Met machines meer mens: samen sterk in onderhandelen

Electrical Engineering, Mathematics and Computer Scienc

Special Issue on ‘Human Factors and Computational Models in Negotiation'

Intelligent SystemsElectrical Engineering, Mathematics and Computer Scienc

Filtering Algorithm for Agent-Based Incident Communication Support in Mobile Human Surveillance (extended abstract)

Intelligent SystemsElectrical Engineering, Mathematics and Computer Scienc

A Survey of Decision Support Mechanisms for Negotiation

This paper introduces a dependency analysis and a categorization of conceptualized and existing economic decision support mechanisms for negotiation. The focus of our survey is on economic decision support mechanisms, although some behavioural support mechanisms were included, to recognize the important work in that area. We categorize support mechanisms from four different aspects: (i) economic versus behavioral decision support, (ii) analytical versus strategical support, (iii) active versus passive support and (iv) implicit versus explicit support. Our survey suggests that active mechanisms would be more effective than passive ones, and that implicit mechanisms can shield the user from mathematical complexities. Furthermore, we provide a list of existing economic support mechanisms.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Interactive Intelligenc

Deniz: A Robust Bidding Strategy for Negotiation Support Systems

This paper presents the Deniz agent that has been specifically designed to support human negotiators in their bidding. The design of Deniz is done with the criteria of robustness and the availability of small data, due to a small number of negotiation rounds in mind. Deniz’s bidding strategy is based on an existing optimal concession strategy that concedes in relation to the expected duration of the negotiation. This accounts for the small data and small number of rounds. Deniz deploys an adaptive behavior-based mechanism to make it robust against exploitation. We tested Deniz against typical bidding strategies and against human negotiators. Our evaluation shows that Deniz is robust against exploitation and gains statistically significant higher utilities than human test subjects, even though it is not designed specifically to get the highest utility against humans.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Interactive Intelligenc

Nooit meer leren

Waarom zou je nog iets leren, dankzij internet kunnen we alles wat we willen weten toch razendsnel opzoeken? Feitjes wel, maar voor de context heb je voorlopig toch echt je eigen hersens nodig, zeggen professor Catholijn Jonker en dr. Pascal WiggersMediamaticsElectrical Engineering, Mathematics and Computer Scienc

Bidding Support by the Pocket Negotiator Improves Negotiation Outcomes

This paper presents the negotiation support mechanisms provided by the Pocket Negotiator (PN) and an elaborate empirical evaluation of the economic decision support (EDS) mechanisms during the bidding phase of negotiations as provided by the PN. Some of these support mechanisms are offered actively, some passively. With passive support we mean that the user only gets that support by clicking a button, whereas active support is provided without prompting. Our results show, that PN improves negotiation outcomes, counters cognitive depletion, and encourages exploration of potential outcomes. We found that the active mechanisms were used more effectively than the passive ones and, overall, the various mechanisms were not used optimally, which opens up new avenues for research. As expected, the participants with higher negotiation skills outperformed the other groups, but still they benefited from PN support. Our experimental results show that people with enough technical skills and with some basic negotiation knowledge will benefit most from PN support. Our results also show that the cognitive depletion effect is reduced by Pocket Negotiator support. The questionnaire taken after the experiment shows that overall the participants found Pocket Negotiator easy to interact with, that it made them negotiate more quickly and that it improves their outcome. Based on our findings, we recommend to 1) provide active support mechanisms (push) to nudge users to be more effective, and 2) provide support mechanisms that shield the user from mathematical complexities.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work publicInteractive Intelligenc

Multilateral Mediated Negotiation Protocols with Feedback (abstract)

Much attention has been paid to bilateral negotiation in which the dispute is between only two parties. However, automated multilateral negotiation in which more than two negotiating parties need to reach a joint agreement, has received relatively less attention, even though such negotiations are required in many circumstances (e.g. a group of managers making a joint decision for their company investments, a group of friends planning their holiday together). In such cases, automated negotiation tools can play a key role in providing effective solutions. One of the important issues in designing such negotiation tools, is to decide on the protocol that governs the interaction between parties and determines when the final agreement will be reached. In this paper, we focus on and investigate different mediator-based protocols for multilateral negotiations. We take [3] as a starting point and propose a variant of this protocol.Intelligent SystemsElectrical Engineering, Mathematics and Computer Scienc

When do rule changes count-as legal rule changes?

Institutions regulate societies. Comprising Searle's constitutive counts-as rules, "A counts-as B in context C", an institution ascribes from brute and institutional facts (As), a social reality comprising institutional facts (Bs) conditional on the social reality (contexts Cs). When brute facts change an institution evolves from one social reality to the next. Rule changes are also regulated by rule-modifying counts-as rules ascribing rule change in the past/present/future (e.g. a majority rule change vote counts-as a rule change). Determining rule change legality is difficult, since changing counts-as rules both alters and is conditional on the social reality, and in some cases hypothetical rule-change effects (e.g. not retroactively criminalising people). However, without a rigorous account of rule change ascriptions, AI agents cannot support humans in understanding the laws imposed on them. Moreover, advances in automated governance design for socio-technical systems, are limited by agents' ability to understand how and when to enact institutional changes. Consequently, we answer "when do rule changes count-as legal rule changes?" in a temporal setting with a novel formal framework.AerodynamicsInformation and Communication TechnologyInteractive Intelligenc

An argumentation framework for qualitative multi-criteria preferences

Preferences are derived in part from knowledge. Knowledge, however, may be defeasible. We present an argumentation framework for deriving qualitative, multi-attribute preferences and incorporate defeasible reasoning about knowledge. Intuitively, preferences based on defeasible conclusions are not as strong as preferences based on certain conclusions, since defeasible conclusions may turn out not to hold. This introduces risk when such knowledge is used in practical reasoning. Typically, a risk prone attitude will result in different preferences than a risk averse attitude. In this paper we introduce qualitative strategies for deriving risk sensitive preferencesMediamaticsElectrical Engineering, Mathematics and Computer Scienc