3,907 research outputs found
The significance of bidding, accepting and opponent modeling in automated negotiation
Given the growing interest in automated negotiation, the search for effective strategies has produced a variety of different negotiation agents. Despite their diversity, there is a common structure to their design. A negotiation agent comprises three key components: the bidding strategy, the opponent model and the acceptance criteria. We show that this three-component view of a negotiating architecture not only provides a useful basis for developing such agents but also provides a useful analytical tool. By combining these components in varying ways, we are able to demonstrate the contribution of each component to the overall negotiation result, and thus determine the key contributing components. Moreover, we are able to study the interaction between components and present detailed interaction effects. Furthermore, we find that the bidding strategy in particular is of critical importance to the negotiator's success and far exceeds the importance of opponent preference modeling techniques. Our results contribute to the shaping of a research agenda for negotiating agent design by providing guidelines on how agent developers can spend their time most effectively
Tax aggressiveness and negotiations: A conceptual paper
Negotiation is a pervasive feature of relationships among auditor-clients, buyer-sellers, as well as being a part of tax audits.Various forms of negotiations occur between the taxpayer and the tax authorities but nothing is mentioned in the literatures on the processes and procedures of how both parties arrive at a settlement that is amicable to both parties.This study reviews the literature on how concession timing negotiation strategies adopted by the tax authorities and the tax practitionersâ
aggressiveness impact negotiation outcomes
Generating Pareto-Optimal Offers in Bilateral Automated Negotiation with One-Side Uncertain Importance Weights
Pareto efficiency is a seminal condition in the bargaining problem which leads autonomous agents to a Nash-equilibrium. This paper investigates the problem of the generating Pareto-optimal offers in bilateral multi-issues negotiation where an agent has incomplete information and the other one has perfect information. To this end, at first, the bilateral negotiation is modeled by split the pie game and alternating-offer protocol. Then, the properties of the Pareto-optimal offers are investigated. Finally, based on properties of the Pareto-optimal offers, an algorithmic solution for generating near-optimal offers with incomplete information is presented. The agent with incomplete information generates near-optimal offers in O(n Ćog n). The results indicate that, in the early rounds of the negotiation, the agent with incomplete information can generate near-optimal offers, but as time passes the agent can learn its opponents preferences and generate Pareto-optimal offers. The empirical analysis also indicates that the proposed algorithm outperform the smart random trade-offs (SRT) algorithm
Automated Service Negotiation Between Autonomous Computational Agents
PhDMulti-agent systems are a new computational approach for solving real world, dynamic and open system
problems. Problems are conceptualized as a collection of decentralised autonomous agents that collaborate
to reach the overall solution. Because of the agents autonomy, their limited rationality, and the distributed
nature of most real world problems, the key issue in multi-agent system research is how to model interactions
between agents. Negotiation models have emerged as suitable candidates to solve this interaction
problem due to their decentralised nature, emphasis on mutual selection of an action, and the prevalence of
negotiation in real social systems.
The central problem addressed in this thesis is the design and engineering of a negotiation model for
autonomous agents for sharing tasks and/or resources. To solve this problem a negotiation protocol and
a set of deliberation mechanisms are presented which together coordinate the actions of a multiple agent
system.
In more detail, the negotiation protocol constrains the action selection problem solving of the agents
through the use of normative rules of interaction. These rules temporally order, according to the agents'
roles, communication utterances by specifying both who can say what, as well as when. Specifically,
the presented protocol is a repeated, sequential model where offers are iteratively exchanged. Under this
protocol, agents are assumed to be fully committed to their utterances and utterances are private between
the two agents. The protocol is distributed, symmetric, supports bi and/or multi-agent negotiation as well
as distributive and integrative negotiation.
