Intelligence pertains to the ability to make appropriate decisions in light of specific goals and to adapt behavior to meet those goals in a range of environments. Mathematical games provide a framework for studying intelligent behavior in models of real-world settings or restricted domains. The behavior of alternative strategies in these games is defined by each individual’s stimulus-response mapping. Limiting these behaviors to linear functions of the environmental conditions renders the results to be little more than a façade: Effective decision making in any complex environment almost always requires nonlinear stimulus-response mappings. The obstacle then comes in choosing the appropriate representation and learning algorithm. Neural networks and evolutionary algorithms provide useful means for addressing these issues. This paper describes efforts to hybridize neural and evolutionary computation to learn appropriate strategies in zeroand nonzero-sum games, including the iterated prisoner’s dilemma, tic-tac-toe, and checkers. With respect to checkers, the evolutionary algorithm was able to discover a neural network that can be used to play at a near-expert level without injecting expert knowledge about how to play the game. The implications of evolutionary learning with respect to machine intelligence are also discussed. It is argued that evolution provides the framework for explaining naturally occurring intelligent entities and can be used to design machines that are also capable of intelligent behavior.

this paper I shall make a case for a dynamic semiotics. I list a set of phenomena that are difficult to understand in standard theories, and suggest a model borrowed from theories of complex dynamic systems. Since such theories rely on processes of self-organization that often defy analytical treatment, I use small computational models for assessing the empirical consequences of the theories.

Women pursue education and careers in computer science far less frequently than men do. In 1990, only 13% of PhDs in computer science went to women, and only 7.8% of computer science professors were female. Additionally, the percentage of female computer science students appears to be increasing at only a slow rate or even decreasing. Apart from ethical concerns at women's lack of participation in computer science, the demographics of the country are such that the United States will not have enough engineers and scientists unless underrepresented groups increase their participation. This report examines the influences against a woman's pursuing a career in a technical field, particularly computer science. Such factors include the different ways in which boys and girls are raised, the stereotypes of female engineers, subtle biases that females face, problems resulting from working in predominantly male environments, and sexual biases in language. Finally, I discuss effective and ineffec...

this article, we examine both shape and color information, and document transformational techniques in these domains by applying them to perceived "dimensions" of the human face. The examples considered here are restricted to manipulations of the facial dimensions of age and gender, but the transformational processes apply to instances of any homogeneous object class. For example, Knuth's idea of a Metafont

The Iterated Prisoner's Dilemma (IPD) has been an effective model of social, biological and political interaction for nearly 40 years. In the traditional definition of the game, constraints are provided that limit the cooperation between players to mutual cooperation, i.e. both players deciding to "cooperate" on a single play. This paper demonstrates that by modifying the traditional constraints, successful strategies must embody the ability to coordinate their interactions over several consecutive plays, a much more complex and potentially more interesting behavior. This form of interaction is termed nonmutual cooperation. This paper demonstrate the evolution of non-mutually cooperative agents, represented as Finite State Machines, under two distinct payoff schemes and discusses the implications of these results.

This paper introduces and presents a solution to the "Escherization" problem: given a closed figure in the plane, find a new closed figure that is similar to the original and tiles the plane. Our solution works by using a simulated annealer to optimize over a parameterization of the "isohedral" tilings, a class of tilings that is flexible enough to encompass nearly all of Escher's own tilings, and yet simple enough to be encoded and explored by a computer. We also describe a representation for isohedral tilings that allows for highly interactive viewing and rendering. We demonstrate the use of these tools---along with several additional techniques for adding decorations to tilings---with a variety of original ornamental designs. CR Categories: I.3.5 [Computational Geometry and Object Modeling]: Geometric algorithms, languages and systems; I.3.8 [Computer Graphics]: Applications; J.5 [Arts and Humanities]: Fine arts; J.6 [Computer-Aided Engineering]: Computer-aided design (CAD). Keywo...

and have found that it is complete and satisfactory in all respects, and that any and all revisions required by the final examining committee have been made.

The Letter Spirit project is an attempt to model central aspects of human high-level perception and creativity on a computer, focusing on the creative act of artistic letter-design. The aim is to model the process of rendering the 26 lowercase letters of the roman alphabet in many different, internally coherent styles. Two important and orthogonal aspects of letterforms are basic to the project: the categorical sameness possessed by instances of a single letter in various styles (e.g., the letter `a' in Baskerville, Palatino, and Helvetica) and the stylistic sameness possessed by instances of various letters in a single style (e.g., the letters `a', `b', and `c' in Baskerville). Starting with one or more seed letters representing the beginnings of a style, the program will attempt to create the rest of the alphabet in such a way that all 26 letters share the same style, or spirit. Letters in the domain are formed exclusively from straight segments on a grid in order to make decisions ...

. The Letter Spirit project explores the creative act of artistic letter-design. The aim is to model how the 26 lowercase letters of the roman alphabet can be rendered in many different but internally coherent styles. Viewed from a distance, the behavior of the program can be seen to result from the interaction of four emergent agents working together to form a coherent style and to design a complete alphabet: the Imaginer (which plays with the concepts behind letterforms), the Drafter (which converts ideas for letterforms into graphical realizations), the Examiner (which combines bottom-up and top-down processing to perceive and categorize letterforms), and the Adjudicator (which perceives and dynamically builds a representation of the evolving style). Creating a gridfont is an iterative process of guesswork and evaluation carried out by the four agents. This process is the "central feedback loop of creativity". Implementation of Letter Spirit is just beginning. This paper outlines ou...

: : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : xiii I Introduction : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 1 A. Why Play Games? : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 2 B. Selective Search and Brute Force Search : : : : : : : : : : : : : : : : : 4 C. Game Learning : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 6 D. Two-Person, Deterministic, Zero-Sum Board Games of Perfect Information : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 7 E. Rule Learning Versus Strategy Learning : : : : : : : : : : : : : : : : : 8 F. Overview : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 9 II Search and Learning : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 11 A. The Need for Search : : : : : : : : : : : : : : : : : : : : : : : : : : : : 12 B. Search Pathology : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 15 C. Learning an Evaluation Function : : : : ...