By Tomoyuki Yamada (auth.), Katsumi Inoue, Ken Satoh, Francesca Toni (eds.)

This ebook constitutes the completely refereed post-proceedings of the seventh foreign Workshop on Computational good judgment for Multi-Agent structures, CLIMA VII, held in Hakodate, Japan, in may well 2006. It used to be an linked occasion of AAMAS 2006, the most overseas convention on self sufficient brokers and multi-agent platforms. The sequence of workshops provides present paintings on program of normal and declarative theories grounded on computational common sense to multi-agent platforms specification, semantics and techniques, and confronts principles comparable to autonomy, deliberation, wisdom, dedication, openness, belief, with the computational good judgment paradigms.

The 14 revised complete technical papers and 4 contest papers have been rigorously chosen from 29 submissions and went via rounds of reviewing and development. the subjects of the typical papers contain agent reasoning, comparable to deontic reasoning, probabilistic reasoning, contextual reasoning, choice making and abduction, agent conversation, corresponding to argumentation and discussion, agent structure and verification of multi-agent platforms. the competition papers describe carried out agent architectures fixing the gold mining domain.

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**Example text**

Minerva does not restrict itself to modeling the beliefs of agents, but allows for full BDI-agents that can plan towards a certain goal. It would be interesting to see if this can also be incorporated in HAS . The complexity of the language used for representing the knowledge is similar. MDLP can be translated to extended logic programs. The procedure given [13] for DLP can easily be extended to MDLP. It is the failure feedback between agents that gives HAS its expressive power, not the expressiveness of the representation language.

This makes sense in the context of hierarchical agents. , as an employee, one should reschedule previously arranged meetings if one’s boss cannot make it on the agreed time. The person with the least power to make changes should concede. Example 2. Take AL = {hypoglycemia, diabetes, sugar, coke, diet coke} and consider the following diabetes agent A. sugar ← hypoglycemia diet coke ← ¬sugar ¬sugar ← diabetes coke ← sugar Intuitively, the above agent is set up to use information from a doctor agent concerning hypoglycemia and diabetes to decide if a patient needs to have diet coke or normal coke.

Obviously, the above construction can be done in polynomial time. Intuitively, the hierarchical agent A1 has agent answer sets for every possible combination of the Xi ’s and if such a combination makes G valid, then the corresponding agent answer set also contains the atom sat. e. for a given input combination over the Xj ’s making G satisfied, the hierarchical agent P∀i will try to find a combination, keeping the Xj ’s with j < i fixed, making G false. e. for a given combination making G false it will try to compute a combination, keeping the Xj ’s with j < i fixed, making G satisfied.