4,128 research outputs found

    A NPC Behaviour Definition System for Use by Programmers and Designers

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    In this paper we describe ZBL/0, a scripting system for defining NPC (Non Player Character) behaviour in FPS (First Person Shooter) games. ZBL/0 has been used to illustrate the use of scripting systems in computer games in general and the scripting of NPC behaviour in particular in the context of a book on game development. Many novice game designers have clear ideas about how the computer game they imagine should work but have little knowledge – if any – about how their ideas can be implemented. This is why books on game creation (design, programming etc.), as well as all-in-one game creation systems – especially designed for ease of use and intended for an amateur audience – enjoy great popularity. A large proportion of these books however merely present solutions in the form of descriptions and explanations of specific implementations with inadequate explanations of principles. While this may benefit rapid application development it often does not lead to a deeper understanding of the underlying concepts. The understanding of rule-based behaviour definition through simple scripting in computer games and the development of such scripts by programmers and designers is what we aim to address with the ZBL/0 system

    Understanding Evolutionary Potential in Virtual CPU Instruction Set Architectures

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    We investigate fundamental decisions in the design of instruction set architectures for linear genetic programs that are used as both model systems in evolutionary biology and underlying solution representations in evolutionary computation. We subjected digital organisms with each tested architecture to seven different computational environments designed to present a range of evolutionary challenges. Our goal was to engineer a general purpose architecture that would be effective under a broad range of evolutionary conditions. We evaluated six different types of architectural features for the virtual CPUs: (1) genetic flexibility: we allowed digital organisms to more precisely modify the function of genetic instructions, (2) memory: we provided an increased number of registers in the virtual CPUs, (3) decoupled sensors and actuators: we separated input and output operations to enable greater control over data flow. We also tested a variety of methods to regulate expression: (4) explicit labels that allow programs to dynamically refer to specific genome positions, (5) position-relative search instructions, and (6) multiple new flow control instructions, including conditionals and jumps. Each of these features also adds complication to the instruction set and risks slowing evolution due to epistatic interactions. Two features (multiple argument specification and separated I/O) demonstrated substantial improvements int the majority of test environments. Some of the remaining tested modifications were detrimental, thought most exhibit no systematic effects on evolutionary potential, highlighting the robustness of digital evolution. Combined, these observations enhance our understanding of how instruction architecture impacts evolutionary potential, enabling the creation of architectures that support more rapid evolution of complex solutions to a broad range of challenges

    Cognitive architectures as Lakatosian research programmes: two case studies

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    Cognitive architectures - task-general theories of the structure and function of the complete cognitive system - are sometimes argued to be more akin to frameworks or belief systems than scientific theories. The argument stems from the apparent non-falsifiability of existing cognitive architectures. Newell was aware of this criticism and argued that architectures should be viewed not as theories subject to Popperian falsification, but rather as Lakatosian research programs based on cumulative growth. Newell's argument is undermined because he failed to demonstrate that the development of Soar, his own candidate architecture, adhered to Lakatosian principles. This paper presents detailed case studies of the development of two cognitive architectures, Soar and ACT-R, from a Lakatosian perspective. It is demonstrated that both are broadly Lakatosian, but that in both cases there have been theoretical progressions that, according to Lakatosian criteria, are pseudo-scientific. Thus, Newell's defense of Soar as a scientific rather than pseudo-scientific theory is not supported in practice. The ACT series of architectures has fewer pseudo-scientific progressions than Soar, but it too is vulnerable to accusations of pseudo-science. From this analysis, it is argued that successive versions of theories of the human cognitive architecture must explicitly address five questions to maintain scientific credibility
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