Evolving Useful Objects
by David Orban on Sep 21, 2007
- 6,179 views
The social spaces of online worlds thrive through object design and interaction. Carefully chosen object categories can usefully evolve through genetic algorithms, and user interaction analysis. Once a...
The social spaces of online worlds thrive through object design and interaction. Carefully chosen object categories can usefully evolve through genetic algorithms, and user interaction analysis. Once a desired threshold is reached, the object can be distributed in-world, and in the future manifactured on-demand via 3d printing personal fabrication methods.
Talk held at CMP's Life 2.0 Summit on 21 September 2007, in Second Life.
Accessibility
Categories
Tags
More...Upload Details
Uploaded via SlideShare as Microsoft PowerPoint
Usage Rights
Statistics
- Favorites
- 7
- Downloads
- 157
- Comments
- 14
- Embed Views
- Views on SlideShare
- 6,024
- Total Views
- 6,179
tanujapatare
Instead of concentrating on a single solution, if we look at the set of possible competing social networks, we realize that they compete for our attention, and it is the varying degree of our attention that makes them successful, not only through the data we provide to them daily.
The same is true in online worlds, with the added value of built-in interaction and creativity. 4 years ago Reply
Different groups receive variations on the objects, which then have to prove themselves, to survive to the next generation, by showing to be useful.
Variations can be relative to shape, size, color, movement of components, means of interaction. The source of variation can be, depending on the nature of the parameter, a table of preset values, or, in case we want to change the functionalities of the objects as well, sets of algorithms.
The definition of usefulness, our utility function, must also adapt to the nature of the object, to the realistic expectations of how, when, and how frequently a given object is used. This function is also not necessarily linear, since the specific community's adoption of the object, or even its dependency on it can change.
Taking the best performing variations, and providing further changes in the successive cycle of seeding takes the entire process one step ahead, towards the goal of maximizing the utility function.
Let's see a couple of examples, of objects being evolved on Vulcano! 4 years ago Reply
The button bar for meetings enables a participant as she listens to a speaker to show agreement, disagreement, not understanding, or asking to talk, via balloons over her head which are visible to all participants. The speaker's adaptation to these visual clues, changes the audience's reactions, and all of this is recorded, to make sure that better speakers have the chance to talk. At the end of the meeting a transcript, similar to the original soundtrack of chemical films, is available, only this time the symbols track the level of understanding among the participants, and let the group pinpoint problem areas in the collaboration.
The 3d mind maps are an analogue of traditional bidimentional mind mapping software, and let a group collaborate through complex concept visualizations, where nodes, links, colors, shapes, all represent meaning, and where the various participants enrich their understanding of the subject matter through the common work of shaping the 3d mind map.
In both cases the variations in the objects's nature and behavior can be analyzed, having a positive or negative impact on their use. In the case of the button bar, the frequency of the use of the visual clues during a meeting can be chosen as a value we want to maximize. In the case of the 3d mind map, not only the size of the map, but at what level of collaboration it has been designed, how eagerly the people part of the group intervene to add parts to the map themselves.
These are naturally just two examples of the evolutionary approach, where much more further research is needed... 4 years ago Reply
We want to properly map, and classify object categories, to better understand what are the indicators that make them a suitable starting point for the evolutionary approach. If possible, encompass further and further categories, via changing our methods themselves.
Make sure that we do not bias our evolutionary trees because of the relatively small sample size we work with today, of a few dozen participants, but by virally propagating objects that are attractive in form and function to start with, we can learn from a larger statistical pool.
We need a better understanding of how to automatically link the changes in the form of the objects to functional algorithmic changes. Since we are today restricting ourselves to objects that are useable at human scales, and via well known methods of interaction, this limits the freedoms of expression in object shape of the eventually emerging algorithms.
The approach must remain scalable as more object classes participate, and we need to keep an eye open for eventual emergent properties, which repeatedly show up accross the classes.
So we have a lot on our hands, but there is also a farther our vision... 4 years ago Reply
Can a given evolved object be then turned into its physical equivalent?
The technology of 3d printers for personal fabrication is rapidly emerging, with dozens of firms working on solutions, quickly approaching consumer prices, and enabling the physical creation of ever more complex objects.
What would be the advantages of our evolutionary approach to the production of physical goods?
We would be able and actually eliminate many of the inefficiencies that I mentioned at the beginning, when I described the limits of the industrial mass production system. Ideas would start to be tested, on vastly larger groups than the focus groups of today, in numbers that are unaffordable now. Production would not start, unless an object has proven itself not only useful, but actually invaluable, and it would be produced at the people that would want, and need them, eliminating the costs of transportation in the meantime.
The perspectives of a similar system to emerge can be several years, but as the consumer classes of China and India emerge, and aim to achieve the levels of consumption and material wealth of the Western societies of today, the resources of the planet are not enough to sustain a wasteful process!
The communities that will form around the needs, and creative experimentation of groups formerly called consumers, are going to be enthusiastic, and energetic, similarly to today's bloggers documenting the unpacking of the latest gadget,, but on a much more effective level. The co-design of products will blur further the distinction between producers and consumers, and the universal access to the creations will add considerable welth to our societies! 4 years ago Reply
Computationally very intensive, while originally introduced already in the '50s, it is only since the '90s that genetic programming has become feasible, and started to produce either original solutions to the stated problems, or actually independently re-discovered patented inventions.
It is also possible to imagine evolutionary approaches to the design of genetic programming systems themselves, which lead to an interesting theoretical explosion of recursive improvement: but that is the subject of an other of my favorite talks... the Technological Singularity! :) 4 years ago Reply
But, as we have seen from the reports of the press lamenting the desert-like nature of too many places in-world, the main value of the online world resides in the communities that form, which in turn are precious because of the interaction they offer, and the creativity they unleash.
What we also know, is that within Second Life every object created is connected to the internet, per definition. If it were not so, we would not even see it! This is the opposite of the physical world, where our desire of connecting every object is a long and difficult task, which will take several years, or decades to be realized.
So, let's now put it all together! 4 years ago Reply
Computationally very intensive, while originally introduced already in the '50s, it is only since the '90s that genetic programming has become feasible, and started to produce either original solutions to the stated problems, or actually independently re-discovered patented inventions.
It is also possible to imagine evolutionary approaches to the design of genetic programming systems themselves, which lead to an interesting theoretical explosion of recursive improvement: but that is the subject of an other of my favorite talks... the Technological Singularity! :)
So let's see instead the third component of our system, the social spaces... 4 years ago Reply