Preference Learning in Automated Negotiation Using Gaussian Uncertainty Models

In this paper, we propose a general two-objective Markov Decision Process (MDP) modeling paradigm for automated negotiation with incomplete information, in which preference elicitation alternates with negotiation actions, with the objective to optimize negotiation outcomes. The key ingredient in our MDP framework is a stochastic utility model governed by a Gaussian law, formalizing the agent's belief (uncertainty) over the user's preferences. Our belief model is fairly general and can be updated in real time as new data becomes available, which makes it a fundamental modeling tool

Automated negotiation with Gaussian process-based utility models

Designing agents that can efficiently learn and integrate user's preferences into decision making processes is a key challenge in automated negotiation. While accurate knowledge of user preferences is highly desirable, eliciting the necessary information might be rather costly, since frequent user interactions may cause inconvenience. Therefore, efficient elicitation strategies (minimizing elicitation costs) for inferring relevant information are critical. We introduce a stochastic, inverse-ranking utility model compatible with the Gaussian Process preference learning framework and integrate it into a (belief) Markov Decision Process paradigm which formalizes automated negotiation processes with incomplete information. Our utility model, which naturally maps ordinal preferences (inferred from the user) into (random) utility values (with the randomness reflecting the underlying uncertainty), provides the basic quantitative modeling ingredient for automated (agent-based) negotiation

SOLACE: A framework for electronic negotiations

Copyright @ 2011 Walter de Gruyter GmbHMost existing frameworks for electronic negotiations today are tied to specific negotiation systems for which they were developed, preventing them from being applied to other negotiation scenarios. Thus, the evaluation of electronic negotiation systems is difficult as each one is based on a different framework. Additionally, each developer has to design a new framework for any system to be developed, leading to a ‘reinvention of the wheel’. This paper presents SOLACE—a generic framework for multi-issue negotiations, which can be applied to a variety of negotiation scenarios. In contrast with other frameworks for electronic negotiations, SOLACE supports hybrid systems in which the negotiation participants can be humans, agents or a combination of the two. By recognizing the importance of strategies in negotiations and incorporating a time attribute in negotiation proposals, SOLACE enhances existing approaches and provides a foundation for the flexible electronic negotiation systems of the future

Enabling Machine Understandable Exchange of Energy Consumption Information in Intelligent Domotic Environments

In the 21st century, all the major countries around the world are coming together to reduce the impact of energy generation and consumption on the global environment. Energy conservation and its efficient usage has become a top agenda on the desks of many governments. In the last decade, the drive to make homes automated and to deliver a better assisted living picked pace and the research into home automation systems accelerated, usually based on a centralized residential gateway. However most devised solutions fail to provide users with information about power consumption of different house appliances. The ability to collect power consumption information can lead us to have a more energy efficient society. The goal addressed in this paper is to enable residential gateways to provide the energy consumption information, in a machine understandable format, to support third party applications and services. To reach this goal, we propose a Semantic Energy Information Publishing Framework. The proposed framework publishes, for different appliances in the house, their power consumption information and other properties, in a machine understandable format. Appliance properties are exposed according to the existing semantic modeling supported by residential gateways, while instantaneous power consumption is modeled through a new modular Energy Profile ontolog

An Investigation of the Negotiation Domain for Electronic Commerce Information Systems

To support fully automatic business cycles, information systems for electronic commerce need to be able to conduct negotiation automatically. In recent years, a number of general frameworks for automated negotiation have been proposed. Application of such frameworks in a specific negotiation situation entails selecting the proper framework and adapting it to this situation. This selection and adaptation process is driven by the specific characteristics of the situation. This paper presents a systematic investigation of there characteristics and surveys a number of frameworks for automated negotiation

Human-Agent Decision-making: Combining Theory and Practice

Extensive work has been conducted both in game theory and logic to model strategic interaction. An important question is whether we can use these theories to design agents for interacting with people? On the one hand, they provide a formal design specification for agent strategies. On the other hand, people do not necessarily adhere to playing in accordance with these strategies, and their behavior is affected by a multitude of social and psychological factors. In this paper we will consider the question of whether strategies implied by theories of strategic behavior can be used by automated agents that interact proficiently with people. We will focus on automated agents that we built that need to interact with people in two negotiation settings: bargaining and deliberation. For bargaining we will study game-theory based equilibrium agents and for argumentation we will discuss logic-based argumentation theory. We will also consider security games and persuasion games and will discuss the benefits of using equilibrium based agents.Comment: In Proceedings TARK 2015, arXiv:1606.0729

Formally based semi-automatic implementation of an open security protocol

International audienceThis paper presents an experiment in which an implementation of the client side of the SSH Transport Layer Protocol (SSH-TLP) was semi-automatically derived according to a model-driven development paradigm that leverages formal methods in order to obtain high correctness assurance. The approach used in the experiment starts with the formalization of the protocol at an abstract level. This model is then formally proved to fulfill the desired secrecy and authentication properties by using the ProVerif prover. Finally, a sound Java implementation is semi-automatically derived from the verified model using an enhanced version of the Spi2Java framework. The resulting implementation correctly interoperates with third party servers, and its execution time is comparable with that of other manually developed Java SSH-TLP client implementations. This case study demonstrates that the adopted model-driven approach is viable even for a real security protocol, despite the complexity of the models needed in order to achieve an interoperable implementation