusses the managerial implications of the findings as well as limitations and constructive new directions for future studies to improve software development team performance.     

Training teams for emergency management

Emergency management (EM), the decision making involved in directing the relief operation after a disaster or otherwise catastrophic accident is an issue of great public and private concern because of the high stakes involved. Due to the nature of emergencies, and especially mass emergencies, EM teams are faced with decision making in stressful situations, information ambiguity and overload, and a significant level of uncertainty, whereby non-routine problem solving of a knowledge-based nature is required. An important characteristic of EM is that it is a team of teams; multiple teams that come from different organizations, with different organizational goals and different organizational cultures, that work together to minimize the negative effects of the emergency. As a consequence, EM requires good coordination and communication not just within, but also among the various teams involved. Coordination among teams should, therefore, be a key focus for training. This paper describes EM within the context of naturalistic decision making, and proposes a framework, an event-based approach to training, together with a number of team training strategies that may be applicable to EM. A brief assessment of available training technologies and recommendations for future research are discussed.