Playing Smart - Artificial Intelligence in Computer Games

Abstract: With this document we will present an overview of artificial intelligence in general and artificial intelligence in the context of its use in modern computer games in particular. To this end we will firstly provide an introduction to the terminology of artificial intelligence, followed by a brief history of this field of computer science and finally we will discuss the impact which this science has had on the development of computer games. This will be further illustrated by a number of case studies, looking at how artificially intelligent behaviour has been achieved in selected games

CS 156: Introduction to Artificial Intelligence Course Redesign

Poster summarizing course redesign activities for CS 156: Introduction to Artificial Intelligence.https://scholarworks.sjsu.edu/davinci_itcr2014/1016/thumbnail.jp

Introduction to Artificial Intelligence

Artificial intelligence (AI) has been a topic of high interest in this day and age. AI has emerged through the early nineties and continues to grow at an unprecedented rate. The idea of having machines that are able to process certain cognition to come to a decision without the intervention of humans is the ultimate idea that is being pursued. Though the stage in which AI is able to completely outperform humans in its cognitive skills is yet to be achieved, there has been remarkable progress towards that area. This chapter aims to provide a brief introduction about AI and the area covered under the topic. Various algorithms are used in programming AI on machines such as evolutionary algorithms, genetic algorithms, and swarm intelligence. AI encompasses machine learning, which will be further discussed in this chapter. Furthermore, the impact of AI on society and futuristic predictions the chapter reviews

Using Artificial Intelligence in Wireless Sensor Routing Protocols

This paper represents a dissertation about how an artificial intelligence technique can be applied to wireless sensor networks. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded in these kind of networks. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore the performance of two very well known routing paradigms, directed diffusion and Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed

Introduction to Data Ethics

An Introduction to data ethics, focusing on questions of privacy and personal identity in the economic world as it is defined by big data technologies, artificial intelligence, and algorithmic capitalism. Originally published in The Business Ethics Workshop, 3rd Edition, by Boston Acacdemic Publishing / FlatWorld Knowledge

An Introduction to Artificial Intelligence

This chapter explores the evolution of artificial intelligence, starting with the first ideas of Alan Turing, going through the promises of its inception, and landing in our current state, when AI invokes a sense of power and awe. Next, the chapter will provide a summary of different technologies related to AI and machine learning, such as deep neural networks, to help the reader distinguish different terminologies. The chapter will end with a discussion of some potential tendencies concerning how AI may be used or evolve in the near future, and some questions about the technology in the long term

A new QoS routing algorithm based on self-organizing maps for wireless sensor networks

For the past ten years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, self-organizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore and compare the performance of two very well known routing paradigms, directed diffusion and Energy- Aware Routing, with our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes

Relationship Determinants between AI Technology Adoption Behavior and Performance of Software Enterprises

With the continuous progress of science and technology, the arrival of artificial intelligence subverts the traditional industries. Enterprises urgently need to carry out technological innovation to reduce costs. The introduction of artificial intelligence technology can reduce workload and improve development efficiency for software enterprises. Reduce operating costs. This paper takes the software enterprise as the research object, takes the artificial intelligence as the independent variable and the software development cost as the dependent variable. The hypothesis is proposed through the four intermediate variables of development efficiency, management innovation, product quality, labor force and the degree of introduction of artificial intelligence. A total of 332 valid questionnaires were collected by using electronic questionnaires. The sample data are analyzed by Smartpls 3.0 software, and the data are analyzed by Algorithm, Bootstrapping, cross multiplication, structural equation and other methods. The results show that AI has a significant positive impact on software development cost, a significant positive impact on product quality, a significant positive impact on labor force, a significant positive impact on development efficiency, a significant positive impact on management innovation, and a significant positive impact on software development cost. Labor has a significant positive impact on software development costs. Development efficiency has a significant positive impact on software development cost. Management innovation has a significant positive impact on software development cost. Product quality plays an intermediary role between the introduction of artificial intelligence and the cost of software development. Development efficiency also plays an intermediary role between the introduction of artificial intelligence and the cost of software development. From the research, we know that the introduction of AI can enrich the theories of process reengineering, process optimization and management decision-making, and can also find the factors that affect output performance from the perspective of technological innovation to provide reference for future research

Giving Neurons to Sensors: An Approach to QoS Management Through Artificial Intelligence in Wireless Networks

For the latest ten years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, selforganizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore the performance of two very well known routing paradigms, directed diffusion and Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes