Extensions to the Estimation Calculus

Walther’s estimation calculus was designed to prove the termination of functional programs, and can also be used to solve the similar problem of proving the well-foundedness of induction rules. However, there are certain features of the goal formulae which are more common to the problem of induction rule well-foundedness than the problem of termination, and which the calculus cannot handle. We present a sound extension of the calculus that is capable of dealing with these features. The extension develops Walther’s concept of an argument bounded function in two ways: firstly, so that the function may be bounded below by its argument, and secondly, so that a bound may exist between two arguments of a predicate. Our calculus enables automatic proofs of the well-foundedness of a large class of induction rules not captured by the original calculus

The Dynamic Creation of Induction Rules Using Proof Planning

Centre for Intelligent Systems and their ApplicationsA key problem in automating proof by mathematical induction is choosing an induction rule suitable for a given conjecture. Since Boyer & Moore’s NQTHM system the standard approach has been based on recursion analysis, which uses a combination of induction rules based on the relevant recursive function definitions. However, there are practical examples on which such techniques are known to fail. Recent research has tried to improve automation by delaying the choice of inductive rule until later in the proof, but these techniques suffer from two serious problems. Firstly, a lack of search control: specifically, in controlling the application of ‘speculative’ proof steps that partially commit to a choice of induction rule. Secondly, a lack of generality: they place significant restrictions on the form of induction rule that can be chosen. In this thesis we describe a new delayed commitment strategy for inductive proof that addresses these problems. The strategy dynamically creates an appropriate induction rule by proving schematic proof goals, where unknown rule structure is represented by meta-variables which become instantiated during the proof. This is accompanied by a proof that the generated rule is valid. The strategy achieves improved control over speculative proof steps via a novel speculation critic. It also generates a wider range of useful induction rules than other delayed commitment techniques, partly because it removes unnecessary restrictions on the individual proof cases, and partly because of a new technique for generating the rule’s overall case structure. The basic version of the strategy has been implemented using the lamdaClam proof planner. The system was extended with a novel proof critics architecture for this purpose. An evaluation shows the strategy is a useful and practical technique, and demonstrates its advantages

Towards generating novel games using conceptual blending

We sketch the process of creating a novel video game by blending two video games specified in the Video Game Description Language (VGDL), following the COINVENT computational model of conceptual blending. We highlight the choices that need to be made in this process, and discuss the prospects for a computational game designer based on blending

Playing NetHack with LLMs: Potential & Limitations as Zero-Shot Agents

Large Language Models (LLMs) have shown great success as high-level planners for zero-shot game-playing agents. However, these agents are primarily evaluated on Minecraft, where long-term planning is relatively straightforward. In contrast, agents tested in dynamic robot environments face limitations due to simplistic environments with only a few objects and interactions. To fill this gap in the literature, we present NetPlay, the first LLM-powered zero-shot agent for the challenging roguelike NetHack. NetHack is a particularly challenging environment due to its diverse set of items and monsters, complex interactions, and many ways to die. NetPlay uses an architecture designed for dynamic robot environments, modified for NetHack. Like previous approaches, it prompts the LLM to choose from predefined skills and tracks past interactions to enhance decision-making. Given NetHack's unpredictable nature, NetPlay detects important game events to interrupt running skills, enabling it to react to unforeseen circumstances. While NetPlay demonstrates considerable flexibility and proficiency in interacting with NetHack's mechanics, it struggles with ambiguous task descriptions and a lack of explicit feedback. Our findings demonstrate that NetPlay performs best with detailed context information, indicating the necessity for dynamic methods in supplying context information for complex games such as NetHack

Danesh: Helping Bridge The Gap Between Procedural Generators And Their Output

Procedural content generation is more popular than ever among game developers, but understanding, adjusting and perfecting a procedural generator is difficult for newcomers and experts alike. In this paper we present Danesh, an intelligent tool we are building to help developers of all skill levels explore, improve and understand procedural generators. We discuss the structure of the tool, report on the techniques used, and lay out the future of the project

The ANGELINA videogame design system, part II

Procedural content generation is generally viewed as a means to an end – a tool employed by designers to overcome technical problems or achieve a particular design goal. When we move from generating single parts of games to automating the entirety of their design, however, we find ourselves facing a far wider and more interesting set of problems than mere generation. When the designer of a game is a piece of software, we face questions about what it means to be a designer, about Computational Creativity, and about how to assess the growth of these automated game designers and the value of their output. Answering these questions can lead to new ideas in how to generate content procedurally, and produce systems that can further the cutting edge of game design. This paper describes work done to take an automated game designer and advance it towards being a member of a creative community. We outline extensions made to the system to give it more autonomy and creative independence, in order to strengthen claims that the software is acting creatively. We describe and reflect upon the software’s participation in the games community, including entering two game development contests, and show the opportunities and difficulties of such engagement. We consider methods for evaluating automated game designers as creative entities, and underline the need for automated game design to be a major frontier in future games research

Automating Game Design In Three Dimensions

We describe ANGELINA-5, a new iteration of the AN- GELINA framework for investigating and building software which automates the process of videogame design. ANGELINA-5 is the first automated game design tool that produces 3D games. We outline here the system’s structure, the challenges inherent in building an auto- mated game designer in a modern game engine, and we discuss the future research directions for the project

The ANGELINA Videogame Design System, Part I

Automatically generating content for videogames has long been a staple of game development and the focus of much successful research. Such forays into content generation usually concern themselves with producing a specific game component, such as a level design. This has proven a rich and challenging area of research, but in focusing on creating separate parts of a larger game, we miss out on the most challenging and interesting aspects of game development. By expanding our scope to the automated design of entire games, we can investigate the relationship between the different creative tasks undertaken in game development, tackle the higher-level creative challenges of game design, and ultimately build systems capable of much greater novelty, surprise and quality in their output. This paper, the first in a series of two, describes two case studies in automating game design, proposing cooperative coevolution as a useful technique to use within systems that automate this process. We show how this technique allows essentially separate content generators to produce content that complements each other. We also describe systems that have used this to design games with subtle emergent effects. After introducing the technique and its technical basis in this paper, in the second paper in the series we discuss higher level issues in automated game design, such as potential overlap with computational creativity and the issue of evaluation