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a r t i c l e i n f o a b s t r a c t This paper presents an in-depth analysis and the key insights gained from the Second International Automated Negotiating Agents Competition (ANAC 2011). ANAC is an international competition that challenges researchers to develop successful automated negotiation agents for scenarios where there is no information about(More)
The efficiency of automated multi-issue negotiation depends on the availability and quality of knowledge about an opponent. We present a generic framework based on Bayesian learning to learn an opponent model, i.e. the issue preferences as well as the issue priorities of an opponent. The algorithm proposed is able to effectively learn opponent preferences(More)
Motivated by the challenges of bilateral negotiations between people and automated agents we organized the first automated negotiating agents competition (ANAC 2010). The purpose of the competition is to facilitate the research in the area bilateral multi-issue closed negotiation. The competition was based on the GENIUS environment, which is a General(More)
A long and lasting problem in agent research has been to close the gap between agent logics and agent programming frameworks. The main reason for this problem of establishing a link between agent logics and agent programming frameworks is identified and explained by the fact that agent programming frameworks have not incorporated the concept of a(More)
The Goal agent programming language is a programming language for programming multi-agent systems. It offers a rich set of language elements and features for writing agent programs. The Goal platform is distributed with a diverse set of environments for which agents can be programmed. These environments include among others the classic Blocks World(More)
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 these(More)
A rational agent derives its choice of action from its beliefs and goals. Goals can be distinguished into achievement goals and maintenance goals. The aim of this paper is to define a mechanism which ensures the satisfaction of maintenance goals. We argue that such a mechanism requires the agent to look ahead, in order to make sure that the execution of(More)