This document proposes two methods for enhancing voxel detail in 3D games: recursive subdivision and direct resampling. Recursive subdivision works by recursively subdividing each voxel into smaller voxels, while direct resampling works by directly resampling the voxel grid at a higher resolution. These methods were inspired by pixel art scaling algorithms and could allow for decoupling voxel modification from rendering to enable new game mechanics. The document discusses implications and related concerns for implementing these methods in games.
This Ppt is based on the Raster animation . It explains u ablout a brief idea bout the Raster Graphics its Working with Real time Animation Examples that are used in our day to day life.
The following points are covered in this ppt
1. Introduction
2. Working of Raster Animation
3. Types of Raster Animations Modern and Traditional
4. Examples
5.Applications
6. Advantages
7. Disadvantages
Company of Heroes 2 (COH2) Rendering Technology: The cold facts of recreating...Daniel Barrero
Presentation at KGC2013 about the techniques developed for COH2 to reproduce the harsh winter conditions of the eastern front of World War 2. It covers the technology developed for dynamic snow and ice rendering, what worked what didn't. It covers as well the lighting and conversion of the COH1 engine from forward to a deferred renderer.
This Ppt is based on the Raster animation . It explains u ablout a brief idea bout the Raster Graphics its Working with Real time Animation Examples that are used in our day to day life.
The following points are covered in this ppt
1. Introduction
2. Working of Raster Animation
3. Types of Raster Animations Modern and Traditional
4. Examples
5.Applications
6. Advantages
7. Disadvantages
Company of Heroes 2 (COH2) Rendering Technology: The cold facts of recreating...Daniel Barrero
Presentation at KGC2013 about the techniques developed for COH2 to reproduce the harsh winter conditions of the eastern front of World War 2. It covers the technology developed for dynamic snow and ice rendering, what worked what didn't. It covers as well the lighting and conversion of the COH1 engine from forward to a deferred renderer.
BMOSLFGEMW: A Spectrum of Game Engine Architecturesrndmcnlly
A good engine hides the problems you don’t care about and amplifies your ability to tackle the ones you do care about.
A bad engine brings out new problems and weighs you down as you go about your other business.
Use/make the right tool for the job, even if it doesn’t look like a traditional “game engine”.
Ludocore: A Logical Game Engine for Modeling Videogamesrndmcnlly
Abstract—LUDOCORE is a logical “game engine”, linking
game rules as reasoned about by game designers to the formal
logic used by automated reasoning tools in AI. A key challenge
in designing this bridge is engineering a concise, safe, and
flexible representation that is compatible with the semantics of
the games that logical models created with our engine intend
to represent.
Building on the event calculus, a formalism for reasoning
about state and events over time, and a set of common structures
and idioms used in modeling games, we present a tool that is
capable of generating gameplay traces that illustrate the game’s
dynamic behavior. It supports incremental modeling of player
and non-player entities in the game world, modification of
game rules without extensive non-local changes, and exploratory
temporal and structural queries. In addition, its logical models
can support play as real-time, graphical games with minimal
user-interface description.
Variations Forever: Flexibly Generating Rulesets from a Sculptable Design Spa...rndmcnlly
Abstract—Variations Forever is a novel game in which the player explores a vast design space of mini-games. In this pa-per, we present the procedural content generation research which makes the automatic generation of suitable game rulesets possible. Our generator, operating in the domain of code-like game content exploits answer-set programming as a means to declaratively represent a generative space as distinct from the domain-independent solvers which we use to enumerate it. Our generative spaces are powerfully sculptable using concise, declarative rules, allowing us to embed significant design know-ledge into our ruleset generator as an important step towards a more serious automation of whole game design process.
The intelligent game designer: Game design as a new domain for automated disc...rndmcnlly
Designing video games is commonly understood to be a creative task,
drawing on a designer's talent, inspiration, and personal experience.
