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In order to help agents in a difficult situation, we integrate the human in the agent's decision process. We develop a new model called Human Help Provider in a Markov Decision Process (HHP-MDP). We define HHP-MDP as a middle ground between an autonomous agent and a teleoperated agent called adjustable autonomy. The global approach of HHP-MDP is based on(More)
Multi-Objective Multiagent Planning (MOMAP) addresses the problem of resolving conflicts between individual agent interests and the group interests. In this paper, we address this problem by presenting a formal framework to represent objective relationships, a decision model using a Vector-Valued Decentralized Markov Decision Process (2V-DEC-MDP) and an(More)
The ability to automatically answer a request that requires the composition of a set of web services has received much interest in the last decade, as it supports B2B applications. Planning techniques are used widely in the literature to describe the web services composition problem but they don’t scale up well. This weakness is due to the search(More)
Automated composition of Web services has received much interest in the last decade, as it supports B2B applications. It aims at selecting and inter-connecting services provided by different partners in response to client requests. Planning techniques are used widely in the literature to describe Web services composition problem. However, since Web services(More)
Autonomous agents dealing with partial knowledge about the environment are a classical subject of study for the decision making community. Moreover, such agents sometimes have to deal with unpredictable situations, which makes any previously computed behavior useless. In this paper, we address such problems using multi-human/multi-robot interactions, where(More)