By Byeong Ho Kang, Quan Bai
This publication constitutes the refereed complaints of the twenty ninth Australasian Joint convention on synthetic Intelligence, AI 2016, held in Hobart, TAS, Australia, in December 2016.
The forty complete papers and 18 brief papers offered including eight invited brief papers have been rigorously reviewed and chosen from 121 submissions. The papers are equipped in topical sections on brokers and multiagent structures; AI functions and options; mammoth information; constraint delight, seek and optimisation; wisdom illustration and reasoning; computing device studying and knowledge mining; social intelligence; and textual content mining and NLP.
The court cases additionally includes 2 contributions of the AI 2016 doctoral consortium and six contributions of the SMA 2016.
Read or Download AI 2016: Advances in Artificial Intelligence: 29th Australasian Joint Conference, Hobart, TAS, Australia, December 5-8, 2016, Proceedings PDF
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Extra info for AI 2016: Advances in Artificial Intelligence: 29th Australasian Joint Conference, Hobart, TAS, Australia, December 5-8, 2016, Proceedings
13–42. Princeton University Press, New Jersey (1959) 13. : Fluxplayer: a successful general game player. In: Proceedings of AAAI 2007, pp. 1191–1196. AAAI Press (2007) 14. : Creating action heuristics for general game playing agents. , Togelius, J. ) CGW/GIGA -2015. CCIS, vol. 614, pp. 149–164. Springer, Heidelberg (2016). 1007/978-3-319-39402-2 11 15. : A logic for reasoning about game strategies. In: Proceedings of the Twenty-Ninth AAAI Conference on Artiﬁcial Intelligence (AAAI-15), pp. 1671–1677 (2015) Corrupt Strategic Argumentation: The Ideal and the Naive Michael J.
In particular, O cannot simply “give up” and fail to make a move – such behaviour would open her to charges of incompetence or corruption. Instead, she must exhaust her possible moves. The Winning Sequence Problem for P Instance A split argumentation framework (ACom , AP , AO , outcome for P . Question Is there a sequence of moves such that P wins? ) and a desired This problem can be solved by a non-deterministic algorithm that guesses moves for P and O and uses oracles for the aim veriﬁcation problem for P and O and the (complement of) the desired outcome problem for O.
We say there a2 or a2 a1 . An is a conﬂict between arguments a1 and a2 if either a1 extension E is conﬂict-free if the restriction of to E is empty. The naive extensions are the maximal conﬂict-free extensions. The stage extensions are the conﬂict-free extensions that are maximal under the containment ordering of E ∪ E − . Alternatively, the stage extensions are the conﬂict-free extensions that minimize the set of undecided arguments. An argument a is defended by E if every argument that attacks a is attacked by some argument in E.
AI 2016: Advances in Artificial Intelligence: 29th Australasian Joint Conference, Hobart, TAS, Australia, December 5-8, 2016, Proceedings by Byeong Ho Kang, Quan Bai