scholarly journals Fractal Analysis of Stealthy Pathfinding Aesthetics

2009 ◽  
Vol 2009 ◽  
pp. 1-7 ◽  
Author(s):  
Ron Coleman
Keyword(s):  
Artificial Intelligence ◽  
Statistical Analysis ◽  
Virtual Worlds ◽  
Fractal Analysis ◽  
Fractal Model ◽  
Aesthetic Value ◽  
New Class ◽  
Experimental Trials ◽  
Aesthetic Values

This paper uses a fractal model to analyze aesthetic values of a new class of obstacle-prone or “stealthy” pathfinding which seeks to avoid detection, exposure, openness, and so forth in videogames. This study is important since in general the artificial intelligence literature has given relatively little attention to aesthetic outcomes in pathfinding. The data we report, according to the fractal model, suggests that stealthy paths are statistically significantly unique in relative aesthetic value when compared to control paths. We show furthermore that paths generated with different stealth regimes are also statistically significantly unique. These conclusions are supported by statistical analysis of model results on experimental trials involving pathfinding in randomly generated, multiroom virtual worlds.

Hundred Mile Aesthetics

2018 ◽  
Author(s):  
Dominic McIver Lopes
Keyword(s):  
Network Theory ◽  
Main Argument ◽  
Aesthetic Value ◽  
Psychological Traits ◽  
Aesthetic Practice ◽  
Almost All ◽  
Aesthetic Values

The main argument for the network theory of aesthetic value is that it better explains the facts about aesthetic activity than aesthetic hedonism. According to the network theory, an aesthetic value figures in a fact that lends weight to the proposition that it would be an aesthetic achievement for an agent to act in the context of an aesthetic practice. Each aesthetic practice has its own aesthetic profile, in which determinate aesthetic values are distinctively realized, and each has core aesthetic norms centred on its distinctive aesthetic profile. An account is given of the valence of aesthetic values. The theory explains why aesthetic experts disperse into almost all demographic niches, why they jointly inhabit the whole aesthetic universe, why they specialize by aesthetic domain, why they specialize by type of activity, why they specialize by activity and domain interacts, and why their expertise is rooted in relatively stable psychological traits.

Getting Practical

2018 ◽  
Author(s):  
Dominic McIver Lopes
Keyword(s):  
Network Theory ◽  
Mental Representations ◽  
Practical Reasons ◽  
Main Argument ◽  
Aesthetic Appreciation ◽  
Aesthetic Value ◽  
Aesthetic Property ◽  
Aesthetic Values ◽  
Aesthetic Reason

While the main argument for the network theory of aesthetic value is that it better explains the facts about aesthetic activity than does aesthetic hedonism, the two theories share some common assumptions. Aesthetic evaluations are mental representations that attribute aesthetic values to items. Aesthetic acts are acts based on aesthetic evaluations. Aesthetic values figure in aesthetic reasons, which are practical reasons. That is, an aesthetic reason lends weight to the proposition that an agent should perform some act—an act of aesthetic appreciation, for example. Hence, one task for a theory of aesthetic value is to state what makes some values aesthetic. A second is to state what makes it the case that an aesthetic property figures in a reason that lends weight to what an agent should do. Aesthetic hedonism and the network theory offer only to explain the practical normativity of aesthetic value.

scholarly journals Using virtual reality to estimate aesthetic values of coral reefs

2018 ◽  
Vol 5 (4) ◽  
pp. 172226 ◽  
Author(s):  
Julie Vercelloni ◽  
Sam Clifford ◽  
M. Julian Caley ◽  
Alan R. Pearse ◽  
Ross Brown ◽  
...  
Keyword(s):  
Coral Reef ◽  
Coral Reefs ◽  
Structural Complexity ◽  
Natural Environments ◽  
Natural Ecosystems ◽  
Aesthetic Value ◽  
Natural Systems ◽  
Holistic Conservation ◽  
Past Experiences ◽  
Aesthetic Values

