An open architecture for emotion and behavior control of autonomous agents (poster)

Author(s):  
Juan D. Velásquez ◽  
Masahiro Fujita ◽  
Hiroaki Kitano

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Mais Haj Qasem ◽  
Amjad Hudaib ◽  
Nadim Obeid

A multiagent system (MAS) is a mechanism for creating goal-oriented autonomous agents in shared environments with communication and coordination facilities. Distributed data mining benefits from this goal-oriented mechanism by implementing various distributed clustering, classification, and prediction techniques. Hence, this study developed a novel multiagent model for distributed classification tasks in cancer detection with the collaboration of several hospitals worldwide using different classifier algorithms. A hospital agent requests help from other agents for instances that are difficult to classify locally. The agents communicate their beliefs (calculated classification), and others decide on the benefit of using such beliefs in classifying instances and adjusting their prior assumptions on each class of data. A MAS model state and behavior and communication are then developed to facilitate information sharing among agents. Regarding accuracy, implementing the proposed approach in comparison with typically different noncommunicated distributed classifications shows that sharable information considerably increases the classification task accuracy by 25.77%.



2014 ◽  
Vol 7 (12) ◽  
pp. 189-198 ◽  
Author(s):  
Yanmin Lei ◽  
Xiaoxue Xing ◽  
Zhibin Feng ◽  
Xiuli Guan ◽  
Du Limin


2007 ◽  
Vol 35 (4) ◽  
pp. 429-442 ◽  
Author(s):  
Seher Balci Çelik

Family function levels of fathers with children aged 0–6 in Samsun, Turkey were compared on the basis of length of marriage, level of education, family structure, and type of marriage. The sample consisted of 171 fathers aged between 24–36 (average age 29.2). The Family Assessment Device (Epstein, Baldwin, & Bishop, 1983) was used to measure family function levels of fathers and t-test and one way ANOVA were used to analyze the data. There was a significant difference in family function levels of the fathers, according to length of their marriage, in the subdimensions of problem solving, communication, affective involvement, behavior control and general functionings, according to their level of education. In all the subdimensions of affective involvement and behavior control, according to the family structures of fathers, significant differences were found between groups and total general points; according to fathers' types of marriage, a significant difference was found between the groups regarding problem solving, communication, affective involvement, behavior control and general total points.



1976 ◽  
Vol 6 (1) ◽  
pp. 23 ◽  
Author(s):  
Gerald Dworkin


2018 ◽  
Vol 6 (1) ◽  
pp. 26
Author(s):  
Cici Violita Dewi Cintya ◽  
Sri Widati

Smoking habit can be done by all circles and professions includes badminton athletes. The purpose of this study is to determine the effect of attitude, subjective norms, and behavior control about smoking habit to athletes on the UKM Bulutangkis of X University Surabaya. This research is analytic by using cross sectional research design using total population in UKM Bulutangkis University X Surabaya. Respondents fulfilled the inclusion criteria in this study amounted to 35 atlet. Data analysis used is logistic regression. The result showed that as many as 40% athletes have smoking habit. The result of regression test showed that attitudes factor (Odds Ratio = 36), subjective norms (Odds Ratio = 15.583), and behavior control (Odds Ratio=17.333) influence smoking habits to UKM Bulutangkis of X University Surabaya is athletes. The conclusion of the research is attitude factor, subjective norm, and behavior control have positive influence to smoking habit at athlete at badminton badminton University X Surabaya. Attitudinal factors are the most positive factor in smoking. Athletes who smoke should start to reduce smoking by avoid and refuse a friend or neighborhood stimulus to smoking. Athletes who do not smoke, still maintain the habit of not smoking by motivating themselves that smoking will harm health. UKM Bulutangkis Universitas X Surabaya, should advise athletes who smoke to reduce smoking and quit smoking habit.



2018 ◽  
Vol 68 ◽  
pp. 169-182 ◽  
Author(s):  
Vanessa Coelho-Santos ◽  
Filipa L. Cardoso ◽  
Ricardo A. Leitão ◽  
Carlos A. Fontes-Ribeiro ◽  
Ana Paula Silva


Philosophies ◽  
2021 ◽  
Vol 6 (4) ◽  
pp. 83
Author(s):  
Kristen Carlson

Methods are currently lacking to prove artificial general intelligence (AGI) safety. An AGI ‘hard takeoff’ is possible, in which first generation AGI1 rapidly triggers a succession of more powerful AGIn that differ dramatically in their computational capabilities (AGIn << AGIn+1). No proof exists that AGI will benefit humans or of a sound value-alignment method. Numerous paths toward human extinction or subjugation have been identified. We suggest that probabilistic proof methods are the fundamental paradigm for proving safety and value-alignment between disparately powerful autonomous agents. Interactive proof systems (IPS) describe mathematical communication protocols wherein a Verifier queries a computationally more powerful Prover and reduces the probability of the Prover deceiving the Verifier to any specified low probability (e.g., 2−100). IPS procedures can test AGI behavior control systems that incorporate hard-coded ethics or value-learning methods. Mapping the axioms and transformation rules of a behavior control system to a finite set of prime numbers allows validation of ‘safe’ behavior via IPS number-theoretic methods. Many other representations are needed for proving various AGI properties. Multi-prover IPS, program-checking IPS, and probabilistically checkable proofs further extend the paradigm. In toto, IPS provides a way to reduce AGIn ↔ AGIn+1 interaction hazards to an acceptably low level.



1982 ◽  
Vol 1 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Robert L. Arrington


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