Some AI researchers say that AI is always researching on things what computers cannot do. When computers learn to do something, it is omitted from AI. AI has done many things, but the things are not considered as results of AI research. We, AI researchers, have to claim that not only what we want to do but also what we have done.

Because impact and variety of disasters are so huge and wide, actions and systems for disaster response must be flexible. Local governments and helper companies in the great east Japan earthquake had to adapt their response plans according to unexpected situations. We report the results of hearing for them, and discuss technical issues on information systems for the disaster response actions.

In Disaster Simulation, multiple heterogeneous agents work together, forming a cooperative team, in a common environment to achieve a common goal. Researches related to agents' action in dynamic environment are still countable. As the expected results using dynamic environment may not be very certain/effective, the current Disaster Simulations are forced to use centralized system in which the central agent is handling the communication, cooperation and coordination activities of all other agents. In centralized system, if the central agent (that is controlling the whole system) fails then the whole system could crash. Also, if we cannot skip the effect of dynamic environmental conditions in centralized system, there could arise a question mark in the performance of the whole system. This paper focuses on such performance bottlenecks caused by centralized model introducing a decentralized model for cooperation. Change in the environment of the whole system is also being one of the main issues in current Disaster Simulation projects. We describe how the decentralized model could be the best solution for robustness of the performance of the Disaster Simulation and we also introduce an algorithm for decentralized cooperation model in dynamic environment.

This paper describes the issue of "AI (Agri-Informatics) Agriculture", a totally new approach in agricultural field of study which utilizes artificial intelligence knowledge. I am going to put together various challenges based on legal and social perspectives about intellectual property rights of newly-acquired methodology from data mining.