Goal-seeking System Research Articles

The Dynamics of Brand-Driven Quality Improvement Decision-Making in Multi-Small-Supplier Agri-Food Supply Chain: The Case of China

This paper develops a system dynamics framework for the closed-loop agri-food brand supply chain (AFBSC) with multiple small farmer suppliers and one core brand manufacturer, and investigates the influences of various factors including brand effort, quality elasticity, price elasticity, revenue sharing, and the number of suppliers on the system behavior. The results show: (i) food quality is determined by all farmer suppliers, who might choose hitchhiking with the prisoner’s dilemma game in a decentralized decision-making mode; (ii) brand effort to improve brand value for food quality is mainly made by the core brand manufacturer, who presents a goal-seeking system dynamics (SD) manner with oscillation behavior around the expected quality of consumers; (iii) whether farmer suppliers or brand manufacturers, the centralized decision-making mode is more useful for them to increase revenue than the decentralized one; furthermore, the shared centralized decision-making mode is most useful for them to obtain more revenue, and the brand manufacturer is still the biggest beneficiary.

Observability of stochastic complex networks under the supervision of cognitive dynamic systems

Much has been said about observability in system theory and control; however, it has been recently that observability in complex networks has seriously attracted the attention of researchers. This paper examines the state-of-the-art and discusses some issues raised due to "complexity" and "stochasticity". These unresolved issues call for a new practical methodology. For stochastic systems, a degree of observability may be defined and the observability problem is not a binary (i.e., yes-no) question anymore. Here, we propose to employ a goal-seeking system to play a supervisory role in the network. Hence, improving the degree of observability would be a valid objective for the supervisory system. Towards this goal, the supervisor dynamically optimizes the observation process by reconfiguring the sensory parts in the network. A cognitive dynamic system is suggested as a proper choice for the supervisory system. In this framework, the network itself is viewed as the environment with which the cognitive dynamic system interacts. Computer experiments confirm the potential of the proposed approach for addressing some of the issues raised in networks due to complexity and stochasticity.

Organizational Identity and the Structure of Nonprofit Umbrella Associations

AbstractThis article applies the concept of organizational identity to the structural issues faced by national and international nonprofit umbrella associations. Such associations grapple with several possible self‐concepts, including goal‐seeking systems, economies, and polities . Two associations—CIVICUS and Girls Incorporated—are studied in depth. Consensus around aclear identity is found to be a key factor in resolving the structural dilemmas of these associations.

Scaling back goals and recalibration of the affect system are processes in normal adaptive self-regulation: understanding ‘response shift’ phenomena

This comment addresses a set of phenomena that have been labeled ‘response shift’. We argue that many of these phenomena reflect recalibration of a goal-seeking system and an affect-management system, both of which are involved in normal adaptive self-regulation. In brief, we hold that these systems act as feedback control mechanisms. The reference values for both systems continuously undergo gradual recalibration. Because in most circumstances the adjustments tend to occur with equivalent frequency in both directions, their cumulative effect is minimal. In situations of either unusually prolonged goal attainment (and overattainment) or unusually prolonged adversity (as occurs, e.g., with deteriorating health), the cumulative effect can be substantial. We believe that these latter recalibrations of reference value account for many response shift phenomena. Other such phenomena are accounted for by the principle of hierarchical organization among the self-regulatory goals that comprise the self.

Spatial and temporal cognitive mapping: a neural network approach

Tolman suggested that cognitive behavior is purposive and can be described in terms of how differant goals are pursued. When pursuing these goals, animals and humans display a remarkable adaptability, which is the result of the combination of a goal-seeking mechanism and a cognitive map. Whereas the goal-seeking mechanism permits the animal to seek different goals, adopting alternative behavioral strategies that are independent of any set of responses, the cognitive map allows the integration of multiple independent pieces of knowledge. Although the concept of cognitive mapping has been mostly applied to spatial mapping, we describe how both spatial and temporal cognitive maps can be mechanistically implemented in terms of recurrent associative networks which store either the adjacency of spatial locations or the contiguity of temporal events. The reinjected predictions of spatial locations or temporal events in the network can be conceptualized as images and their sequences conceptualized as the process of imagining. The combination of goal-seeking systems and cognitive maps permits the description of problem solving tasks in terms of the sequence of subgoals (a plan) to be pursued to reach the goal. Whereas the hippocampus might play a major role in the storage of both spatial and temporal cognitive maps in association cortex, the frontal cortex might participate in goal-seeking tasks, decision making and planing.

The psychology of robots

In recent years, neural networks have been proposed that portray many of the complexities of adaptive behavior. The networks describe how agents learn to predict future events by: 1) building models of the would, 2) inferring new predictions from past experiences, 3) combining elementary environmental stimuli into complex internal representations, 4) attending to stimuli associated with environmental novelty, and 5) attending to stimuli that are good predictors of other environmental events. When a predictive network is attached to a goal seeking system, the resulting architecture is able to describe spatial and maze navigation, as well as problem solving and planning. When the predictions of future events are based on the combination of environmental stimuli and the animal's own responses the networks provide the information necessary to choose between alternative behaviors. When the agent's own responses can be identified with the responses of other agents, the networks can describe learning by imitation. It is suggested that these principles might be applied to the design of adaptive, communicating autonomous robots.

