scholarly journals A Survey of Planning and Learning in Games

2020 ◽  
Vol 10 (13) ◽  
pp. 4529
Author(s):  
Fernando Fradique Duarte ◽  
Nuno Lau ◽  
Artur Pereira ◽  
Luis Paulo Reis
Keyword(s):  
Artificial Intelligence ◽  
Video Games ◽  
Intelligent Agents ◽  
Learning In Games ◽  
Planning Techniques ◽  
Artificial Intelligence Research ◽  
Board Games ◽  
Human World ◽  
World Champion ◽  
Theoretical Foundations

In general, games pose interesting and complex problems for the implementation of intelligent agents and are a popular domain in the study of artificial intelligence. In fact, games have been at the center of some of the most well-known achievements in artificial intelligence. From classical board games such as chess, checkers, backgammon and Go, to video games such as Dota 2 and StarCraft II, artificial intelligence research has devised computer programs that can play at the level of a human master and even at a human world champion level. Planning and learning, two well-known and successful paradigms of artificial intelligence, have greatly contributed to these achievements. Although representing distinct approaches, planning and learning try to solve similar problems and share some similarities. They can even complement each other. This has led to research on methodologies to combine the strengths of both approaches to derive better solutions. This paper presents a survey of the multiple methodologies that have been proposed to integrate planning and learning in the context of games. In order to provide a richer contextualization, the paper also presents learning and planning techniques commonly used in games, both in terms of their theoretical foundations and applications.

scholarly journals The Game Is Not over Yet—Go in the Post-AlphaGo Era

Philosophies ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 37
Author(s):  
Attila Egri-Nagy ◽  
Antti Törmänen
Keyword(s):  
Artificial Intelligence ◽  
Computational Complexity ◽  
State Of The Art ◽  
The State ◽  
Combinatorial Complexity ◽  
Human Culture ◽  
Board Games ◽  
Human World ◽  
Catch Up ◽  
World Champion

The game of Go was the last great challenge for artificial intelligence in abstract board games. AlphaGo was the first system to reach supremacy, and subsequent implementations further improved the state of the art. As in chess, the fall of the human world champion did not lead to the end of the game. Now, we have renewed interest in the game due to new questions that emerged in this development. How far are we from perfect play? Can humans catch up? How compressible is Go knowledge? What is the computational complexity of a perfect player? How much energy is really needed to play the game optimally? Here, we investigate these and related questions with respect to the special properties of Go (meaningful draws and extreme combinatorial complexity). Since traditional board games have an important role in human culture, our analysis is relevant in a broader context. What happens in the game world could forecast our relationship with AI entities, their explainability, and usefulness.

Theoretical Foundations of the Automatic Production and Processing of Technical Reports

1979 ◽  
Vol 9 (3) ◽  
pp. 239-269 ◽  
Author(s):  
Robert De Beaugrande
Keyword(s):  
Artificial Intelligence ◽  
Computer Science ◽  
Computer System ◽  
Recent Progress ◽  
Automatic Production ◽  
Reading And Writing ◽  
Artificial Intelligence Research ◽  
Theoretical Foundations

The following treatise surveys the issues and approaches for designing a computer system capable of reading, understanding, and writing technical reports. Recent progress in computer science and artificial intelligence research is used to specify the nature of the modules in the system. The processing of a sample text is observed during the phases of reading and writing a report on the origin of sunspots. The author advances some proposals for correlating syntax and semantics of English from a procedural standpoint. The discussion is illustrated with structural diagrams.

scholarly journals Use of Artificial Intelligence and Machine Learning in Games

2020 ◽  
pp. 114-118
Author(s):  
Nachiket Jadhav ◽  
Aniket Matodkar ◽  
Anish Mandhare ◽  
Sujata Bhairnallykar
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Video Games ◽  
The Other ◽  
Hardware Support ◽  
Learning In Games ◽  
Game Play ◽  
Cost Efficient

With modern video games surpassing every set of expectations in terms of graphics, game play, mechanics and hardware support, Artificial Intelligence in video games has also come a long way, from when it was first implemented in 1951. Although every set of games has an AI unique to itself, many of the algorithms are now developed such that they can be implemented in various games without any major changes in coding. But this could lead to the players exploiting AI in a single game to break the other games as well. Though this could be easily fixed by changing some minor fragments of algorithms, it would very well be an efficient way of developing complex AI for many games at once. This paper focuses on providing a cost-efficient way to implement AI algorithms that would benefit most of the upcoming and future games that will depend on AI to make themselves more dynamic to the players. This is done by taking the examples of various AI algorithms implemented in games like Pacman, Dota2, Tom Clancy's- The Division and many more.