The last ten years have seen multiple calls from the design community to
produce reusable knowledge about the structure of games and the design
process itself. These designers would like to establish a standardized
language and libraries of design patterns so that the next generation of
designers can benefit from the best of past generations. The
realization of such a move can be read as a transition from thinking
about game design as a playable-artifact creation process to a science
of play in which we might see the designer's goal as discovering new
gameplay structures and their production of concrete games as a side
effect of this process.
Thirty years ago, a similar-yet-disconnected thread of research in
artificial intelligence was just being born. First marked by Doug
Lenat's AM (an “automated mathematician”), discovery systems aim to
automatically produce new and interesting knowledge. Such systems
contrast sharply with the then-popular expert systems which applied
fixed libraries of “expert” knowledge to various tasks. Discovery
systems, which have commonly operated in the domains of natural science
and mathematics, are now seen as distant ancestors of contemporary,
statistical machine learning techniques which find extensive application
in a wide array of industries. Contrary to the current emphasis on the
optimal learning statistical descriptions of data, some recent
developments in machine learning, specifically combined abductive and
inductive logic learning systems, are bringing the production and
revision of structured, symbolic knowledge back into focus.
Simultaneous research in computational creativity is making inroads into
modeling the creative process and the production of creative artifacts.
This is the question I aim to answer: If we squint a bit to see game
design as the science-of-play that some designers imagine it to be, can
we build a discovery system that really works in the domain of game
design? Can we build an intelligent game designer?
In my thesis proposal I lay out a plan to build an intelligent game
designer that learns from the process of game design, including the
observation of human players, and exports newly discovered design
knowledge. This will require an operationalization of game design as an
automatable, scientific process and a detailed re-synthesis of the
creative design of expressive artifacts as a knowledge-seeking effort.
BMOSLFGEMW: A Spectrum of Game Engine Architecturesrndmcnlly
A good engine hides the problems you don’t care about and amplifies your ability to tackle the ones you do care about.
A bad engine brings out new problems and weighs you down as you go about your other business.
Use/make the right tool for the job, even if it doesn’t look like a traditional “game engine”.
Ludocore: A Logical Game Engine for Modeling Videogamesrndmcnlly
Abstract—LUDOCORE is a logical “game engine”, linking
game rules as reasoned about by game designers to the formal
logic used by automated reasoning tools in AI. A key challenge
in designing this bridge is engineering a concise, safe, and
flexible representation that is compatible with the semantics of
the games that logical models created with our engine intend
to represent.
Building on the event calculus, a formalism for reasoning
about state and events over time, and a set of common structures
and idioms used in modeling games, we present a tool that is
capable of generating gameplay traces that illustrate the game’s
dynamic behavior. It supports incremental modeling of player
and non-player entities in the game world, modification of
game rules without extensive non-local changes, and exploratory
temporal and structural queries. In addition, its logical models
can support play as real-time, graphical games with minimal
user-interface description.
Variations Forever: Flexibly Generating Rulesets from a Sculptable Design Spa...rndmcnlly
Abstract—Variations Forever is a novel game in which the player explores a vast design space of mini-games. In this pa-per, we present the procedural content generation research which makes the automatic generation of suitable game rulesets possible. Our generator, operating in the domain of code-like game content exploits answer-set programming as a means to declaratively represent a generative space as distinct from the domain-independent solvers which we use to enumerate it. Our generative spaces are powerfully sculptable using concise, declarative rules, allowing us to embed significant design know-ledge into our ruleset generator as an important step towards a more serious automation of whole game design process.
The intelligent game designer: Game design as a new domain for automated disc...rndmcnlly
Designing video games is commonly understood to be a creative task,
drawing on a designer's talent, inspiration, and personal experience.
The last ten years have seen multiple calls from the design community to
produce reusable knowledge about the structure of games and the design
process itself. These designers would like to establish a standardized
language and libraries of design patterns so that the next generation of
designers can benefit from the best of past generations. The
realization of such a move can be read as a transition from thinking
about game design as a playable-artifact creation process to a science
of play in which we might see the designer's goal as discovering new
gameplay structures and their production of concrete games as a side
effect of this process.
