Get PRICAI 2014: Trends in Artificial Intelligence: 13th Pacific PDF

Get PRICAI 2014: Trends in Artificial Intelligence: 13th Pacific PDF

By Duc-Nghia Pham, Seong-Bae Park

This publication constitutes the refereed court cases of the thirteenth Pacific Rim convention on man made Intelligence, PRICAI 2014, held in Gold Coast, Queensland, Australia, in December 2014. The seventy four complete papers and 20 brief papers provided during this quantity have been rigorously reviewed and chosen from 203 submissions. the subjects comprise inference; reasoning; robotics; social intelligence. AI foundations; functions of AI; brokers; Bayesian networks; neural networks; Markov networks; bioinformatics; cognitive platforms; constraint pride; facts mining and information discovery; determination concept; evolutionary computation; video games and interactive leisure; heuristics; wisdom acquisition and ontology; wisdom illustration, computer studying; multimodal interplay; common language processing; making plans and scheduling; probabilistic.

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Read or Download PRICAI 2014: Trends in Artificial Intelligence: 13th Pacific Rim International Conference on Artificial Intelligence, Gold Coast, QLD, Australia, December 1-5, 2014. Proceedings PDF

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Extra info for PRICAI 2014: Trends in Artificial Intelligence: 13th Pacific Rim International Conference on Artificial Intelligence, Gold Coast, QLD, Australia, December 1-5, 2014. Proceedings

Example text

We showed that the same is true for $FLTL. Finding both $FLTL and PLTL wanting of expressive power, we have developed a forward looking logic $∗ F LT L which is able to describe behaviours that correspond to regular languages. The formulae we used to define $∗ F LT L will give reward engineers much more flexibility in compactly expressing rich reward signals in decision-theoretic planning. In closing, we note that $∗ F LT L is by no means the first linear temporal logic with the power to describe any regular language.

Detailedly, follower number is the number of a user’s followers, retweeted number is the number of retweet action for a user’s micro-blogs, and mentioned number is the how many times a user has been mentioned in others’ micro-blogs. Different from [6], we consider those three factores together to get a user’s influence, of which the formula is given below: A(u) = α N F (u) N R (u ) N M (u) +β +γ ,(α + β + γ = 1) Max ( N F ) Max ( N R ) Max( N M ) (2) where A(u ) means the influence of user u , and N F (u ) is the number of the followers of u , and Max ( N F ) is the largest N F (u ) of all the users.

Thus, we cannot get a counting language from disjunction. In the case f U m where m is propositional, we have Bf U m ≡ (L )∗ ◦ (Bf ∩ (L )∗ ) where L = {s|s |=B m} for any B. Thus U does not give us a counting language. 7 $∗ F LT L: A More Expressive LTL for Planning We are thus motivated to enhance $FLTL to obtain a logic equal in expressive power to regular expressions. We only enhance the forward looking language because our primary interest lies in online search-based planning procedures, a setting that is ill-suited to PLTL approaches.

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