Aesthetic value, or beauty, is important to the relationship between humans and natural environments and is, therefore, a fundamental socio-economic attribute of conservation alongside other ecosystem services. However, beauty is difficult to quantify and is not estimated well using traditional approaches to monitoring coral-reef aesthetics. To improve the estimation of ecosystem aesthetic values, we developed and implemented a novel framework used to quantify features of coral-reef aesthetics based on people's perceptions of beauty. Three observer groups with different experience to reef environments (Marine Scientist, Experienced Diver and Citizen) were virtually immersed in Australian's Great Barrier Reef (GBR) using 360° images. Perceptions of beauty and observations were used to assess the importance of eight potential attributes of reef-aesthetic value. Among these, heterogeneity, defined by structural complexity and colour diversity, was positively associated with coral-reef-aesthetic values. There were no group-level differences in the way the observer groups perceived reef aesthetics suggesting that past experiences with coral reefs do not necessarily influence the perception of beauty by the observer. The framework developed here provides a generic tool to help identify indicators of aesthetic value applicable to a wide variety of natural systems. The ability to estimate aesthetic values robustly adds an important dimension to the holistic conservation of the GBR, coral reefs worldwide and other natural ecosystems.

Believable and Effective AI Agents in Virtual Worlds

2012 ◽  
Vol 4 (2) ◽  
pp. 37-59 ◽  
Author(s):  
Iskander Umarov ◽  
Maxim Mozgovoy
Keyword(s):  
Artificial Intelligence ◽  
Video Games ◽  
Virtual Worlds ◽  
Rapid Development ◽  
Virtual Agents ◽  
High Ability ◽  
Topic Area ◽  
Human Likeness ◽  
New Challenges ◽  
The Creation

The rapid development of complex virtual worlds (most notably, in 3D computer and video games) introduces new challenges for the creation of virtual agents, controlled by artificial intelligence (AI) systems. Two important subproblems in this topic area which need to be addressed are (a) believability and (b) effectiveness of agents’ behavior, i.e., human-likeness of the characters and high ability to achieving their own goals. In this paper, the authors study current approaches to believability and effectiveness of AI behavior in virtual worlds. They examine the concepts of believability and effectiveness, and analyze several successful attempts to address these challenges.

scholarly journals Coupling Discriminating Statistical Analysis and Artificial Intelligence for Geotechnical Characterization of the Kampemba’s Municipality Soils (Lubumbashi, DR Congo)

Geomaterials ◽  
2020 ◽  
Vol 10 (03) ◽  
pp. 35-55
Author(s):  
Kavula Ngoy Elysée ◽  
Kasongo wa Mutombo Portance ◽  
Libasse Sow ◽  
Ngoy Biyukaleza Bilez ◽  
Kavula Mwenze Corneille ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Statistical Analysis ◽  
Dr Congo ◽  
Geotechnical Characterization

scholarly journals Hybrid Neuro-Fractal Analysis of ECG Signals to Predict Ischemia

2021 ◽  
Author(s):  
Hedieh Montazeri
Keyword(s):  
Neural Network ◽  
Logistic Regression ◽  
Statistical Analysis ◽  
Linear Regression ◽  
Fractal Analysis ◽  
Prediction Accuracy ◽  
Clinical Characteristics ◽  
Hybrid Approach ◽  
Binary Logistic Regression ◽  
Ecg Signals

In this thesis, we propose and implement a new hybrid approach using fractal analysis, statistical analysis and neural network computation to build a model for prediction the number of ischemia occurrence based on ECG recordings. The main advantage of the proposed approach over similar earlier related works is that first useful parameters from fractal analysis of the signal are extracted to build a model that includes both clinical characteristics and signal attributes. Statistical analysis such as binary logistic regression and multivariate linear regression are then used to further explore the relation of parameters in order to obtain a more accurate model. We show that the results compare well with those of earlier work and clearly indicate that the augmentation of the above mentioned approaches improves the prediction accuracy.