Thirty years ago, a similar-yet-disconnected thread of research in
artificial intelligence was just being born. First marked by Doug
Lenat's AM (an “automated mathematician”), discovery systems aim to
automatically produce new and interesting knowledge. Such systems
contrast sharply with the then-popular expert systems which applied
fixed libraries of “expert” knowledge to various tasks. Discovery
systems, which have commonly operated in the domains of natural science
and mathematics, are now seen as distant ancestors of contemporary,
statistical machine learning techniques which find extensive application
in a wide array of industries. Contrary to the current emphasis on the
optimal learning statistical descriptions of data, some recent
developments in machine learning, specifically combined abductive and
inductive logic learning systems, are bringing the production and
revision of structured, symbolic knowledge back into focus.
Simultaneous research in computational creativity is making inroads into
modeling the creative process and the production of creative artifacts.
This is the question I aim to answer: If we squint a bit to see game
design as the science-of-play that some designers imagine it to be, can
we build a discovery system that really works in the domain of game
design? Can we build an intelligent game designer?
In my thesis proposal I lay out a plan to build an intelligent game
designer that learns from the process of game design, including the
observation of human players, and exports newly discovered design
knowledge. This will require an operationalization of game design as an
automatable, scientific process and a detailed re-synthesis of the
creative design of expressive artifacts as a knowledge-seeking effort.
The intelligent game designer: Game design as a new domain for automated disc...
Two Methods for Voxel Detail Enhancement
1. Two Methods for Voxel Detail
Enhancement
Adam M. Smith
adam.smith@hackerdojo.com
@rndmcnlly
2. Two Methods for Voxel Detail Enhancement
Adam M. Smith (presenter)
expressiveintelligencestudio
UC Santa Cruz
amsmith@soe.ucsc.edu
PCGames 2011 – Bordeaux, France
4. Exploratory Design
• Design
– Analysis × Synthesis
• Exploration
– travelling for the purpose of discovery
• Exploratory Design:
– Extracting interesting nuggets
– Building new components out of them
– Examining implication for design of new artifacts
Two Methods for Voxel Detail Enhancement 4
5. Where does exploratory design
happen?
Location Events
The Independent
Game Jam
SuperHappyDevHouse
Hacker Dojo
Mountain View, CA, USA
“Hacker Dojo is a community
center for hackers and thinkers South Bay Game Jam
to meet, discuss, learn, create,
build and play.”
Two Methods for Voxel Detail Enhancement 5
7. Woxel’s a Voxel?
Pixels in Wolfenstein 3D Voxels in Voxelstein 3D
(voxel: a colored cube in space)
(pixel: a colored square on a plane)
Two Methods for Voxel Detail Enhancement 7
8. Voxels in Action
• Minecraft
– Player-created architecture
• Ace of Spades
– Combat on top of player-created architecture
• Voxatron
– Retro-inspired arcade, bulk destruction
• Atomontage
– Photorealism, limited editing
Two Methods for Voxel Detail Enhancement 8
17. Decoupling
Enhancement
Rendering
Perception
Two Methods for Voxel Detail Enhancement 17
18. Exploring a Design Space
Dwarf Fortress (2006) Minecraft (2009) Terraria (
Wolfenstein 3D (1992) Voxelstein (2008) Ace of Spades (2011)
Voxatron (201x)
Wolfenstein (2009)
??? (20xx)
Braid (2008)
Hardware-accelerated
Voxel detail enhancement
voxel rendering engines
Hardware-accelerated
Pixel art scaling algorithms
triangle rendering engines
Two Methods for Voxel Detail Enhancement 18
19. Related Concerns
• Visibility
– Ignore the voxel unless it has a different neighbor
• Computational Complexity
– Terrains are 2D manifolds only n2 of n3 are visible
• Neighbor Dependence and Caching
– Deterministic, finite domain – memoize it!
• Physics
– Voxel normals only point in grid directions…
• Lighting
– Emit many wandering snowflakes, they each lives long
enough with hitting terrain, accumulate intensity
Two Methods for Voxel Detail Enhancement 19