Learning about the opponent in automated bilateral negotiation: A comprehensive survey of opponent modeling techniques

A negotiation between agents is typically an incomplete information game, where the agents initially do not know their opponent’s preferences or strategy. This poses a challenge, as efficient and effective negotiation requires the bidding agent to take the other’s wishes and future behavior into account when deciding on a proposal. Therefore, in...

Mood contagion of robot body language in human robot interaction

The aim of our work is to design bodily mood expressions of humanoid robots for interactive settings that can be recognized by users and have (positive) effects on people who interact with the robots. To this end, we develop a parameterized behavior model for humanoid robots to express mood through body language. Different settings of the...

Active Affordance Learning in Continuous State and Action Spaces

Learning object affordances and manipulation skills is essential for developing cognitive service robots. We propose an active affordance learning approach in continuous state and action spaces without manual discretization of states or exploratory motor primitives. During exploration in the action space, the robot learns a forward model to...

Robot Mood is Contagious: Effects of Robot Body Language in the Imitation Game

Mood contagion is an automatic mechanism that induces a congruent mood state by means of the observation of another person's emotional expression. In this paper, we address the question whether robot mood displayed during an imitation game can (a) be recognized by participants and (b) produce contagion effects. Robot mood was displayed by...

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...

Accepting Optimally in Automated Negotiation with Incomplete Information (abstract)

A Framework for Qualitative Multi-Criteria Preferences (extended abstract)

Decoupling Negotiating Agents to Explore the Space of Negotiation Strategies (extended abstract)

GENIUS: An integrated environment for supporting the design of generic automated negotiators

The design of automated negotiators has been the focus of abundant research in recent years. However, due to difficulties involved in creating generalized agents that can negotiate in several domains and against human counterparts, many automated negotiators are domain specific and their behavior cannot be generalized for other domains. Some of...

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

Argumentation-based qualitative preference modelling with incomplete and uncertain information

This paper presents an argumentation-based framework for the modelling of, and automated reasoning about multi-attribute preferences of a qualitative nature. The framework presents preferences according to the lexicographic ordering that is well-understood by humans. Preferences are derived in part from knowledge. Knowledge, however, may be...

Towards an environment interface standard for agent platforms

We introduce an interface for connecting agent platforms to environments. This interface provides generic functionality for executing actions and for perceiving changes in an agent’s environment. It also provides support for managing an environment, e.g., for starting, pausing and terminating it. Among the benefits of such an interface are (1)...

Unreal Goal Bots

It remains a challenge with current state of the art technology to use BDI agents to control real-time, dynamic and complex environments. We report on our effort to connect the GOAL agent programming language to the real-time game UNREAL TOURNAMENT 2004. We focus in particular on the design of a suitable interface to manage agent-bot interaction...

Formalizing Organizational Constraints: A Semantic Approach (extended abstract)

Qualitative One-to-Many Multi-Issue Negotiation: Approximating the QVA

When there is one buyer interested in obtaining a service from one of a set of sellers, multi-attribute or multi-issue auctions can ensure an allocation that is efficient. Even when there is no transferable utility (e.g., money), a recent qualitative version of the Vickrey auction may be used, the QVA, to obtain a Pareto-efficient outcome where...

Reasoning About Multi-Attribute Preferences (extended abstract)

Exploring Heuristic Action Selection in Agent Programming (extended abstract)

Rational agents programmed in agent programming languages derive their choice of action from their beliefs and goals. One of the main benefits of such programming languages is that they facilitate a highlevel and conceptually elegant specification of agent behaviour. Qualitative concepts alone, however, are not sufficient to specify that this...

Opponent Modelling in Automated Multi-Issue Negotiation Using Bayesian Learning (extended abstract)

In this paper, we show that it is nonetheless possible to construct an opponent model, i.e. a model of the opponent’s preferences that can be effectively used to improve negotiation outcomes. We provide a generic framework for learning both the preferences associated with issue values as well as the weights that rank the importance of issues to...