On the market value of information commodities. I. The nature of information and information commodities

This article lays the conceptual foundations for the study of the market value of information commodities. The terms “information” and “commodity” are given precise definitions in order to characterize “information commodity,” and thus to provide a sound basis for examining questions of pricing. Information is used by marketplace actors to make decisions or to control processes. Thus, we define information as the ability of a goal-seeking system to decide or control. By “decide” we mean choosing one alternative among several that may be executed in pursuit of a well-defined objective. “Control” means the ordering of actions. Two factors make it possible to turn something into a commodity: (1) appropriability, and (2) valuability. If something cannot be appropriated (i.e., owned), it cannot be traded; moreover, if it cannot be valued, there is no way to determine for what it might be exchanged. We define an information commodity as a commodity whose function it is to enable the user, a goal-seeking system, to obtain information, i.e., to otain the ability to decide or control. Books, databases, computer programs, and advisory services are common examples of information commodities. Their market value derives from their capacity to furnish information. © 1992 John Wiley & Sons, Inc.

Automatic Control and Directed Cell Movement Novel Approach for Understanding Chemotaxis, Galvanotaxis, Galvanotropism

It is shown that chemotaxis, galvanotaxis, galvanotropism, etc. are functions of cells having a goal-seeking system. Even when the involved physicochemical signals are unknown, the cellular system can be treated phenomenologically like an automatic controller having a closed-loop feedback system. The model is verified by means of galvanotaxis and chemotaxis data of human granulocytes. The galvanotaxis and chemotaxis coefficient quantifying the cellular sensibility can be predicted from the coefficient which characterizes the deterministic part of the signal transduction/response system of the cell divided by the coefficient which characterizes the noise strength in the cellular signal transduction/response system. The model is not restricted to directed movement of granulocytes. It is very general and can be applied to any cell type for directed phenomena like chemotaxis, galvanotaxis, phototaxis, magnetotaxis, directed growth, etc. The virus-disturbed directed migration of granulocytes is discussed and it is shown that the virus alters the deterministic part of the cellular controller.

Learning as a generating process of higher-order decision situations by a goal-seeking system

The nature of the learning process of decision-making systems is conceptualized, and the process is formulated and explored in the framework of mathematical general systems theory. Learning is understood as a process by which the decision-making system acquires knowledge about its decision situations to increase the potential of its decision-making ability. First, learning is formulated as a generating process of a sequence of higher-order decision situations, then, after introducing concepts of solutions for the decision situations it is shown that as the order of the decision situations increases their solution sets expand. Furthermore, it is proved that there are certain limitations on the expansions and these are identified. During the generating process of higher-order decision situations, the order of the decision situations increases and they structurally change. In order to explicitly describe the structural changes of the decision situations, a category-theoretic framework is adopted. Then, the limitations of the expansions of the solution sets are expressed as categorical limits.

A model of the visual localization of prey by frog and toad

In this paper we demonstrate how prey localization can be achieved rapidly and accurately by coupling prey-selection and lens-accommodation processes within a feedback loop. Information derived from prey selection supplies a setpoint for accommodation. In turn, adjustment of the lens modifies the visual input and can alter the prey selection process. The natural feedback of this goal-seeking system automatically corrects for the problem of ambiguity in binocular matching. Although it is of general interest as a depth algorithm, we tie the model to the known anatomy, physiology and behavior of frogs and toads. Instead of building a global depth-map we propose that the goal of catching a prey leads a frog or toad to select a particular region of its visual world for special scrutiny. We suggest that the first step of the prey-catching sequence is to adjust the accommodative state of the lenses and thus lock the visual apparatus on to a stimulus. We identify brain regions that could provide the neural substrates necessary to support the model's various functional stages and present experiments, with a computer simulation, that compare its functioning to animal behavior.

ALGEBRAIC FORMULATION OF RELATIONSHIP BETWEEN A GOAL SEEKING SYSTEM AND ITS ENVIRONMENT

The purpose of this paper is, first, to formalize the key concepts for describing the relationship between a goal seeking system and its relevant environment and, then, mainly based on Ashby's Law of Requisite Variety, to develop a formal discussion on the relationship in the framework of mathematical general systems theory. The law, one of the most well-known laws in the general systems theory, intuitively claims that “only the variety can destroy the variety”. Although the claim is so simple and has attracted more and more attention from organization theory, organizational cybernetics and control theory, the concepts involved are used quite loosely. By defining the concepts of the varieties in terms of equivalence relations, we will formulate the basic logic explaining the relationship between a goal seeking system and its relevant environment and explore its meaning and significance. In this process we will also reveal the meaning of the internal model principle, which says that in order to control the...

Theory of Control for Active Goal-Seeking Systems

The paper discusses the premises for and some findings in theory of control for systems made of active goal-seekinf elements. Planning laws are studied and conditions are considered which insure meeting the planned targets by lower level elements.