In addition to coordinating the agent interactions through normative rules, a set of mechanisms are presented
that coordinate the deliberation process of the agents during the ongoing negotiation. Whereas the
protocol normatively describes the orderings of actions, the mechanisms describe the possible set of agent
strategies in using the protocol. These strategies are captured by a negotiation architecture that is composed
of responsive and deliberative decision mechanisms. Decision making with the former mechanism is based
on a linear combination of simple functions called tactics, which manipulate the utility of deals. The latter
mechanisms are subdivided into trade-off and issue manipulation mechanisms. The trade-off mechanism
generates offers that manipulate the value, rather than the overall utility, of the offer. The issue manipulation mechanism aims to increase the likelihood of an agreement by adding and removing issues into the
negotiation set. When taken together, these mechanisms represent a continuum of possible decision making
capabilities: ranging from behaviours that exhibit greater awareness of environmental resources and less to
solution quality, to behaviours that attempt to acquire a given solution quality independently of the resource
consumption.
The protocol and mechanisms are empirically evaluated and have been applied to real world task
distribution problems in the domains of business process management and telecommunication management.
The main contribution and novelty of this research are: i) a domain independent computational model
of negotiation that agents can use to support a wide variety of decision making strategies, ii) an empirical
evaluation of the negotiation model for a given agent architecture in a number of different negotiation environments,
and iii) the application of the developed model to a number of target domains. An increased
strategy set is needed because the developed protocol is less restrictive and less constrained than the traditional
ones, thus supporting development of strategic interaction models that belong more to open systems.
Furthermore, because of the combination of the large number of environmental possibilities and the size of
the set of possible strategies, the model has been empirically investigated to evaluate the success of strategies
in different environments. These experiments have facilitated the development of general guidelines
that can be used by designers interested in developing strategic negotiating agents. The developed model
is grounded from the requirement considerations from both the business process management and telecommunication
application domains. It has also been successfully applied to five other real world scenarios
Computational intelligence based complex adaptive system-of-systems architecture evolution strategy
The dynamic planning for a system-of-systems (SoS) is a challenging endeavor. Large scale organizations and operations constantly face challenges to incorporate new systems and upgrade existing systems over a period of time under threats, constrained budget and uncertainty. It is therefore necessary for the program managers to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. Managers and engineers are always looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This research helps in analyzing sequential decisions in an evolving SoS architecture based on the wave model through three key features namely; meta-architecture generation, architecture assessment and architecture implementation. Meta-architectures are generated using evolutionary algorithms and assessed using type II fuzzy nets. The approach can accommodate diverse stakeholder views and convert them to key performance parameters (KPP) and use them for architecture assessment. On the other hand, it is not possible to implement such architecture without persuading the systems to participate into the meta-architecture. To address this issue a negotiation model is proposed which helps the SoS manger to adapt his strategy based on system owners behavior. This work helps in capturing the varied differences in the resources required by systems to prepare for participation. The viewpoints of multiple stakeholders are aggregated to assess the overall mission effectiveness of the overarching objective. An SAR SoS example problem illustrates application of the method. Also a dynamic programing approach can be used for generating meta-architectures based on the wave model. --Abstract, page iii
Human-Machine Cooperative Decision Making