CONTENT OF TEACHING THE ELEMENTS OF ARTIFICIAL INTELLIGENCE IN A SCHOOL INFORMATICS COURSE

2020 ◽  
pp. 3-10
Author(s):  
I. V. Levchenko
Keyword(s):  
Artificial Intelligence ◽  
General Education ◽  
Extracurricular Activities ◽  
Information Technologies ◽  
Learning Experience ◽  
9Th Grade ◽  
Modern Information ◽  
Further Development ◽  
Form Variant ◽  
Theoretical Foundations

The article considers the feasibility of integrating artificial intelligence technologies into school education and identifies a problem in identifying didactic elements in the field of artificial intelligence, which must be mastered in a school informatics course. The purpose of the article is to propose variant of the content of teaching the elements of artificial intelligence for the general education of schoolchildren as part of the curricular and extracurricular activities in informatics. An analysis of the psychological, pedagogical and scientific-methodical literature in the field of artificial intelligence made it possible to identify the appropriateness of teaching schoolchildren the elements of artificial intelligence in the framework of a comprehensive informatics course, as the theoretical foundations of modern information technologies. Summarizing and systematizing the learning experience of schoolchildren in the field of artificial intelligence made it possible to form variant of the content of teaching the elements of artificial intelligence, which can be implemented in a compulsory informatics course for 9th grade, as well as in elective classes. The results of the study are the theoretical basis for the further development of the components of the methodological system of teaching the elements of artificial intelligence in a school informatics course. The research materials may be useful to specialists in the field of teaching informatics and to informatics teachers.

Dyadic Obligations over Complex Actions as Deontic Constraints in the Situation Calculus

2020 ◽  
Author(s):  
Jens Claßen ◽  
James Delgrande
Keyword(s):  
Artificial Intelligence ◽  
Deontic Logic ◽  
Action Theory ◽  
Prima Facie ◽  
Situation Calculus ◽  
Artificial Agents ◽  
Planning Techniques ◽  
Course Of Action ◽  
Reasoning About Action ◽  
The Given

With the advent of artificial agents in everyday life, it is important that these agents are guided by social norms and moral guidelines. Notions of obligation, permission, and the like have traditionally been studied in the field of Deontic Logic, where deontic assertions generally refer to what an agent should or should not do; that is they refer to actions. In Artificial Intelligence, the Situation Calculus is (arguably) the best known and most studied formalism for reasoning about action and change. In this paper, we integrate these two areas by incorporating deontic notions into Situation Calculus theories. We do this by considering deontic assertions as constraints, expressed as a set of conditionals, which apply to complex actions expressed as GOLOG programs. These constraints induce a ranking of "ideality" over possible future situations. This ranking in turn is used to guide an agent in its planning deliberation, towards a course of action that adheres best to the deontic constraints. We present a formalization that includes a wide class of (dyadic) deontic assertions, lets us distinguish prima facie from all-things-considered obligations, and particularly addresses contrary-to-duty scenarios. We furthermore present results on compiling the deontic constraints directly into the Situation Calculus action theory, so as to obtain an agent that respects the given norms, but works solely based on the standard reasoning and planning techniques.

scholarly journals A Survey of Encoding Techniques for Signal Processing in Spiking Neural Networks

2021 ◽  
Author(s):  
Daniel Auge ◽  
Julian Hille ◽  
Etienne Mueller ◽  
Alois Knoll
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Industrial Applications ◽  
Spiking Neural Networks ◽  
Biologically Inspired ◽  
Power Efficient ◽  
Signal Encoding ◽  
Uniform Nomenclature ◽  
Theoretical Foundations ◽  
Do So

AbstractBiologically inspired spiking neural networks are increasingly popular in the field of artificial intelligence due to their ability to solve complex problems while being power efficient. They do so by leveraging the timing of discrete spikes as main information carrier. Though, industrial applications are still lacking, partially because the question of how to encode incoming data into discrete spike events cannot be uniformly answered. In this paper, we summarise the signal encoding schemes presented in the literature and propose a uniform nomenclature to prevent the vague usage of ambiguous definitions. Therefore we survey both, the theoretical foundations as well as applications of the encoding schemes. This work provides a foundation in spiking signal encoding and gives an overview over different application-oriented implementations which utilise the schemes.

scholarly journals RECOMIA—a cloud-based platform for artificial intelligence research in nuclear medicine and radiology

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Elin Trägårdh ◽  
Pablo Borrelli ◽  
Reza Kaboteh ◽  
Tony Gillberg ◽  
Johannes Ulén ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Nuclear Medicine ◽  
Artificial Intelligence Research
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