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Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on

Issue 1 • Date Jan. 2006

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Displaying Results 1 - 20 of 20
  • Table of contents

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  • IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews publication information

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  • Satisficing negotiations

    Page(s): 4 - 18
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    Negotiation procedures that are founded on the doctrine of individual rationality, where each participant is committed to maximizing its own satisfaction, are limited in their ability to accommodate the interests of others, and therefore, may unnecessarily constrain the negotiability of a decision maker, particularly in cooperative environments. Satisficing game theory provides a distinct alternative to the hyperrationality of conventional rational choice by waiving reliance on the individual rationality premise and offering an approach to negotiatory decision making that is based on a well-defined mathematical notion of satisficing, or being good enough, that permits the modeling of complex interrelationships between agents. This approach provides a mechanism to compute the attitude, or degree of conflict or contentedness, of the negotiators. Examples illustrate both single-round and multiround satisficing negotiation protocols View full abstract»

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  • Integrative negotiation among agents situated in organizations

    Page(s): 19 - 30
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    This paper addresses the problem of negotiation in a complex organizational context. An integrative negotiation mechanism is introduced, which enables agents to dynamically select a negotiation attitude based on the degree of external directedness. Experimental work explores the question of whether it always improves the organization's social welfare to have an agent be completely externally directed when negotiating and making choices. Results show that there are situations in which it is better for the organization if agents are partially externally directed in their negotiations with other agents rather than completely externally directed. The paper discusses the driving factors behind this unexpected result View full abstract»

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  • Bilateral negotiation decisions with uncertain dynamic outside options

    Page(s): 31 - 44
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (264 KB) |  | HTML iconHTML  

    We present a model for bilateral negotiations that considers the uncertain and dynamic outside options. Outside options affect the negotiation strategies via their impact on the reservation price. The model is composed of three modules: single-threaded negotiations, synchronized multithreaded negotiations, and dynamic multithreaded negotiations. These three modules embody increased sophistication and complexity. The single-threaded negotiation model provides negotiation strategies without specifically considering outside options. The model of synchronized multithreaded negotiations builds on the single-threaded negotiation model and considers the presence of concurrently existing outside options. The model of dynamic multithreaded negotiations expands the synchronized multithreaded model by considering the uncertain outside options that may come dynamically in the future. Experimental analysis is provided to characterize the impact of outside options on the reservation price and thus on the negotiation strategy. The results show that the utility of a negotiator improves significantly if he/she considers outside options, and the average utility is higher when he/she considers both the concurrent outside options and the foresees future options View full abstract»

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  • Bilateral bargaining with multiple opportunities: knowing your opponent's bargaining position

    Page(s): 45 - 55
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (297 KB) |  | HTML iconHTML  

    Negotiations have been extensively studied theoretically throughout the years. A well-known bilateral approach is the ultimatum game, where two agents negotiate on how to split a surplus or a "dollar"-the proposer makes an offer and responder can choose to accept or reject. In this paper a natural extension of the ultimatum game is presented, in which both agents can negotiate with other opponents in case of a disagreement. This way the basics of a competitive market are modeled, where, for instance, a buyer can try several sellers before making a purchase decision. The game is investigated using an evolutionary simulation. The outcomes appear to depend largely on the information available to the agents. We find that if the agents' number of remaining bargaining opportunities is commonly known, the proposer has the advantage. If this information is held private, however, the responder can obtain a larger share of the surplus. For the first case we also provide a game-theoretic analysis and compare the outcome with evolutionary results. Furthermore, the effects of search costs, uncertainty about future opportunities, and allowing multiple issues to be negotiated simultaneously are investigated View full abstract»

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  • Software agents and market (in) efficiency: a human trader experiment

    Page(s): 56 - 67
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (244 KB) |  | HTML iconHTML  

    This paper studies how software agents influence the market behavior of human traders. Software agents with a passive arbitrage-seeking strategy are introduced in a double auction market experiment with human subjects in the laboratory. As a treatment variable, the influence of information on the existence of software agents is investigated. We found that common knowledge about the presence of software agents triggers more efficient market prices when the programmed strategy was employed, whereas an effect of the information condition on behavioral variables could not be observed. When controlling for information on software agents' participation, the introduction of software agents results in lower market efficiency View full abstract»

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  • A game theoretic approach to contracts in multiagent systems