Predictive Analysis for Digital Marketing Using Big Data

2017 ◽  
pp. 259-283
Author(s):  
Balamurugan Balusamy ◽  
Priya Jha ◽  
Tamizh Arasi ◽  
Malathi Velu
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Big Data ◽  
Statistical Analysis ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Predictive Analysis ◽  
Cognitive Computing ◽  
Internet Resources ◽  
To Come

Big data analytics in recent years had developed lightning fast applications that deal with predictive analysis of huge volumes of data in domains of finance, health, weather, travel, marketing and more. Business analysts take their decisions using the statistical analysis of the available data pulled in from social media, user surveys, blogs and internet resources. Customer sentiment has to be taken into account for designing, launching and pricing a product to be inducted into the market and the emotions of the consumers changes and is influenced by several tangible and intangible factors. The possibility of using Big data analytics to present data in a quickly viewable format giving different perspectives of the same data is appreciated in the field of finance and health, where the advent of decision support system is possible in all aspects of their working. Cognitive computing and artificial intelligence are making big data analytical algorithms to think more on their own, leading to come out with Big data agents with their own functionalities.

The Use of Artificial Intelligence Systems for Support of Medical Decision-Making

2011 ◽  
pp. 1017-1029
Author(s):  
William Claster ◽  
Nader Ghotbi ◽  
Subana Shanmuganathan
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Statistical Analysis ◽  
Medical Records ◽  
Clinical Decision Making ◽  
Ct Scanning ◽  
Clinical Decision ◽  
Radiology Department ◽  
Self Organizing Map ◽  
One Year

There is a treasure trove of hidden information in the textual and narrative data of medical records that can be deciphered by text-mining techniques. The information provided by these methods can provide a basis for medical artificial intelligence and help support or improve clinical decision making by medical doctors. In this paper we extend previous work in an effort to extract meaningful information from free text medical records. We discuss a methodology for the analysis of medical records using some statistical analysis and the Kohonen Self-Organizing Map (SOM). The medical data derive from about 700 pediatric patients’ radiology department records where CT (Computed Tomography) scanning was used as part of a diagnostic exploration. The patients underwent CT scanning (single and multiple) throughout a one-year period in 2004 at the Nagasaki University Medical Hospital. Our approach led to a model based on SOM clusters and statistical analysis which may suggest a strategy for limiting CT scan requests. This is important because radiation at levels ordinarily used for CT scanning may pose significant health risks especially to children.

scholarly journals The Impact of Awareness of New Artificial Intelligence Technologies on Policy Governance on Risk

2020 ◽  
Vol 11 (2) ◽  
pp. 152
Author(s):  
Do-Hyung Yee ◽  
Yen-Yoo You
Keyword(s):  
Artificial Intelligence ◽  
Statistical Analysis ◽  
Analysis Data ◽  
Risk Awareness ◽  
National Security Agency ◽  
Policy Governance ◽  
Risk Manager ◽  
The Impact ◽  
Positive Effect ◽  
Descriptive Statistical Analysis

Background/Objectives: This study examined the risks of new AI technologies and their impact on policy governance. Artificial intelligence is bringing about changes in various fields such as politics, economy and culture through information society and technology. In particular, it has a positive effect on solving various problems of existing society and overcoming limitations. But this advancement in artificial intelligence can create the opposite problem as expected. This appears to be a risk. We identify the factors that recognize this risk and investigate the possible impact on government governance.Methods/Statistical analysis: The questionnaire and data of this journal were analyzed by Korean public portal data, and the analysis data were designated by the Korea Information Technology Agency, AI related company, AI association, Ministry of Science, ICT and Future Planning, IT society, government research institute, Korea Communications Commission, and National Security Agency The questionnaire survey was based on AI experts working in the field.The analysis program uses IBM SPSS Statistics 22. The analysis methods are descriptive statistical analysis, reliability analysis and exploratory factor analysis.Findings: This study examined the risks of new AI technologies and their impact on policy governance. The survey was conducted to clarify comments on awareness of new AI-related technologies, awareness of AI risks, and improvements to AI-related policies.AI risk has become an integral part of regulation and the government's role as a risk manager is important.Improvements/Applications: Further discussion is needed regarding the commercialization effects of AI technology awareness, benefit items and timing items on policy governance through risk awareness.

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