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This ebook constitutes the refereed court cases of the second one foreign Workshop on self sufficient clever platforms: brokers and information Mining, AIS-ADM 2007, held in St. Petersburg, Russia in June 2007.

The 17 revised complete papers and six revised brief papers offered including four invited lectures have been conscientiously reviewed and chosen from 39 submissions. The papers are geared up in topical sections on agent and information mining, agent pageant and information mining, in addition to textual content mining, semantic internet, and agents.

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Extra info for Autonomous Intelligent Systems: Multi-Agents and Data Mining: Second International Workshop, AIS-ADM 2007, St. Petersburg, Russia, June 3-5, 2007, Proceedings

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Otherwise L and the nodes at level H make up the probable agreements Q at the end of the second phase. In the third phase, agents reach the final Pareto optimal solution by exchanging offers from Q. Agents take turn in making offers from Q, and the recipient removes agreements from Q that are dominated by the received offer. When Q cannot be reduced further, an agreement is picked randomly from it. Our goal was to develop protocols that lead rational agents to Pareto optimal agreements and to increase fairness as much as possible.

It is difficult to reach optimal outcomes in bilateral or multi-lateral negotiations over multiple resources when the agents’ preferences for the resources are not common knowledge. Self-interested agents often end up negotiating inefficient agreements in such situations. We have developed a 38 S. Sen et al. protocol for negotiation over multiple indivisible resources which can be used by rational agents to reach efficient outcomes [13]. Our proposed protocol enables the negotiating agents to identify efficient solutions using systematic distributed search that visits only a subspace of the whole solution space.

What this implies is that societal relations and interactions are important and essential in our lives. Various modalities and temporal horizons of social interactions enrich our life and supports our material and spiritual pursuits. As agent researchers, we envision autonomous, intelligent agents as augmentations of our natural selves that can relieve us of some of our chores and responsibilities. While some of these tasks can be achieved individually, without input from others, a significant proportion of such tasks would require our agents to interact with agents of our peers or other members of our society.

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