Diese Dissertation beschĂ€ftigt sich mit der gemeinsamen Entscheidungsfindung in der Mensch-Maschine-Kooperation und liefert neue Erkenntnisse, welche von der theoretischen Modellierung bis zu experimentellen Untersuchungen reichen. ZunĂ€chst wird eine methodische Klassifikation bestehender Forschung zur Mensch-Maschine-Kooperation vorgenommen und der Forschungsfokus dieser Dissertation mithilfe eines vorgestellten Taxonomiemodells der Mensch-Maschine-Kooperation, dem Butterfly-Modell, abgegrenzt. Darauffolgend stellt die Dissertation zwei mathematische Verhaltensmodelle der gemeinsamen Entscheidungsfindung von Mensch und Maschine vor: das Adaptive Verhandlungsmodell und den n-stufigen War of Attrition. Beide modellieren den Einigungsprozess zweier emanzipierter Kooperationspartner und unterscheiden sich hinsichtlich ihrer UrsprĂŒnge, welche in der Verhandlungs- beziehungsweise Spieltheorie liegen. ZusĂ€tzlich wird eine Studie vorgestellt, die die Eignung der vorgeschlagenen mathematischen Modelle zur Beschreibung des menschlichen Nachgebeverhaltens in kooperativen Entscheidungsfindungs-Prozessen nachweist. Darauf aufbauend werden zwei modellbasierte Automationsdesigns bereitgestellt, welche die Entwicklung von Maschinen ermöglichen, die an einem Einigungsprozess mit einem Menschen teilnehmen können. Zuletzt werden zwei experimentelle Untersuchungen der vorgeschlagenen Automationsdesigns im Kontext von teleoperierten mobilen Robotern in Such- und Rettungsszenarien und anhand einer Anwendung in einem hochautomatisierten Fahrzeug prĂ€sentiert. Die experimentellen Ergebnisse liefern empirische Evidenz fĂŒr die Ăberlegenheit der vorgestellten modellbasierten Automationsdesigns gegenĂŒber den bisherigen AnsĂ€tzen in den Aspekten der objektiven kooperativen Performanz, des menschlichen Vertrauens in die Interaktion mit der Maschine und der Nutzerzufriedenheit. So zeigt diese Dissertation, dass Menschen eine emanzipierte Interaktion mit Bezug auf die Entscheidungsfindung bevorzugen, und leistet einen wertvollen Beitrag zur vollumfĂ€nglichen Betrachtung und Verwirklichung von Mensch-Maschine-Kooperationen
Human-Machine Cooperative Decision Making
The research reported in this thesis focuses on the decision making aspect of human-machine cooperation and reveals new insights from theoretical modeling to experimental evaluations: Two mathematical behavior models of two emancipated cooperation partners in a cooperative decision making process are introduced. The model-based automation designs are experimentally evaluated and thereby demonstrate their benefits compared to state-of-the-art approaches
The role of leadership in salespeopleâs price negotiation behavior
Salespeople assume a key role in defending firmsâ price levels in price negotiations with customers. The degree to which salespeople defend prices should critically depend upon their leadersâ influence. However, the influence of leadership on salespeopleâs price defense behavior is barely understood, conceptually or empirically. Therefore, building on social learning theory, the authors propose that salespeople might adopt their leadersâ price defense behavior given a transformational leadership style. Furthermore, drawing on the contingency leadership perspective, the authors argue that this adoption fundamentally depends on three variables deduced from the motivationâabilityâopportunity (MAO) framework, that is, salespeopleâs learning motivation, negotiation efficacy, and perceived customer lenience. Results of a multi-level model using data from 92 salespeople and 264 salespersonâcustomer interactions confirm these predictions. The first to explore contingencies of salespeopleâs adoption of their transformational leadersâ price negotiation behaviors, this study extends marketing theory and provides actionable guidance to practitioners
2. Talking it through: communication sequences in negotiation
If negotiation is like a dance The moves in negotiations are acts of communication. Negotiators communicate using oral and written messages, conveyed with various postures, facial expressions, rates of speech, and tones of voice, among other concerns In what follows, we first outline how scholars study the communication sequences that comprise the negotiation process. Then we examine findings on negotiation strategy and tactics, the primary emphasis of negotiation research on communication sequences. Next we examine findings on nonverbal communication. Finally, we consider lines of research that are opening up new kinds of sequences to explore
Human-Machine Cooperative Decision Making
The research reported in this thesis focuses on the decision making aspect of human-machine cooperation and reveals new insights from theoretical modeling to experimental evaluations: Two mathematical behavior models of two emancipated cooperation partners in a cooperative decision making process are introduced. The model-based automation designs are experimentally evaluated and thereby demonstrate their benefits compared to state-of-the-art approaches
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