    Page(s): 68 - 79
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    Contracts are used to create new interaction possibilities among agents, and therefore play an important role in the game theoretic analysis of agent interaction. We use normative multiagent systems to model both the contracts and the interactions. In particular, we formalize contracts as systems of regulative and constitutive norms within a larger rule-governed setting and, using recursive modeling, we develop a game theory wherein agents make contracts. We show how agents can modify the behavior of normative systems by means of constitutive rules in the contract changing these systems, and we illustrate how agents use the game theory within contract negotiation in organizations View full abstract»

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  • A Cooperative mediation-based protocol for dynamic distributed resource allocation

    Page(s): 80 - 91
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    In this paper, we present a cooperative mediation-based protocol that solves a distributed resource allocation problem while conforming to soft real-time constraints in a dynamic environment. Two central principles are used in this protocol that allow it to operate in constantly changing conditions. First, we frame the allocation problem as an optimization problem, similar to a partial constraint satisfaction problem (PCSP), and use relaxation techniques to derive conflict (constraint violation) free solutions. Second, by using overlapping mediation sessions to conduct the search, we are able to prune large parts of the search space by using a form of arc-consistency. This allows the protocol to both quickly identify situations when the problem is over-constrained, and to determine the appropriate repair. From the global perspective, the protocol has a hill climbing behavior and because it was designed to work in dynamic environments, is approximate. We describe the domain which inspired the creation of this protocol, as well as discuss experimental results View full abstract»

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  • Learning dynamic prices in MultiSeller electronic retail markets with price sensitive customers, stochastic demands, and inventory replenishments

    Page(s): 92 - 106
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (307 KB) |  | HTML iconHTML  

    In this paper, we use reinforcement learning (RL) as a tool to study price dynamics in an electronic retail market consisting of two competing sellers, and price sensitive and lead time sensitive customers. Sellers, offering identical products, compete on price to satisfy stochastically arriving demands (customers), and follow standard inventory control and replenishment policies to manage their inventories. In such a generalized setting, RL techniques have not previously been applied. We consider two representative cases: 1) no information case, were none of the sellers has any information about customer queue levels, inventory levels, or prices at the competitors; and 2) partial information case, where every seller has information about the customer queue levels and inventory levels of the competitors. Sellers employ automated pricing agents, or pricebots, which use RL-based pricing algorithms to reset the prices at random intervals based on factors such as number of back orders, inventory levels, and replenishment lead times, with the objective of maximizing discounted cumulative profit. In the no information case, we show that a seller who uses Q-learning outperforms a seller who uses derivative following (DF). In the partial information case, we model the problem as a Markovian game and use actor-critic based RL to learn dynamic prices. We believe our approach to solving these problems is a new and promising way of setting dynamic prices in multiseller environments with stochastic demands, price sensitive customers, and inventory replenishments View full abstract»

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  • ISEM: a multiagent Simulator for testing agent market strategies

    Page(s): 107 - 113
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    With the increasing importance of e-commerce across the Internet, the need for software agents to support customers and suppliers in buying and selling goods/services is growing rapidly. It is becoming increasingly evident that in a few years the Internet will host a large number of interacting software agents. Most of them will be economically motivated, and will negotiate a variety of goods and services. It is therefore important to consider the economic incentives and behaviors of economic software agents, and to use all available means to anticipate their collective interactions. This paper addresses this concern by presenting a multiagent market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, and considering risk preferences. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions. The results of the negotiations between agents are analyzed by data mining algorithms to extract rules that give agents feedback to improve their strategies View full abstract»

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  • List of Reviewers for the Special Issue on Game-Theoretic Analysis and Stochastic Simulation

    Page(s): 114
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  • Special issue on service systems and service management

    Page(s): 115
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  • 2006 IEEE International Conference on Systems, Man, and Cybernetics

    Page(s): 116
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  • Special issue on intelligent computation for bioinformatics

    Page(s): 117
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  • IEEE order form for reprints

    Page(s): 118
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  • IEEE copyright form

    Page(s): 119 - 120
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  • IEEE Systems, Man, and Cybernetics Society Information

    Page(s): c3
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  • IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews Information for authors

    Page(s): c4
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Aims & Scope

Overview, tutorial and application papers concerning all areas of interest to the SMC Society: systems engineering, human factors and human machine systems, and cybernetics and computational intelligence. 

This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Human-Machine Systems.

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Meet Our Editors

Editor-in-Chief
Dr. Vladimir Marik
(until 31 December 2012)