Monthly Archives: July 2016

Microsoft, Minecraft, and AI: Project Malmo

In a previous post, I complimented Microsoft on their purchase of Minecraft. I ruminated on the potential for STEM and experiential learning it opens up, particularly with the addition of HoloLens and augmented reality. Recently, Microsoft announced the public availability of their Project Malmo platform that uses Minecraft to provide an interactive environment for development and testing of intelligent agents. This further illuminates Microsoft’s long-term plans for Minecraft.

In contrast to highly specific, applied AI, Project Malmo harnesses the almost unlimited exploration and experimentation possibilities of Minecraft as a research tool for general artificial intelligence. Agents can learn, comprehend, communicate, and do tasks in the Minecraft world. A mod for Minecraft provides an API for programming, and uses XML and JSON to hold representations of the world in computer memory. Agents can explore their surroundings, see and touch Minecraft blocks, take actions, and receive feedback from the environment. This enables reinforcement learning. Instead of just applying deductive, symbolic reasoning, agents can benefit from inductive (experiential) learning.

The potential benefits are compelling.

minecraft block

 

Sandbox development allows strategies and algorithms developed in the Minecraft world to be later moved to a much larger simulation environment, possibly on distributed systems and/or supercomputers. Computational agents do not require sensory augmentation or biological interfaces, since they connect ‘directly’ to the simulated world. The ability to ‘overclock’ the simulation frees agents from the limits of our time scale (they can ‘live’ many days in an hour of real time).

For remote sensing applications, such as planetary probes & rovers, the benefits are huge. Autonomous machines must be developed and tested before they are deployed. The time delay incurred by vast distance precludes ground-based control. By the time people on Earth receive video from Mars and send the command, “don’t drive off that cliff”, it’s far too late. The ‘smarts’ to navigate and make decisions locally must exist in the robot. Hazardous locations, even here on Earth, also require considerable autonomous learning and decision-making.

Collaboration and comparison between people and teams is possible with a common testing ground. Minecraft can be played as an individual, but the real power is that a Minecraft world can be hosted on a server, enabling many people, wherever they are, to experience and simultaneously participate in that Minecraft world. Players, agents, landscapes & artifacts, or even a combination can all exist and interact. This is much more like the natural world.

Project Malmo encourages public participation and involvement. It’s an open architecture that invites experimentation by all. This is somewhat similar to the citizen science movement, which not only provides the benefits of ‘crowdsourcing’ to scientific research, but also enhances public understanding of scientific methods. In the modern world, a pervasive, basic understanding of artificial intelligence would be of tremendous benefit.

The ability to go far beyond the development of a single agent also opens up the possibility for social simulations of almost limitless scale. Agent-based models have long shown their usefulness in the study of social interaction, from ant colonies to human nations and cultures. One example is the simulation of ancient civilizations. This could lead to an entirely new approach to deciphering Linear A, for example. I considered a much more vast model in Future Psychohistory. In 2011, when I wrote that article, I had a standard neural network model in mind, but if I were to write it today, I’d definitely go with intelligent agents.

The concept of agency is central in many areas of life science. Relational databases are far too static for life science – Cassandra for Life Science. The proper representation of life is not tabular, but associative. Dynamic systems interact, adapt, and even learn. This is the basis of evolution. Machinery as tiny as enzymes and ribosomes, and possibly even medical nano-robots in the near future, all require much more dynamic models to study.

Project Malmo offers major benefits for teaching computer programming. Different paradigms such as procedural, functional, object oriented, declarative, and concatenative are all suitable and helpful in the construction of agents. And of course, there’s one of my favourite hobby horses – constructionism. This only adds to the already expansive use of Minecraft in education.

And for game play itself, Project Malmo can be of great usefulness. Dangerous and tedious tasks can be handed off to agents, amplifying a human player’s efforts. Tutoring and nurturing AI agents is a good use of human intelligence — and it’s a lot of fun.

Greek Pattern 1

AI research and Minecraft now have a powerful and resourceful champion – nice.
I look forward to seeing the fruits of Project Malmo.

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