A computer scientist looks at game theory

I consider issues in distributed computation that should be of relevance to game theory. In particular, I focus on (a) representing knowledge and uncertainty, (b) dealing with failures, and (c) specification of mechanisms.Comment: To appear, Games and Economic Behavior. JEL classification numbers: D80, D8

Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

On The Foundations of Digital Games

Computers have lead to a revolution in the games we play, and, following this, an interest for computer-based games has been sparked in research communities. However, this easily leads to the perception of a one-way direction of influence between that the field of game research and computer science. This historical investigation points towards a deep and intertwined relationship between research on games and the development of computers, giving a richer picture of both fields. While doing so, an overview of early game research is presented and an argument made that the distinction between digital games and non-digital games may be counter-productive to game research as a whole

Complex Systems: A Survey

A complex system is a system composed of many interacting parts, often called agents, which displays collective behavior that does not follow trivially from the behaviors of the individual parts. Examples include condensed matter systems, ecosystems, stock markets and economies, biological evolution, and indeed the whole of human society. Substantial progress has been made in the quantitative understanding of complex systems, particularly since the 1980s, using a combination of basic theory, much of it derived from physics, and computer simulation. The subject is a broad one, drawing on techniques and ideas from a wide range of areas. Here I give a survey of the main themes and methods of complex systems science and an annotated bibliography of resources, ranging from classic papers to recent books and reviews.Comment: 10 page

Disordered Eating Habits and Theory of Mind in Undergraduate Students

Theory of mind, the ability to ascribe mental states to oneself and others, has intimate connections with mental disorders like autism and schizophrenia. Recent research has suggested a connection between eating disorders and theory of mind ability, but these findings have been mixed. The idea that disorders lie along a continuum (Johns & van Os, 2001) leads to the hypothesis that people with disordered eating habits will have a lesser theory of mind ability than those without. Data was collected on 25 undergraduate students at Butler University. Results showed a positive correlation between theory of mind and negative eating attitudes. Although the sample size was small, the present results suggest that individuals with more negative eating attitudes are better at understanding others’ mental states

Wittgenstein´s Critique of Gödel´s Incompleteness Results

It is often said that Gödel´s famous theorem of 1931 is\ud equal to the Cretian Liar, who says that everything that he\ud says is a lie. But Gödel´s result is only similar to this\ud sophism and not equivalent to it. When mathematicians\ud deal with Gödel´s theorem, then it is often the case that\ud they become poetical or even emotional: some of them\ud show a high esteem of it and others despise it. Wittgenstein\ud sees the famous Liar as a useless language game\ud which doesn´t excite anybody. Gödel´s first incompleteness\ud theorem shows us that in mathematics there are\ud puzzles which have no solution at all and therefore in\ud mathematics one should be very careful when one\ud chooses a puzzle on which one wants to work. Gödel´s\ud second imcompleteness theorem deals with hidden\ud contradictions – Wittgenstein shows a paradigmatic\ud solution: he simply shrugs his shoulders on this problem\ud and many mathematicians do so today as well. Wittgenstein\ud says than Gödel´s results should not be treated as\ud mathematical theorems, but as elements of the humanistic\ud sciences. Wittgenstein sees them as something which\ud should be worked on in a creative manner

Algorithmic Randomness as Foundation of Inductive Reasoning and Artificial Intelligence

This article is a brief personal account of the past, present, and future of algorithmic randomness, emphasizing its role in inductive inference and artificial intelligence. It is written for a general audience interested in science and philosophy. Intuitively, randomness is a lack of order or predictability. If randomness is the opposite of determinism, then algorithmic randomness is the opposite of computability. Besides many other things, these concepts have been used to quantify Ockham's razor, solve the induction problem, and define intelligence.Comment: 9 LaTeX page